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Diffstat (limited to 'third_party/python/setuptools/pkg_resources/_vendor/typing_extensions.py')
| -rw-r--r-- | third_party/python/setuptools/pkg_resources/_vendor/typing_extensions.py | 2209 |
1 files changed, 2209 insertions, 0 deletions
diff --git a/third_party/python/setuptools/pkg_resources/_vendor/typing_extensions.py b/third_party/python/setuptools/pkg_resources/_vendor/typing_extensions.py new file mode 100644 index 0000000000..ef42417c20 --- /dev/null +++ b/third_party/python/setuptools/pkg_resources/_vendor/typing_extensions.py @@ -0,0 +1,2209 @@ +import abc +import collections +import collections.abc +import functools +import operator +import sys +import types as _types +import typing + + +__all__ = [ + # Super-special typing primitives. + 'Any', + 'ClassVar', + 'Concatenate', + 'Final', + 'LiteralString', + 'ParamSpec', + 'ParamSpecArgs', + 'ParamSpecKwargs', + 'Self', + 'Type', + 'TypeVar', + 'TypeVarTuple', + 'Unpack', + + # ABCs (from collections.abc). + 'Awaitable', + 'AsyncIterator', + 'AsyncIterable', + 'Coroutine', + 'AsyncGenerator', + 'AsyncContextManager', + 'ChainMap', + + # Concrete collection types. + 'ContextManager', + 'Counter', + 'Deque', + 'DefaultDict', + 'NamedTuple', + 'OrderedDict', + 'TypedDict', + + # Structural checks, a.k.a. protocols. + 'SupportsIndex', + + # One-off things. + 'Annotated', + 'assert_never', + 'assert_type', + 'clear_overloads', + 'dataclass_transform', + 'get_overloads', + 'final', + 'get_args', + 'get_origin', + 'get_type_hints', + 'IntVar', + 'is_typeddict', + 'Literal', + 'NewType', + 'overload', + 'override', + 'Protocol', + 'reveal_type', + 'runtime', + 'runtime_checkable', + 'Text', + 'TypeAlias', + 'TypeGuard', + 'TYPE_CHECKING', + 'Never', + 'NoReturn', + 'Required', + 'NotRequired', +] + +# for backward compatibility +PEP_560 = True +GenericMeta = type + +# The functions below are modified copies of typing internal helpers. +# They are needed by _ProtocolMeta and they provide support for PEP 646. + +_marker = object() + + +def _check_generic(cls, parameters, elen=_marker): + """Check correct count for parameters of a generic cls (internal helper). + This gives a nice error message in case of count mismatch. + """ + if not elen: + raise TypeError(f"{cls} is not a generic class") + if elen is _marker: + if not hasattr(cls, "__parameters__") or not cls.__parameters__: + raise TypeError(f"{cls} is not a generic class") + elen = len(cls.__parameters__) + alen = len(parameters) + if alen != elen: + if hasattr(cls, "__parameters__"): + parameters = [p for p in cls.__parameters__ if not _is_unpack(p)] + num_tv_tuples = sum(isinstance(p, TypeVarTuple) for p in parameters) + if (num_tv_tuples > 0) and (alen >= elen - num_tv_tuples): + return + raise TypeError(f"Too {'many' if alen > elen else 'few'} parameters for {cls};" + f" actual {alen}, expected {elen}") + + +if sys.version_info >= (3, 10): + def _should_collect_from_parameters(t): + return isinstance( + t, (typing._GenericAlias, _types.GenericAlias, _types.UnionType) + ) +elif sys.version_info >= (3, 9): + def _should_collect_from_parameters(t): + return isinstance(t, (typing._GenericAlias, _types.GenericAlias)) +else: + def _should_collect_from_parameters(t): + return isinstance(t, typing._GenericAlias) and not t._special + + +def _collect_type_vars(types, typevar_types=None): + """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) + """ + if typevar_types is None: + typevar_types = typing.TypeVar + tvars = [] + for t in types: + if ( + isinstance(t, typevar_types) and + t not in tvars and + not _is_unpack(t) + ): + tvars.append(t) + if _should_collect_from_parameters(t): + tvars.extend([t for t in t.__parameters__ if t not in tvars]) + return tuple(tvars) + + +NoReturn = typing.NoReturn + +# Some unconstrained type variables. These are used by the container types. +# (These are not for export.) +T = typing.TypeVar('T') # Any type. +KT = typing.TypeVar('KT') # Key type. +VT = typing.TypeVar('VT') # Value type. +T_co = typing.TypeVar('T_co', covariant=True) # Any type covariant containers. +T_contra = typing.TypeVar('T_contra', contravariant=True) # Ditto contravariant. + + +if sys.version_info >= (3, 11): + from typing import Any +else: + + class _AnyMeta(type): + def __instancecheck__(self, obj): + if self is Any: + raise TypeError("typing_extensions.Any cannot be used with isinstance()") + return super().__instancecheck__(obj) + + def __repr__(self): + if self is Any: + return "typing_extensions.Any" + return super().__repr__() + + class Any(metaclass=_AnyMeta): + """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 + checks. + """ + def __new__(cls, *args, **kwargs): + if cls is Any: + raise TypeError("Any cannot be instantiated") + return super().__new__(cls, *args, **kwargs) + + +ClassVar = typing.ClassVar + +# On older versions of typing there is an internal class named "Final". +# 3.8+ +if hasattr(typing, 'Final') and sys.version_info[:2] >= (3, 7): + Final = typing.Final +# 3.7 +else: + class _FinalForm(typing._SpecialForm, _root=True): + + def __repr__(self): + return 'typing_extensions.' + self._name + + def __getitem__(self, parameters): + item = typing._type_check(parameters, + f'{self._name} accepts only a single type.') + return typing._GenericAlias(self, (item,)) + + Final = _FinalForm('Final', + doc="""A special typing construct to indicate that a name + cannot be re-assigned or overridden in a subclass. + For example: + + MAX_SIZE: Final = 9000 + MAX_SIZE += 1 # Error reported by type checker + + class Connection: + TIMEOUT: Final[int] = 10 + class FastConnector(Connection): + TIMEOUT = 1 # Error reported by type checker + + There is no runtime checking of these properties.""") + +if sys.version_info >= (3, 11): + final = typing.final +else: + # @final exists in 3.8+, but we backport it for all versions + # before 3.11 to keep support for the __final__ attribute. + # See https://bugs.python.org/issue46342 + def final(f): + """This decorator can be used to indicate to type checkers that + the decorated method cannot be overridden, and decorated class + cannot be subclassed. For example: + + class Base: + @final + def done(self) -> None: + ... + class Sub(Base): + def done(self) -> None: # Error reported by type checker + ... + @final + class Leaf: + ... + class Other(Leaf): # Error reported by type checker + ... + + There is no runtime checking of these properties. The decorator + sets the ``__final__`` attribute to ``True`` on the decorated object + to allow runtime introspection. + """ + try: + f.__final__ = True + except (AttributeError, TypeError): + # Skip the attribute silently if it is not writable. + # AttributeError happens if the object has __slots__ or a + # read-only property, TypeError if it's a builtin class. + pass + return f + + +def IntVar(name): + return typing.TypeVar(name) + + +# 3.8+: +if hasattr(typing, 'Literal'): + Literal = typing.Literal +# 3.7: +else: + class _LiteralForm(typing._SpecialForm, _root=True): + + def __repr__(self): + return 'typing_extensions.' + self._name + + def __getitem__(self, parameters): + return typing._GenericAlias(self, parameters) + + Literal = _LiteralForm('Literal', + doc="""A type that can be used to indicate to type checkers + that the corresponding value has a value literally equivalent + to the provided parameter. For example: + + var: Literal[4] = 4 + + The type checker understands that 'var' is literally equal to + the value 4 and no other value. + + Literal[...] cannot be subclassed. There is no runtime + checking verifying that the parameter is actually a value + instead of a type.""") + + +_overload_dummy = typing._overload_dummy # noqa + + +if hasattr(typing, "get_overloads"): # 3.11+ + overload = typing.overload + get_overloads = typing.get_overloads + clear_overloads = typing.clear_overloads +else: + # {module: {qualname: {firstlineno: func}}} + _overload_registry = collections.defaultdict( + functools.partial(collections.defaultdict, dict) + ) + + def overload(func): + """Decorator for overloaded functions/methods. + + In a stub file, place two or more stub definitions for the same + function in a row, each decorated with @overload. For example: + + @overload + def utf8(value: None) -> None: ... + @overload + def utf8(value: bytes) -> bytes: ... + @overload + def utf8(value: str) -> bytes: ... + + In a non-stub file (i.e. a regular .py file), do the same but + follow it with an implementation. The implementation should *not* + be decorated with @overload. For example: + + @overload + def utf8(value: None) -> None: ... + @overload + def utf8(value: bytes) -> bytes: ... + @overload + def utf8(value: str) -> bytes: ... + def utf8(value): + # implementation goes here + + The overloads for a function can be retrieved at runtime using the + get_overloads() function. + """ + # classmethod and staticmethod + f = getattr(func, "__func__", func) + try: + _overload_registry[f.