"""

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

Among other things, the module includes the following:

* Generic, Protocol, and internal machinery to support generic aliases.

All subscripted types like X[int], Union[int, str] are generic aliases.

* Various "special forms" that have unique meanings in type annotations:

NoReturn, Never, ClassVar, Self, Concatenate, Unpack, and others.

* Classes whose instances can be type arguments to generic classes and functions:

TypeVar, ParamSpec, TypeVarTuple.

* Public helper functions: get_type_hints, overload, cast, final, and others.

* Several protocols to support duck-typing:

SupportsFloat, SupportsIndex, SupportsAbs, and others.

* Special types: NewType, NamedTuple, TypedDict.

* Deprecated aliases for builtin types and collections.abc ABCs.

Any name not present in __all__ is an implementation detail

that may be changed without notice. Use at your own risk!

"""

from abc import abstractmethod, ABCMeta

import collections

from collections import defaultdict

import collections.abc

import copyreg

import functools

import operator

import sys

import types

from types import WrapperDescriptorType, MethodWrapperType, MethodDescriptorType, GenericAlias

from _typing import (

_idfunc,

TypeVar,

ParamSpec,

TypeVarTuple,

ParamSpecArgs,

ParamSpecKwargs,

TypeAliasType,

Generic,

NoDefault,

)

# Please keep __all__ alphabetized within each category.

__all__ = [

# Super-special typing primitives.

'Annotated',

'Any',

'Callable',

'ClassVar',

'Concatenate',

'Final',

'ForwardRef',

'Generic',

'Literal',

'Optional',

'ParamSpec',

'Protocol',

'Tuple',

'Type',

'TypeVar',

'TypeVarTuple',

'Union',

# ABCs (from collections.abc).

'AbstractSet', # collections.abc.Set.

'ByteString',

'Container',

'ContextManager',

'Hashable',

'ItemsView',

'Iterable',

'Iterator',

'KeysView',

'Mapping',

'MappingView',

'MutableMapping',

'MutableSequence',

'MutableSet',

'Sequence',

'Sized',

'ValuesView',

'Awaitable',

'AsyncIterator',

'AsyncIterable',

'Coroutine',

'Collection',

'AsyncGenerator',

'AsyncContextManager',

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

'Reversible',

'SupportsAbs',

'SupportsBytes',

'SupportsComplex',

'SupportsFloat',

'SupportsIndex',

'SupportsInt',

'SupportsRound',

# Concrete collection types.

'ChainMap',

'Counter',

'Deque',

'Dict',

'DefaultDict',

'List',

'OrderedDict',

'Set',

'FrozenSet',

'NamedTuple', # Not really a type.

'TypedDict', # Not really a type.

'Generator',

# Other concrete types.

'BinaryIO',

'IO',

'Match',

'Pattern',

'TextIO',

# One-off things.

'AnyStr',

'assert_type',

'assert_never',

'cast',

'clear_overloads',

'dataclass_transform',

'final',

'get_args',

'get_origin',

'get_overloads',

'get_protocol_members',

'get_type_hints',

'is_protocol',

'is_typeddict',

'LiteralString',

'Never',

'NewType',

'no_type_check',

'no_type_check_decorator',

'NoDefault',

'NoReturn',

'NotRequired',

'overload',

'override',

'ParamSpecArgs',

'ParamSpecKwargs',

'ReadOnly',

'Required',

'reveal_type',

'runtime_checkable',

'Self',

'Text',

'TYPE_CHECKING',

'TypeAlias',

'TypeGuard',

'TypeIs',

'TypeAliasType',

'Unpack',

]

def _type_convert(arg, module=None, *, allow_special_forms=False):

"""For converting None to type(None), and strings to ForwardRef."""

if arg is None:

return type(None)

if isinstance(arg, str):

return ForwardRef(arg, module=module, is_class=allow_special_forms)

return arg

def _type_check(arg, msg, is_argument=True, module=None, *, allow_special_forms=False):

"""Check that the argument is a type, and return it (internal helper).