__module__][f.__qualname__][ + f.__code__.co_firstlineno + ] = func + except AttributeError: + # Not a normal function; ignore. + pass + return _overload_dummy + + def get_overloads(func): + """Return all defined overloads for *func* as a sequence.""" + # classmethod and staticmethod + f = getattr(func, "__func__", func) + if f.__module__ not in _overload_registry: + return [] + mod_dict = _overload_registry[f.__module__] + if f.__qualname__ not in mod_dict: + return [] + return list(mod_dict[f.__qualname__].values()) + + def clear_overloads(): + """Clear all overloads in the registry.""" + _overload_registry.clear() + + +# This is not a real generic class. Don't use outside annotations. +Type = typing.Type + +# Various ABCs mimicking those in collections.abc. +# A few are simply re-exported for completeness. + + +Awaitable = typing.Awaitable +Coroutine = typing.Coroutine +AsyncIterable = typing.AsyncIterable +AsyncIterator = typing.AsyncIterator +Deque = typing.Deque +ContextManager = typing.ContextManager +AsyncContextManager = typing.AsyncContextManager +DefaultDict = typing.DefaultDict + +# 3.7.2+ +if hasattr(typing, 'OrderedDict'): + OrderedDict = typing.OrderedDict +# 3.7.0-3.7.2 +else: + OrderedDict = typing._alias(collections.OrderedDict, (KT, VT)) + +Counter = typing.Counter +ChainMap = typing.ChainMap +AsyncGenerator = typing.AsyncGenerator +NewType = typing.NewType +Text = typing.Text +TYPE_CHECKING = typing.TYPE_CHECKING + + +_PROTO_WHITELIST = ['Callable', 'Awaitable', + 'Iterable', 'Iterator', 'AsyncIterable', 'AsyncIterator', + 'Hashable', 'Sized', 'Container', 'Collection', 'Reversible', + 'ContextManager', 'AsyncContextManager'] + + +def _get_protocol_attrs(cls): + attrs = set() + for base in cls.__mro__[:-1]: # without object + if base.__name__ in ('Protocol', 'Generic'): + continue + annotations = getattr(base, '__annotations__', {}) + for attr in list(base.__dict__.keys()) + list(annotations.keys()): + if (not attr.startswith('_abc_') and attr not in ( + '__abstractmethods__', '__annotations__', '__weakref__', + '_is_protocol', '_is_runtime_protocol', '__dict__', + '__args__', '__slots__', + '__next_in_mro__', '__parameters__', '__origin__', + '__orig_bases__', '__extra__', '__tree_hash__', + '__doc__', '__subclasshook__', '__init__', '__new__', + '__module__', '_MutableMapping__marker', '_gorg')): + attrs.add(attr) + return attrs + + +def _is_callable_members_only(cls): + return all(callable(getattr(cls, attr, None)) for attr in _get_protocol_attrs(cls)) + + +def _maybe_adjust_parameters(cls): + """Helper function used in Protocol.__init_subclass__ and _TypedDictMeta.__new__. + + The contents of this function are very similar + to logic found in typing.Generic.__init_subclass__ + on the CPython main branch. + """ + tvars = [] + if '__orig_bases__' in cls.__dict__: + tvars = typing._collect_type_vars(cls.__orig_bases__) + # Look for Generic[T1, ..., Tn] or Protocol[T1, ..., Tn]. + # If found, tvars must be a subset of it. + # If not found, tvars is it. + # Also check for and reject plain Generic, + # and reject multiple Generic[...] and/or Protocol[...]. + gvars = None + for base in cls.__orig_bases__: + if (isinstance(base, typing._GenericAlias) and + base.__origin__ in (typing.Generic, Protocol)): + # for error messages + the_base = base.__origin__.__name__ + if gvars is not None: + raise TypeError( + "Cannot inherit from Generic[...]" + " and/or Protocol[...] multiple types.") + gvars = base.__parameters__ + if gvars is None: + gvars = tvars + else: + tvarset = set(tvars) + gvarset = set(gvars) + if not tvarset <= gvarset: + s_vars = ', '.join(str(t) for t in tvars if t not in gvarset) + s_args = ', '.join(str(g) for g in gvars) + raise TypeError(f"Some type variables ({s_vars}) are" + f" not listed in {the_base}[{s_args}]") + tvars = gvars + cls.__parameters__ = tuple(tvars) + + +# 3.8+ +if hasattr(typing, 'Protocol'): + Protocol = typing.Protocol +# 3.7 +else: + + def _no_init(self, *args, **kwargs): + if type(self)._is_protocol: + raise TypeError('Protocols cannot be instantiated') + + class _ProtocolMeta(abc.ABCMeta): # noqa: B024 + # This metaclass is a bit unfortunate and exists only because of the lack + # of __instancehook__. + def __instancecheck__(cls, instance): + # We need this method for situations where attributes are + # assigned in __init__. + if ((not getattr(cls, '_is_protocol', False) or + _is_callable_members_only(cls)) and + issubclass(instance.__class__, cls)): + return True + if cls._is_protocol: + if all(hasattr(instance, attr) and + (not callable(getattr(cls, attr, None)) or + getattr(instance, attr) is not None) + for attr in _get_protocol_attrs(cls)): + return True + return super().__instancecheck__(instance) + + class Protocol(metaclass=_ProtocolMeta): + # There is quite a lot of overlapping code with typing.Generic. + # Unfortunately it is hard to avoid this while these live in two different + # modules. The duplicated code will be removed when Protocol is moved to typing. + """Base class for protocol classes. Protocol classes are defined as:: + + class Proto(Protocol): + def meth(self) -> int: + ... + + Such classes are primarily used with static type checkers that recognize + structural subtyping (static duck-typing), for example:: + + class C: + def meth(self) -> int: + return 0 + + def func(x: Proto) -> int: + return x.meth() + + func(C()) # Passes static type check + + See PEP 544 for details. Protocol classes decorated with + @typing_extensions.runtime act as simple-minded runtime protocol that checks + only the presence of given attributes, ignoring their type signatures. + + Protocol classes can be generic, they are defined as:: + + class GenProto(Protocol[T]): + def meth(self) -> T: + ... + """ + __slots__ = () + _is_protocol = True + + def __new__(cls, *args, **kwds): + if cls is Protocol: + raise TypeError("Type Protocol cannot be instantiated; " + "it can only be used as a base class") + return super().__new__(cls) + + @typing._tp_cache + def __class_getitem__(cls, params): + if not isinstance(params, tuple): + params = (params,) + if not params and cls is not typing.Tuple: + raise TypeError( + f"Parameter list to {cls.__qualname__}[...] cannot be empty") + msg = "Parameters to generic types must be types." + params = tuple(typing._type_check(p, msg) for p in params) # noqa + if cls is Protocol: + # Generic can only be subscripted with unique type variables. + if not all(isinstance(p, typing.TypeVar) for p in params): + i = 0 + while isinstance(params[i], typing.TypeVar): + i += 1 + raise TypeError( + "Parameters to Protocol[...] must all be type variables." + f" Parameter {i + 1} is {params[i]}") + if len(set(params)) != len(params): + raise TypeError( + "Parameters to Protocol[...] must all be unique") + else: + # Subscripting a regular Generic subclass. + _check_generic(cls, params, len(cls.__parameters__)) + return typing._GenericAlias(cls, params) + + def __init_subclass__(cls, *args, **kwargs): + if '__orig_bases__' in cls.__dict__: + error = typing.Generic in cls.__orig_bases__ + else: + error = typing.Generic in cls.__bases__ + if error: + raise TypeError("Cannot inherit from plain Generic") + _maybe_adjust_parameters(cls) + + # Determine if this is a protocol or a concrete subclass. + if not cls.__dict__.get('_is_protocol', None): + cls._is_protocol = any(b is Protocol for b in cls.__bases__) + + # Set (or override) the protocol subclass hook. + def _proto_hook(other): + if not cls.__dict__.get('_is_protocol', None): + return NotImplemented + if not getattr(cls, '_is_runtime_protocol', False): + if sys._getframe(2).f_globals['__name__'] in ['abc', 'functools']: + return NotImplemented + raise TypeError("Instance and class checks can only be used with" + " @runtime protocols") + if not _is_callable_members_only(cls): + if sys._getframe(2).f_globals['__name__'] in ['abc', 'functools']: + return NotImplemented + raise TypeError("Protocols with non-method members" + " don't support issubclass()") + if not isinstance(other, type): + # Same error as for issubclass(1, int) + raise TypeError('issubclass() arg 1 must be a class') + for attr in _get_protocol_attrs(cls): + for base in other.__mro__: + if attr in base.__dict__: + if base.__dict__[attr] is None: + return NotImplemented + break + annotations = getattr(base, '__annotations__', {}) + if (isinstance(annotations, typing.Mapping) and + attr in annotations and + isinstance(other, _ProtocolMeta) and + other._is_protocol): + break + else: + return NotImplemented + return True + if '__subclasshook__' not in cls.__dict__: + cls.__subclasshook__ = _proto_hook + + # We have nothing more to do for non-protocols. + if not cls._is_protocol: + return + + # Check consistency of bases. + for base in cls.__bases__: + if not (base in (object, typing.Generic) or + base.__module__ == 'collections.abc' and + base.__name__ in _PROTO_WHITELIST or + isinstance(base, _ProtocolMeta) and base._is_protocol): + raise TypeError('Protocols can only inherit from other' + f' protocols, got {repr(base)}') + cls.__init__ = _no_init + + +# 3.8+ +if hasattr(typing, 'runtime_checkable'): + runtime_checkable = typing.runtime_checkable +# 3.7 +else: + def runtime_checkable(cls): + """Mark a protocol class as a runtime protocol, so that it + can be used with isinstance() and issubclass(). Raise TypeError + if applied to a non-protocol class. + + This allows a simple-minded structural check very similar to the + one-offs in collections.abc such as Hashable. + """ + if not isinstance(cls, _ProtocolMeta) or not cls._is_protocol: + raise TypeError('@runtime_checkable can be only applied to protocol classes,' + f' got {cls!r}') + cls._is_runtime_protocol = True + return cls + + +# Exists for backwards compatibility. +runtime = runtime_checkable + + +# 3.8+ +if hasattr(typing, 'SupportsIndex'): + SupportsIndex = typing.SupportsIndex +# 3.7 +else: + @runtime_checkable + class SupportsIndex(Protocol): + __slots__ = () + + @abc.abstractmethod + def __index__(self) -> int: + pass + + +if hasattr(typing, "Required"): + # The standard library TypedDict in Python 3.8 does not store runtime information + # about which (if any) keys are optional. See https://bugs.python.org/issue38834 + # The standard library TypedDict in Python 3.9.0/1 does not honour the "total" + # keyword with old-style TypedDict(). See https://bugs.python.org/issue42059 + # The standard library TypedDict below Python 3.11 does not store runtime + # information about optional and required keys when using Required or NotRequired. + # Generic TypedDicts are also impossible using typing.TypedDict on Python <3.11. + TypedDict = typing.TypedDict + _TypedDictMeta = typing._TypedDictMeta + is_typeddict = typing.is_typeddict +else: + def _check_fails(cls, other): + try: + if sys._getframe(1).f_globals['__name__'] not in ['abc', + 'functools', + 'typing']: + # Typed dicts are only for static structural subtyping. + raise TypeError('TypedDict does not support instance and class checks') + except (AttributeError, ValueError): + pass + return False + + def _dict_new(*args, **kwargs): + if not args: + raise TypeError('TypedDict.__new__(): not enough arguments') + _, args = args[0], args[1:] # allow the "cls" keyword be passed + return dict(*args, **kwargs) + + _dict_new.__text_signature__ = '($cls, _typename, _fields=None, /, **kwargs)' + + def _typeddict_new(*args, total=True, **kwargs): + if not args: + raise TypeError('TypedDict.__new__(): not enough arguments') + _, args = args[0], args[1:] # allow the "cls" keyword be passed + if args: + typename, args = args[0], args[1:] # allow the "_typename" keyword be passed + elif '_typename' in kwargs: + typename = kwargs.pop('_typename') + import warnings + warnings.warn("Passing '_typename' as keyword argument is deprecated", + DeprecationWarning, stacklevel=2) + else: + raise TypeError("TypedDict.__new__() missing 1 required positional " + "argument: '_typename'") + if args: + try: + fields, = args # allow the "_fields" keyword be passed + except ValueError: + raise TypeError('TypedDict.__new__() takes from 2 to 3 ' + f'positional arguments but {len(args) + 2} ' + 'were given') + elif '_fields' in kwargs and len(kwargs) == 1: + fields = kwargs.pop('_fields') + import warnings + warnings.warn("Passing '_fields' as keyword argument is deprecated", + DeprecationWarning, stacklevel=2) + else: + fields = None + + if fields is None: + fields = kwargs + elif kwargs: + raise TypeError("TypedDict takes either a dict or keyword arguments," + " but not both") + + ns = {'__annotations__': dict(fields)} + try: + # Setting correct module is necessary to make typed dict classes pickleable. + ns['__module__'] = sys._getframe(1).f_globals.get('__name__', '__main__') + except (AttributeError, ValueError): + pass + + return _TypedDictMeta(typename, (), ns, total=total) + + _typeddict_new.__text_signature__ = ('($cls, _typename, _fields=None,' + ' /, *, total=True, **kwargs)') + + class _TypedDictMeta(type): + def __init__(cls, name, bases, ns, total=True): + super().__init__(name, bases, ns) + + def __new__(cls, name, bases, ns, total=True): + # Create new typed dict class object. + # This method is called directly when TypedDict is subclassed, + # or via _typeddict_new when TypedDict is instantiated. This way + # TypedDict supports all three syntaxes described in its docstring. + # Subclasses and instances of TypedDict return actual dictionaries + # via _dict_new. + ns['__new__'] = _typeddict_new if name == 'TypedDict' else _dict_new + # Don't insert typing.Generic into __bases__ here, + # or Generic.__init_subclass__ will raise TypeError + # in the super().__new__() call. + # Instead, monkey-patch __bases__ onto the class after it's been created. + tp_dict = super().__new__(cls, name, (dict,), ns) + + if any(issubclass(base, typing.Generic) for base in bases): + tp_dict.__bases__ = (typing.Generic, dict) + _maybe_adjust_parameters(tp_dict) + + annotations = {} + own_annotations = ns.get('__annotations__', {}) + msg = "TypedDict('Name', {f0: t0, f1: t1, ...}); each t must be a type" + own_annotations = { + n: typing._type_check(tp, msg) for n, tp in own_annotations.items() + } + required_keys = set() + optional_keys = set() + + for base in bases: + annotations.update(base.__dict__.get('__annotations__', {})) + required_keys.update(base.__dict__.get('__required_keys__', ())) + optional_keys.update(base.__dict__.get('__optional_keys__', ())) + + annotations.update(own_annotations) + for annotation_key, annotation_type in own_annotations.items(): + annotation_origin = get_origin(annotation_type) + if annotation_origin is Annotated: + annotation_args = get_args(annotation_type) + if annotation_args: + annotation_type = annotation_args[0] + annotation_origin = get_origin(annotation_type) + + if annotation_origin is Required: + required_keys.add(annotation_key) + elif annotation_origin is NotRequired: + optional_keys.add(annotation_key) + elif total: + required_keys.add(annotation_key) + else: + optional_keys.add(annotation_key) + + tp_dict.__annotations__ = annotations + tp_dict.__required_keys__ = frozenset(required_keys) + tp_dict.__optional_keys__ = frozenset(optional_keys) + if not hasattr(tp_dict, '__total__'): + tp_dict.__total__ = total + return tp_dict + + __instancecheck__ = __subclasscheck__ = _check_fails + + TypedDict = _TypedDictMeta('TypedDict', (dict,), {}) + TypedDict.__module__ = __name__ + TypedDict.__doc__ = \ + """A simple typed name space. At runtime it is equivalent to a plain dict. + + TypedDict creates a dictionary type that expects all of its + instances to have a certain set of keys, with each key + associated with a value of a consistent type. This expectation + is not checked at runtime but is only enforced by type checkers. + Usage:: + + class Point2D(TypedDict): + x: int + y: int + label: str + + a: Point2D = {'x': 1, 'y': 2, 'label': 'good'} # OK + b: Point2D = {'z': 3, 'label': 'bad'} # Fails type check + + assert Point2D(x=1, y=2, label='first') == dict(x=1, y=2, label='first') + + The type info can be accessed via the Point2D.__annotations__ dict, and + the Point2D.__required_keys__ and Point2D.__optional_keys__ frozensets. + TypedDict supports two additional equivalent forms:: + + Point2D = TypedDict('Point2D', x=int, y=int, label=str) + Point2D = TypedDict('Point2D', {'x': int, 'y': int, 'label': str}) + + The class syntax is only supported in Python 3.6+, while two other + syntax forms work for Python 2.7 and 3.2+ + """ + + if hasattr(typing, "_TypedDictMeta"): + _TYPEDDICT_TYPES = (typing._TypedDictMeta, _TypedDictMeta) + else: + _TYPEDDICT_TYPES = (_TypedDictMeta,) + + def is_typeddict(tp): + """Check if an annotation is a TypedDict class + + For example:: + class Film(TypedDict): + title: str + year: int + + is_typeddict(Film) # => True + is_typeddict(Union[list, str]) # => False + """ + return isinstance(tp, tuple(_TYPEDDICT_TYPES)) + + +if hasattr(typing, "assert_type"): + assert_type = typing.assert_type + +else: + def assert_type(__val, __typ): + """Assert (to the type checker) that the value is of the given type. + + When the type checker encounters a call to assert_type(), it + emits an error if the value is not of the specified type:: + + def greet(name: str) -> None: + assert_type(name, str) # ok + assert_type(name, int) # type checker error + + At runtime this returns the first argument unchanged and otherwise + does nothing. + """ + return __val + + +if hasattr(typing, "Required"): + get_type_hints = typing.get_type_hints +else: + import functools + import types + + # replaces _strip_annotations() + def _strip_extras(t): + """Strips Annotated, Required and NotRequired from a given type.""" + if isinstance(t, _AnnotatedAlias): + return _strip_extras(t.__origin__) + if hasattr(t, "__origin__") and t.__origin__ in (Required, NotRequired): + return _strip_extras(t.__args__[0]) + if isinstance(t, typing._GenericAlias): + stripped_args = tuple(_strip_extras(a) for a in t.__args__) + if stripped_args == t.__args__: + return t + return t.copy_with(stripped_args) + if hasattr(types, "GenericAlias") and isinstance(t, types.GenericAlias): + stripped_args = tuple(_strip_extras(a) for a in t.__args__) + if stripped_args == t.__args__: + return t + return types.GenericAlias(t.__origin__, stripped_args) + if hasattr(types, "UnionType") and isinstance(t, types.UnionType): + stripped_args = tuple(_strip_extras(a) for a in t.__args__) + if stripped_args == t.__args__: + return t + return functools.reduce(operator.or_, stripped_args) + + return t + + def get_type_hints(obj, globalns=None, localns=None, include_extras=False): + """Return type hints for an object. + + This is often the same as obj.__annotations__, but it handles + forward references encoded as string literals, adds Optional[t] if a + default value equal to None is set and recursively replaces all + 'Annotated[T, ...]', 'Required[T]' or 'NotRequired[T]' with 'T' + (unless 'include_extras=True'). + + The argument may be a module, class, method, or function. The annotations + are returned as a dictionary. For classes, annotations include also + inherited members. + + TypeError is raised if the argument is not of a type that can contain + annotations, and an empty dictionary is returned if no annotations are + present. + + BEWARE -- the behavior of globalns and localns is counterintuitive + (unless you are familiar with how eval() and exec() work). The + search order is locals first, then globals. + + - If no dict arguments are passed, an attempt is made to use the + globals from obj (or the respective module's globals for classes), + and these are also used as the locals. If the object does not appear + to have globals, an empty dictionary is used. + + - If one dict argument is passed, it is used for both globals and + locals. + + - If two dict arguments are passed, they specify globals and + locals, respectively. + """ + if hasattr(typing, "Annotated"): + hint = typing.get_type_hints( + obj, globalns=globalns, localns=localns, include_extras=True + ) + else: + hint = typing.get_type_hints(obj, globalns=globalns, localns=localns) + if include_extras: + return hint + return {k: _strip_extras(t) for k, t in hint.items()} + + +# Python 3.9+ has PEP 593 (Annotated) +if hasattr(typing, 'Annotated'): + Annotated = typing.Annotated + # Not exported and not a public API, but needed for get_origin() and get_args() + # to work. + _AnnotatedAlias = typing._AnnotatedAlias +# 3.7-3.8 +else: + class _AnnotatedAlias(typing._GenericAlias, _root=True): + """Runtime representation of an annotated type. + + At its core 'Annotated[t, dec1, dec2, ...]' is an alias for the type 't' + with extra annotations. The alias behaves like a normal typing alias, + instantiating is the same as instantiating the underlying type, binding + it to types is also the same. + """ + def __init__(self, origin, metadata): + if isinstance(origin, _AnnotatedAlias): + metadata = origin.__metadata__ + metadata + origin = origin.__origin__ + super().__init__(origin, origin) + self.__metadata__ = metadata + + def copy_with(self, params): + assert len(params) == 1 + new_type = params[0] + return _AnnotatedAlias(new_type, self.__metadata__) + + def __repr__(self): + return (f"typing_extensions.Annotated[{typing._type_repr(self.__origin__)}, " + f"{', '.join(repr(a) for a in self.__metadata__)}]") + + def __reduce__(self): + return operator.getitem, ( + Annotated, (self.__origin__,) + self.__metadata__ + ) + + def __eq__(self, other): + if not isinstance(other, _AnnotatedAlias): + return NotImplemented + if self.__origin__ != other.__origin__: + return False + return self.__metadata__ == other.__metadata__ + + def __hash__(self): + return hash((self.__origin__, self.__metadata__)) + + class Annotated: + """Add context specific metadata to a type. + + Example: Annotated[int, runtime_check.Unsigned] indicates to the + hypothetical runtime_check module that this type is an unsigned int. + Every other consumer of this type can ignore this metadata and treat + this type as int. + + The first argument to Annotated must be a valid type (and will be in + the __origin__ field), the remaining arguments are kept as a tuple in + the __extra__ field. + + Details: + + - It's an error to call `Annotated` with less than two arguments. + - Nested Annotated are flattened:: + + Annotated[Annotated[T, Ann1, Ann2], Ann3] == Annotated[T, Ann1, Ann2, Ann3] + + - Instantiating an annotated type is equivalent to instantiating the + underlying type:: + + Annotated[C, Ann1](5) == C(5) + + - Annotated can be used as a generic type alias:: + + Optimized = Annotated[T, runtime.Optimize()] + Optimized[int] == Annotated[int, runtime.Optimize()] + + OptimizedList = Annotated[List[T], runtime.Optimize()] + OptimizedList[int] == Annotated[List[int], runtime.Optimize()] + """ + + __slots__ = () + + def __new__(cls, *args, **kwargs): + raise TypeError("Type Annotated cannot be instantiated.") + + @typing._tp_cache + def __class_getitem__(cls, params): + if not isinstance(params, tuple) or len(params) < 2: + raise TypeError("Annotated[...] should be used " + "with at least two arguments (a type and an " + "annotation).") + allowed_special_forms = (ClassVar, Final) + if get_origin(params[0]) in allowed_special_forms: + origin = params[0] + else: + msg = "Annotated[t, ...]: t must be a type." + origin = typing._type_check(params[0], msg) + metadata = tuple(params[1:]) + return _AnnotatedAlias(origin, metadata) + + def __init_subclass__(cls, *args, **kwargs): + raise TypeError( + f"Cannot subclass {cls.__module__}.Annotated" + ) + +# Python 3.8 has get_origin() and get_args() but those implementations aren't +# Annotated-aware, so we can't use those. Python 3.9's versions don't support +# ParamSpecArgs and ParamSpecKwargs, so only Python 3.10's versions will do. +if sys.version_info[:2] >= (3, 10): + get_origin = typing.get_origin + get_args = typing.get_args +# 3.7-3.9 +else: + try: + # 3.9+ + from typing import _BaseGenericAlias + except ImportError: + _BaseGenericAlias = typing._GenericAlias + try: + # 3.9+ + from typing import GenericAlias as _typing_GenericAlias + except ImportError: + _typing_GenericAlias = typing._GenericAlias + + def get_origin(tp): + """Get the unsubscripted version of a type. + + This supports generic types, Callable, Tuple, Union, Literal, Final, ClassVar + and Annotated. Return None for unsupported types. Examples:: + + get_origin(Literal[42]) is Literal + get_origin(int) is None + get_origin(ClassVar[int]) is ClassVar + get_origin(Generic) is Generic + get_origin(Generic[T]) is Generic + get_origin(Union[T, int]) is Union + get_origin(List[Tuple[T, T]][int]) == list + get_origin(P.args) is P + """ + if isinstance(tp, _AnnotatedAlias): + return Annotated + if isinstance(tp, (typing._GenericAlias, _typing_GenericAlias, _BaseGenericAlias, + ParamSpecArgs, ParamSpecKwargs)): + return tp.__origin__ + if tp is typing.Generic: + return typing.Generic + return None + + def get_args(tp): + """Get type arguments with all substitutions performed. + + For unions, basic simplifications used by Union constructor are performed. + Examples:: + get_args(Dict[str, int]) == (str, int) + get_args(int) == () + get_args(Union[int, Union[T, int], str][int]) == (int, str) + get_args(Union[int, Tuple[T, int]][str]) == (int, Tuple[str, int]) + get_args(Callable[[], T][int]) == ([], int) + """ + if isinstance(tp, _AnnotatedAlias): + return (tp.__origin__,) + tp.__metadata__ + if isinstance(tp, (typing._GenericAlias, _typing_GenericAlias)): + if getattr(tp, "_special", False): + return () + res = tp.__args__ + if get_origin(tp) is collections.abc.Callable and res[0] is not Ellipsis: + res = (list(res[:-1]), res[-1]) + return res + return () + + +# 3.10+ +if hasattr(typing, 'TypeAlias'): + TypeAlias = typing.TypeAlias +# 3.9 +elif sys.version_info[:2] >= (3, 9): + class _TypeAliasForm(typing._SpecialForm, _root=True): + def __repr__(self): + return 'typing_extensions.' + self._name + + @_TypeAliasForm + def TypeAlias(self, parameters): + """Special marker indicating that an assignment should + be recognized as a proper type alias definition by type + checkers. + + For example:: + + Predicate: TypeAlias = Callable[..., bool] + + It's invalid when used anywhere except as in the example above. + """ + raise TypeError(f"{self} is not subscriptable") +# 3.7-3.8 +else: + class _TypeAliasForm(typing._SpecialForm, _root=True): + def __repr__(self): + return 'typing_extensions.' + self._name + + TypeAlias = _TypeAliasForm('TypeAlias', + doc="""Special marker indicating that an assignment should + be recognized as a proper type alias definition by type + checkers. + + For example:: + + Predicate: TypeAlias = Callable[..., bool] + + It's invalid when used anywhere except as in the example + above.""") + + +class _DefaultMixin: + """Mixin for TypeVarLike defaults.""" + + __slots__ = () + + def __init__(self, default): + if isinstance(default, (tuple, list)): + self.__default__ = tuple((typing._type_check(d, "Default must be a type") + for d in default)) + elif default: + self.__default__ = typing._type_check(default, "Default must be a type") + else: + self.__default__ = None + + +# Add default and infer_variance parameters from PEP 696 and 695 +class TypeVar(typing.TypeVar, _DefaultMixin, _root=True): + """Type variable.""" + + __module__ = 'typing' + + def __init__(self, name, *constraints, bound=None, + covariant=False, contravariant=False, + default=None, infer_variance=False): + super().__init__(name, *constraints, bound=bound, covariant=covariant, + contravariant=contravariant) + _DefaultMixin.__init__(self, default) + self.__infer_variance__ = infer_variance + + # for pickling: + try: + def_mod = sys._getframe(1).f_globals.get('__name__', '__main__') + except (AttributeError, ValueError): + def_mod = None + if def_mod != 'typing_extensions': + self.__module__ = def_mod + + +# Python 3.10+ has PEP 612 +if hasattr(typing, 'ParamSpecArgs'): + ParamSpecArgs = typing.ParamSpecArgs + ParamSpecKwargs = typing.ParamSpecKwargs +# 3.7-3.9 +else: + class _Immutable: + """Mixin to indicate that object should not be copied.""" + __slots__ = () + + def __copy__(self): + return self + + def __deepcopy__(self, memo): + return self + + class ParamSpecArgs(_Immutable): + """The args for a ParamSpec object. + + Given a ParamSpec object P, P.args is an instance of ParamSpecArgs. + + ParamSpecArgs objects have a reference back to their ParamSpec: + + P.args.__origin__ is P + + This type is meant for runtime introspection and has no special meaning to + static type checkers. + """ + def __init__(self, origin): + self.__origin__ = origin + + def __repr__(self): + return f"{self.__origin__.__name__}.args" + + def __eq__(self, other): + if not isinstance(other, ParamSpecArgs): + return NotImplemented + return self.__origin__ == other.__origin__ + + class ParamSpecKwargs(_Immutable): + """The kwargs for a ParamSpec object. + + Given a ParamSpec object P, P.kwargs is an instance of ParamSpecKwargs. + + ParamSpecKwargs objects have a reference back to their ParamSpec: + + P.kwargs.__origin__ is P + + This type is meant for runtime introspection and has no special meaning to + static type checkers. + """ + def __init__(self, origin): + self.__origin__ = origin + + def __repr__(self): + return f"{self.__origin__.__name__}.kwargs" + + def __eq__(self, other): + if not isinstance(other, ParamSpecKwargs): + return NotImplemented + return self.__origin__ == other.__origin__ + +# 3.10+ +if hasattr(typing, 'ParamSpec'): + + # Add default Parameter - PEP 696 + class ParamSpec(typing.ParamSpec, _DefaultMixin, _root=True): + """Parameter specification variable.""" + + __module__ = 'typing' + + def __init__(self, name, *, bound=None, covariant=False, contravariant=False, + default=None): + super().__init__(name, bound=bound, covariant=covariant, + contravariant=contravariant) + _DefaultMixin.__init__(self, default) + + # for pickling: + try: + def_mod = sys._getframe(1).f_globals.get('__name__', '__main__') + except (AttributeError, ValueError): + def_mod = None + if def_mod != 'typing_extensions': + self.__module__ = def_mod + +# 3.7-3.9 +else: + + # Inherits from list as a workaround for Callable checks in Python < 3.9.2. + class ParamSpec(list, _DefaultMixin): + """Parameter specification variable. + + Usage:: + + P = ParamSpec('P') + + Parameter specification variables exist primarily for the benefit of static + type checkers. They are used to forward the parameter types of one + callable to another callable, a pattern commonly found in higher order + functions and decorators. They are only valid when used in ``Concatenate``, + or s the first argument to ``Callable``. In Python 3.10 and higher, + they are also supported in user-defined Generics at runtime. + See class Generic for more information on generic types. An + example for annotating a decorator:: + + T = TypeVar('T') + P = ParamSpec('P') + + def add_logging(f: Callable[P, T]) -> Callable[P, T]: + '''A type-safe decorator to add logging to a function.''' + def inner(*args: P.args, **kwargs: P.kwargs) -> T: + logging.info(f'{f.__name__} was called') + return f(*args, **kwargs) + return inner + + @add_logging + def add_two(x: float, y: float) -> float: + '''Add two numbers together.''' + return x + y + + Parameter specification variables defined with covariant=True or + contravariant=True can be used to declare covariant or contravariant + generic types. These keyword arguments are valid, but their actual semantics + are yet to be decided. See PEP 612 for details. + + Parameter specification variables can be introspected. e.g.: + + P.__name__ == 'T' + P.__bound__ == None + P.__covariant__ == False + P.__contravariant__ == False + + Note that only parameter specification variables defined in global scope can + be pickled. + """ + + # Trick Generic __parameters__. + __class__ = typing.TypeVar + + @property + def args(self): + return ParamSpecArgs(self) + + @property + def kwargs(self): + return ParamSpecKwargs(self) + + def __init__(self, name, *, bound=None, covariant=False, contravariant=False, + default=None): + super().__init__([self]) + self.__name__ = name + self.__covariant__ = bool(covariant) + self.__contravariant__ = bool(contravariant) + if bound: + self.__bound__ = typing._type_check(bound, 'Bound must be a type.') + else: + self.__bound__ = None + _DefaultMixin.__init__(self, default) + + # for pickling: + try: + def_mod = sys._getframe(1).f_globals.get('__name__', '__main__') + except (AttributeError, ValueError): + def_mod = None + if def_mod != 'typing_extensions': + self.__module__ = def_mod + + def __repr__(self): + if self.__covariant__: + prefix = '+' + elif self.__contravariant__: + prefix = '-' + else: + prefix = '~' + return prefix + self.__name__ + + def __hash__(self): + return object.__hash__(self) + + def __eq__(self, other): + return self is other + + def __reduce__(self): + return self.__name__ + + # Hack to get typing._type_check to pass. + def __call__(self, *args, **kwargs): + pass + + +# 3.7-3.9 +if not hasattr(typing, 'Concatenate'): + # Inherits from list as a workaround for Callable checks in Python < 3.9.2. + class _ConcatenateGenericAlias(list): + + # Trick Generic into looking into this for __parameters__. + __class__ = typing._GenericAlias + + # Flag in 3.8. + _special = False + + def __init__(self, origin, args): + super().__init__(args) + self.__origin__ = origin + self.__args__ = args + + def __repr__(self): + _type_repr = typing._type_repr + return (f'{_type_repr(self.__origin__)}' + f'[{", ".join(_type_repr(arg) for arg in self.__args__)}]') + + def __hash__(self): + return hash((self.__origin__, self.__args__)) + + # Hack to get typing._type_check to pass in Generic. + def __call__(self, *args, **kwargs): + pass + + @property + def __parameters__(self): + return tuple( + tp for tp in self.__args__ if isinstance(tp, (typing.TypeVar, ParamSpec)) + ) + + +# 3.7-3.9 +@typing._tp_cache +def _concatenate_getitem(self, parameters): + if parameters == (): + raise TypeError("Cannot take a Concatenate of no types.") + if not isinstance(parameters, tuple): + parameters = (parameters,) + if not isinstance(parameters[-1], ParamSpec): + raise TypeError("The last parameter to Concatenate should be a " + "ParamSpec variable.") + msg = "Concatenate[arg, ...]: each arg must be a type." + parameters = tuple(typing._type_check(p, msg) for p in parameters) + return _ConcatenateGenericAlias(self, parameters) + + +# 3.10+ +if hasattr(typing, 'Concatenate'): + Concatenate = typing.Concatenate + _ConcatenateGenericAlias = typing._ConcatenateGenericAlias # noqa +# 3.9 +elif sys.version_info[:2] >= (3, 9): + @_TypeAliasForm + def Concatenate(self, parameters): + """Used in conjunction with ``ParamSpec`` and ``Callable`` to represent a + higher order function which adds, removes or transforms parameters of a + callable. + + For example:: + + Callable[Concatenate[int, P], int] + + See PEP 612 for detailed information. + """ + return _concatenate_getitem(self, parameters) +# 3.7-8 +else: + class _ConcatenateForm(typing._SpecialForm, _root=True): + def __repr__(self): + return 'typing_extensions.' + self._name + + def __getitem__(self, parameters): + return _concatenate_getitem(self, parameters) + + Concatenate = _ConcatenateForm( + 'Concatenate', + doc="""Used in conjunction with ``ParamSpec`` and ``Callable`` to represent a + higher order function which adds, removes or transforms parameters of a + callable. + + For example:: + + Callable[Concatenate[int, P], int] + + See PEP 612 for detailed information. + """) + +# 3.10+ +if hasattr(typing, 'TypeGuard'): + TypeGuard = typing.TypeGuard +# 3.9 +elif sys.version_info[:2] >= (3, 9): + class _TypeGuardForm(typing._SpecialForm, _root=True): + def __repr__(self): + return 'typing_extensions.' + self._name + + @_TypeGuardForm + def TypeGuard(self, parameters): + """Special typing form used to annotate the return type of a user-defined + type guard function. ``TypeGuard`` only accepts a single type argument. + At runtime, functions marked this way should return a boolean. + + ``TypeGuard`` aims to benefit *type narrowing* -- a technique used by static + type checkers to determine a more precise type of an expression within a + program's code flow. Usually type narrowing is done by analyzing + conditional code flow and applying the narrowing to a block of code. The + conditional expression here is sometimes referred to as a "type guard". + + Sometimes it would be convenient to use a user-defined boolean function + as a type guard. Such a function should use ``TypeGuard[...]`` as its + return type to alert static type checkers to this intention. + + Using ``-> TypeGuard`` tells the static type checker that for a given + function: + + 1. The return value is a boolean. + 2. If the return value is ``True``, the type of its argument + is the type inside ``TypeGuard``. + + For example:: + + def is_str(val: Union[str, float]): + # "isinstance" type guard + if isinstance(val, str): + # Type of ``val`` is narrowed to ``str`` + ... + else: + # Else, type of ``val`` is narrowed to ``float``. + ... + + Strict type narrowing is not enforced -- ``TypeB`` need not be a narrower + form of ``TypeA`` (it can even be a wider form) and this may lead to + type-unsafe results. The main reason is to allow for things like + narrowing ``List[object]`` to ``List[str]`` even though the latter is not + a subtype of the former, since ``List`` is invariant. The responsibility of + writing type-safe type guards is left to the user. + + ``TypeGuard`` also works with type variables. For more information, see + PEP 647 (User-Defined Type Guards). + """ + item = typing._type_check(parameters, f'{self} accepts only a single type.') + return typing._GenericAlias(self, (item,)) +# 3.7-3.8 +else: + class _TypeGuardForm(typing._SpecialForm, _root=True): + + def __repr__(self): + return 'typing_extensions.' + self._name + + def __getitem__(self, parameters): + item = typing._type_check(parameters, + f'{self._name} accepts only a single type') + return typing._GenericAlias(self, (item,)) + + TypeGuard = _TypeGuardForm( + 'TypeGuard', + doc="""Special typing form used to annotate the return type of a user-defined + type guard function. ``TypeGuard`` only accepts a single type argument. + At runtime, functions marked this way should return a boolean. + + ``TypeGuard`` aims to benefit *type narrowing* -- a technique used by static + type checkers to determine a more precise type of an expression within a + program's code flow. Usually type narrowing is done by analyzing + conditional code flow and applying the narrowing to a block of code. The + conditional expression here is sometimes referred to as a "type guard". + + Sometimes it would be convenient to use a user-defined boolean function + as a type guard. Such a function should use ``TypeGuard[...]`` as its + return type to alert static type checkers to this intention. + + Using ``-> TypeGuard`` tells the static type checker that for a given + function: + + 1. The return value is a boolean. + 2. If the return value is ``True``, the type of its argument + is the type inside ``TypeGuard``. + + For example:: + + def is_str(val: Union[str, float]): + # "isinstance" type guard + if isinstance(val, str): + # Type of ``val`` is narrowed to ``str`` + ... + else: + # Else, type of ``val`` is narrowed to ``float``. + ... + + Strict type narrowing is not enforced -- ``TypeB`` need not be a narrower + form of ``TypeA`` (it can even be a wider form) and this may lead to + type-unsafe results. The main reason is to allow for things like + narrowing ``List[object]`` to ``List[str]`` even though the latter is not + a subtype of the former, since ``List`` is invariant. The responsibility of + writing type-safe type guards is left to the user. + + ``TypeGuard`` also works with type variables. For more information, see + PEP 647 (User-Defined Type Guards). + """) + + +# Vendored from cpython typing._SpecialFrom +class _SpecialForm(typing._Final, _root=True): + __slots__ = ('_name', '__doc__', '_getitem') + + def __init__(self, getitem): + self._getitem = getitem + self._name = getitem.__name__ + self.__doc__ = getitem.__doc__ + + def __getattr__(self, item): + if item in {'__name__', '__qualname__'}: + return self._name + + raise AttributeError(item) + + def __mro_entries__(self, bases): + raise TypeError(f"Cannot subclass {self!r}") + + def __repr__(self): + return f'typing_extensions.{self._name}' + + def __reduce__(self): + return self._name + + def __call__(self, *args, **kwds): + raise TypeError(f"Cannot instantiate {self!r}") + + def __or__(self, other): + return typing.Union[self, other] + + def __ror__(self, other): + return typing.Union[other, self] + + def __instancecheck__(self, obj): + raise TypeError(f"{self} cannot be used with isinstance()") + + def __subclasscheck__(self, cls): + raise TypeError(f"{self} cannot be used with issubclass()") + + @typing._tp_cache + def __getitem__(self, parameters): + return self._getitem(self, parameters) + + +if hasattr(typing, "LiteralString"): + LiteralString = typing.LiteralString +else: + @_SpecialForm + def LiteralString(self, params): + """Represents an arbitrary literal string. + + Example:: + + from typing_extensions import LiteralString + + def query(sql: LiteralString) -> ...: + ... + + query("SELECT * FROM table") # ok + query(f"SELECT * FROM {input()}") # not ok + + See PEP 675 for details. + + """ + raise TypeError(f"{self} is not subscriptable") + + +if hasattr(typing, "Self"): + Self = typing.Self +else: + @_SpecialForm + def Self(self, params): + """Used to spell the type of "self" in classes. + + Example:: + + from typing import Self + + class ReturnsSelf: + def parse(self, data: bytes) -> Self: + ... + return self + + """ + + raise TypeError(f"{self} is not subscriptable") + + +if hasattr(typing, "Never"): + Never = typing.Never +else: + @_SpecialForm + def Never(self, params): + """The bottom type, a type that has no members. + + This can be used to define a function that should never be + called, or a function that never returns:: + + from typing_extensions import Never + + def never_call_me(arg: Never) -> None: + pass + + def int_or_str(arg: int | str) -> None: + never_call_me(arg) # type checker error + match arg: + case int(): + print("It's an int") + case str(): + print("It's a str") + case _: + never_call_me(arg) # ok, arg is of type Never + + """ + + raise TypeError(f"{self} is not subscriptable") + + +if hasattr(typing, 'Required'): + Required = typing.Required + NotRequired = typing.NotRequired +elif sys.version_info[:2] >= (3, 9): + class _ExtensionsSpecialForm(typing._SpecialForm, _root=True): + def __repr__(self): + return 'typing_extensions.' + self._name + + @_ExtensionsSpecialForm + def Required(self, parameters): + """A special typing construct to mark a key of a total=False TypedDict + as required. For example: + + class Movie(TypedDict, total=False): + title: Required[str] + year: int + + m = Movie( + title='The Matrix', # typechecker error if key is omitted + year=1999, + ) + + There is no runtime checking that a required key is actually provided + when instantiating a related TypedDict. + """ + item = typing._type_check(parameters, f'{self._name} accepts only a single type.') + return typing._GenericAlias(self, (item,)) + + @_ExtensionsSpecialForm + def NotRequired(self, parameters): + """A special typing construct to mark a key of a TypedDict as + potentially missing. For example: + + class Movie(TypedDict): + title: str + year: NotRequired[int] + + m = Movie( + title='The Matrix', # typechecker error if key is omitted + year=1999, + ) + """ + item = typing._type_check(parameters, f'{self._name} accepts only a single type.') + return typing._GenericAlias(self, (item,)) + +else: + class _RequiredForm(typing._SpecialForm, _root=True): + def __repr__(self): + return 'typing_extensions.' + self._name + + def __getitem__(self, parameters): + item = typing._type_check(parameters, + f'{self._name} accepts only a single type.') + return typing._GenericAlias(self, (item,)) + + Required = _RequiredForm( + 'Required', + doc="""A special typing construct to mark a key of a total=False TypedDict + as required. For example: + + class Movie(TypedDict, total=False): + title: Required[str] + year: int + + m = Movie( + title='The Matrix', # typechecker error if key is omitted + year=1999, + ) + + There is no runtime checking that a required key is actually provided + when instantiating a related TypedDict. + """) + NotRequired = _RequiredForm( + 'NotRequired', + doc="""A special typing construct to mark a key of a TypedDict as + potentially missing. For example: + + class Movie(TypedDict): + title: str + year: NotRequired[int] + + m = Movie( + title='The Matrix', # typechecker error if key is omitted + year=1999, + ) + """) + + +if hasattr(typing, "Unpack"): # 3.11+ + Unpack = typing.Unpack +elif sys.version_info[:2] >= (3, 9): + class _UnpackSpecialForm(typing._SpecialForm, _root=True): + def __repr__(self): + return 'typing_extensions.' + self._name + + class _UnpackAlias(typing._GenericAlias, _root=True): + __class__ = typing.TypeVar + + @_UnpackSpecialForm + def Unpack(self, parameters): + """A special typing construct to unpack a variadic type. For example: + + Shape = TypeVarTuple('Shape') + Batch = NewType('Batch', int) + + def add_batch_axis( + x: Array[Unpack[Shape]] + ) -> Array[Batch, Unpack[Shape]]: ... + + """ + item = typing._type_check(parameters, f'{self._name} accepts only a single type.') + return _UnpackAlias(self, (item,)) + + def _is_unpack(obj): + return isinstance(obj, _UnpackAlias) + +else: + class _UnpackAlias(typing._GenericAlias, _root=True): + __class__ = typing.TypeVar + + class _UnpackForm(typing._SpecialForm, _root=True): + def __repr__(self): + return 'typing_extensions.' + self._name + + def __getitem__(self, parameters): + item = typing._type_check(parameters, + f'{self._name} accepts only a single type.') + return _UnpackAlias(self, (item,)) + + Unpack = _UnpackForm( + 'Unpack', + doc="""A special typing construct to unpack a variadic type. For example: + + Shape = TypeVarTuple('Shape') + Batch = NewType('Batch', int) + + def add_batch_axis( + x: Array[Unpack[Shape]] + ) -> Array[Batch, Unpack[Shape]]: ... + + """) + + def _is_unpack(obj): + return isinstance(obj, _UnpackAlias) + + +if hasattr(typing, "TypeVarTuple"): # 3.11+ + + # Add default Parameter - PEP 696 + class TypeVarTuple(typing.TypeVarTuple, _DefaultMixin, _root=True): + """Type variable tuple.""" + + def __init__(self, name, *, default=None): + super().__init__(name) + _DefaultMixin.__init__(self, default) + + # for pickling: + try: + def_mod = sys._getframe(1).f_globals.get('__name__', '__main__') + except (AttributeError, ValueError): + def_mod = None + if def_mod != 'typing_extensions': + self.__module__ = def_mod + +else: + class TypeVarTuple(_DefaultMixin): + """Type variable tuple. + + Usage:: + + Ts = TypeVarTuple('Ts') + + In the same way that a normal type variable is a stand-in for a single + type such as ``int``, a type variable *tuple* is a stand-in for a *tuple* + type such as ``Tuple[int, str]``. + + Type variable tuples can be used in ``Generic`` declarations. + Consider the following example:: + + class Array(Generic[*Ts]): ... + + The ``Ts`` type variable tuple here behaves like ``tuple[T1, T2]``, + where ``T1`` and ``T2`` are type variables. To use these type variables + as type parameters of ``Array``, we must *unpack* the type variable tuple using + the star operator: ``*Ts``. The signature of ``Array`` then behaves + as if we had simply written ``class Array(Generic[T1, T2]): ...``. + In contrast to ``Generic[T1, T2]``, however, ``Generic[*Shape]`` allows + us to parameterise the class with an *arbitrary* number of type parameters. + + Type variable tuples can be used anywhere a normal ``TypeVar`` can. + This includes class definitions, as shown above, as well as function + signatures and variable annotations:: + + class Array(Generic[*Ts]): + + def __init__(self, shape: Tuple[*Ts]): + self._shape: Tuple[*Ts] = shape + + def get_shape(self) -> Tuple[*Ts]: + return self._shape + + shape = (Height(480), Width(640)) + x: Array[Height, Width] = Array(shape) + y = abs(x) # Inferred type is Array[Height, Width] + z = x + x # ... is Array[Height, Width] + x.get_shape() # ... is tuple[Height, Width] + + """ + + # Trick Generic __parameters__. + __class__ = typing.TypeVar + + def __iter__(self): + yield self.__unpacked__ + + def __init__(self, name, *, default=None): + self.__name__ = name + _DefaultMixin.__init__(self, default) + + # for pickling: + try: + def_mod = sys._getframe(1).f_globals.get('__name__', '__main__') + except (AttributeError, ValueError): + def_mod = None + if def_mod != 'typing_extensions': + self.__module__ = def_mod + + self.__unpacked__ = Unpack[self] + + def __repr__(self): + return self.__name__ + + def __hash__(self): + return object.__hash__(self) + + def __eq__(self, other): + return self is other + + def __reduce__(self): + return self.__name__ + + def __init_subclass__(self, *args, **kwds): + if '_root' not in kwds: + raise TypeError("Cannot subclass special typing classes") + + +if hasattr(typing, "reveal_type"): + reveal_type = typing.reveal_type +else: + def reveal_type(__obj: T) -> T: + """Reveal the inferred type of a variable. + + When a static type checker encounters a call to ``reveal_type()``, + it will emit the inferred type of the argument:: + + x: int = 1 + reveal_type(x) + + Running a static type checker (e.g., ``mypy``) on this example + will produce output similar to 'Revealed type is "builtins.int"'. + + At runtime, the function prints the runtime type of the + argument and returns it unchanged. + + """ + print(f"Runtime type is {type(__obj).__name__!r}", file=sys.stderr) + return __obj + + +if hasattr(typing, "assert_never"): + assert_never = typing.assert_never +else: + def assert_never(__arg: Never) -> Never: + """Assert to the type checker that a line of code is unreachable. + + Example:: + + def int_or_str(arg: int | str) -> None: + match arg: + case int(): + print("It's an int") + case str(): + print("It's a str") + case _: + assert_never(arg) + + If a type checker finds that a call to assert_never() is + reachable, it will emit an error. + + At runtime, this throws an exception when called. + + """ + raise AssertionError("Expected code to be unreachable") + + +if hasattr(typing, 'dataclass_transform'): + dataclass_transform = typing.dataclass_transform +else: + def dataclass_transform( + *, + eq_default: bool = True, + order_default: bool = False, + kw_only_default: bool = False, + field_specifiers: typing.Tuple[ + typing.Union[typing.Type[typing.Any], typing.Callable[..., typing.Any]], + ... + ] = (), + **kwargs: typing.Any, + ) -> typing.Callable[[T], T]: + """Decorator that marks a function, class, or metaclass as providing + dataclass-like behavior. + + Example: + + from typing_extensions import dataclass_transform + + _T = TypeVar("_T") + + # Used on a decorator function + @dataclass_transform() + def create_model(cls: type[_T]) -> type[_T]: + ... + return cls + + @create_model + class CustomerModel: + id: int + name: str + + # Used on a base class + @dataclass_transform() + class ModelBase: ... + + class CustomerModel(ModelBase): + id: int + name: str + + # Used on a metaclass + @dataclass_transform() + class ModelMeta(type): ... + + class ModelBase(metaclass=ModelMeta): ... + + class CustomerModel(ModelBase): + id: int + name: str + + Each of the ``CustomerModel`` classes defined in this example will now + behave similarly to a dataclass created with the ``@dataclasses.dataclass`` + decorator. For example, the type checker will synthesize an ``__init__`` + method. + + The arguments to this decorator can be used to customize this behavior: + - ``eq_default`` indicates whether the ``eq`` parameter is assumed to be + True or False if it is omitted by the caller. + - ``order_default`` indicates whether the ``order`` parameter is + assumed to be True or False if it is omitted by the caller. + - ``kw_only_default`` indicates whether the ``kw_only`` parameter is + assumed to be True or False if it is omitted by the caller. + - ``field_specifiers`` specifies a static list of supported classes + or functions that describe fields, similar to ``dataclasses.field()``. + + At runtime, this decorator records its arguments in the + ``__dataclass_transform__`` attribute on the decorated object. + + See PEP 681 for details. + + """ + def decorator(cls_or_fn): + cls_or_fn.__dataclass_transform__ = { + "eq_default": eq_default, + "order_default": order_default, + "kw_only_default": kw_only_default, + "field_specifiers": field_specifiers, + "kwargs": kwargs, + } + return cls_or_fn + return decorator + + +if hasattr(typing, "override"): + override = typing.override +else: + _F = typing.TypeVar("_F", bound=typing.Callable[..., typing.Any]) + + def override(__arg: _F) -> _F: + """Indicate that a method is intended to override a method in a base class. + + Usage: + + class Base: + def method(self) -> None: ... + pass + + class Child(Base): + @override + def method(self) -> None: + super().method() + + When this decorator is applied to a method, the type checker will + validate that it overrides a method with the same name on a base class. + This helps prevent bugs that may occur when a base class is changed + without an equivalent change to a child class. + + See PEP 698 for details. + + """ + return __arg + + +# We have to do some monkey patching to deal with the dual nature of +# Unpack/TypeVarTuple: +# - We want Unpack to be a kind of TypeVar so it gets accepted in +# Generic[Unpack[Ts]] +# - We want it to *not* be treated as a TypeVar for the purposes of +# counting generic parameters, so that when we subscript a generic, +# the runtime doesn't try to substitute the Unpack with the subscripted type. +if not hasattr(typing, "TypeVarTuple"): + typing._collect_type_vars = _collect_type_vars + typing._check_generic = _check_generic + + +# Backport typing.NamedTuple as it exists in Python 3.11. +# In 3.11, the ability to define generic `NamedTuple`s was supported. +# This was explicitly disallowed in 3.9-3.10, and only half-worked in <=3.8. +if sys.version_info >= (3, 11): + NamedTuple = typing.NamedTuple +else: + def _caller(): + try: + return sys._getframe(2).f_globals.get('__name__', '__main__') + except (AttributeError, ValueError): # For platforms without _getframe() + return None + + def _make_nmtuple(name, types, module, defaults=()): + fields = [n for n, t in types] + annotations = {n: typing._type_check(t, f"field {n} annotation must be a type") + for n, t in types} + nm_tpl = collections.namedtuple(name, fields, + defaults=defaults, module=module) + nm_tpl.__annotations__ = nm_tpl.__new__.__annotations__ = annotations + # The `_field_types` attribute was removed in 3.9; + # in earlier versions, it is the same as the `__annotations__` attribute + if sys.version_info < (3, 9): + nm_tpl._field_types = annotations + return nm_tpl + + _prohibited_namedtuple_fields = typing._prohibited + _special_namedtuple_fields = frozenset({'__module__', '__name__', '__annotations__'}) + + class _NamedTupleMeta(type): + def __new__(cls, typename, bases, ns): + assert _NamedTuple in bases + for base in bases: + if base is not _NamedTuple and base is not typing.Generic: + raise TypeError( + 'can only inherit from a NamedTuple type and Generic') + bases = tuple(tuple if base is _NamedTuple else base for base in bases) + types = ns.get('__annotations__', {}) + default_names = [] + for field_name in types: + if field_name in ns: + default_names.append(field_name) + elif default_names: + raise TypeError(f"Non-default namedtuple field {field_name} " + f"cannot follow default field" + f"{'s' if len(default_names) > 1 else ''} " + f"{', '.join(default_names)}") + nm_tpl = _make_nmtuple( + typename, types.items(), + defaults=[ns[n] for n in default_names], + module=ns['__module__'] + ) + nm_tpl.__bases__ = bases + if typing.Generic in bases: + class_getitem = typing.Generic.__class_getitem__.__func__ + nm_tpl.__class_getitem__ = classmethod(class_getitem) + # update from user namespace without overriding special namedtuple attributes + for key in ns: + if key in _prohibited_namedtuple_fields: + raise AttributeError("Cannot overwrite NamedTuple attribute " + key) + elif key not in _special_namedtuple_fields and key not in nm_tpl._fields: + setattr(nm_tpl, key, ns[key]) + if typing.Generic in bases: + nm_tpl.__init_subclass__() + return nm_tpl + + def NamedTuple(__typename, __fields=None, **kwargs): + 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, module=_caller()) + + NamedTuple.__doc__ = typing.NamedTuple.__doc__ + _NamedTuple = type.__new__(_NamedTupleMeta, 'NamedTuple', (), {}) + + # On 3.8+, alter the signature so that it matches typing.NamedTuple. + # The signature of typing.NamedTuple on >=3.8 is invalid syntax in Python 3.7, + # so just leave the signature as it is on 3.7. + if sys.version_info >= (3, 8): + NamedTuple.__text_signature__ = '(typename, fields=None, /, **kwargs)' + + def _namedtuple_mro_entries(bases): + assert NamedTuple in bases + return (_NamedTuple,) + + NamedTuple.__mro_entries__ = _namedtuple_mro_entries |