As a special case, accept None and return type(None) instead. Also wrap strings

into ForwardRef instances. Consider several corner cases, for example plain

special forms like Union are not valid, while Union[int, str] is OK, etc.

The msg argument is a human-readable error message, e.g.::

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

We append the repr() of the actual value (truncated to 100 chars).

"""

invalid_generic_forms = (Generic, Protocol)

if not allow_special_forms:

invalid_generic_forms += (ClassVar,)

if is_argument:

invalid_generic_forms += (Final,)

arg = _type_convert(arg, module=module, allow_special_forms=allow_special_forms)

if (isinstance(arg, _GenericAlias) and

arg.__origin__ in invalid_generic_forms):

raise TypeError(f"{arg} is not valid as type argument")

if arg in (Any, LiteralString, NoReturn, Never, Self, TypeAlias):

return arg

if allow_special_forms and arg in (ClassVar, Final):

return arg

if isinstance(arg, _SpecialForm) or arg in (Generic, Protocol):

raise TypeError(f"Plain {arg} is not valid as type argument")

if type(arg) is tuple:

raise TypeError(f"{msg} Got {arg!r:.100}.")

return arg

def _is_param_expr(arg):

return arg is ... or isinstance(arg,

(tuple, list, ParamSpec, _ConcatenateGenericAlias))

def _should_unflatten_callable_args(typ, args):

"""Internal helper for munging collections.abc.Callable's __args__.

The canonical representation for a Callable's __args__ flattens the

argument types, see https://github.com/python/cpython/issues/86361.

For example::

>>> import collections.abc

>>> P = ParamSpec('P')

>>> collections.abc.Callable[[int, int], str].__args__ == (int, int, str)

True

>>> collections.abc.Callable[P, str].__args__ == (P, str)

True

As a result, if we need to reconstruct the Callable from its __args__,

we need to unflatten it.

"""

return (

typ.__origin__ is collections.abc.Callable

and not (len(args) == 2 and _is_param_expr(args[0]))

)

def _type_repr(obj):

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

If obj is a type, we return a shorter version than the default

type.__repr__, based on the module and qualified name, which is

typically enough to uniquely identify a type. For everything

else, we fall back on repr(obj).

"""

# When changing this function, don't forget about

# `_collections_abc._type_repr`, which does the same thing

# and must be consistent with this one.

if isinstance(obj, type):

if obj.__module__ == 'builtins':

return obj.__qualname__

return f'{obj.__module__}.{obj.__qualname__}'

if obj is ...:

return '...'

if isinstance(obj, types.FunctionType):

return obj.__name__

if isinstance(obj, tuple):

# Special case for `repr` of types with `ParamSpec`:

return '[' + ', '.join(_type_repr(t) for t in obj) + ']'

return repr(obj)

def _collect_type_parameters(args, *, enforce_default_ordering: bool = True):

"""Collect all type parameters in args

in order of first appearance (lexicographic order).

For example::

>>> P = ParamSpec('P')

>>> T = TypeVar('T')

>>> _collect_type_parameters((T, Callable[P, T]))

(~T, ~P)

"""

# required type parameter cannot appear after parameter with default

default_encountered = False

# or after TypeVarTuple

type_var_tuple_encountered = False

parameters = []

for t in args:

if isinstance(t, type):

# We don't want __parameters__ descriptor of a bare Python class.

pass

elif isinstance(t, tuple):

# `t` might be a tuple, when `ParamSpec` is substituted with

# `[T, int]`, or `[int, *Ts]`, etc.

for x in t:

for collected in _collect_type_parameters([x]):

if collected not in parameters:

parameters.append(collected)

elif hasattr(t, '__typing_subst__'):

if t not in parameters:

if enforce_default_ordering:

if type_var_tuple_encountered and t.has_default():

raise TypeError('Type parameter with a default'

' follows TypeVarTuple')

if t.has_default():

default_encountered = True

elif default_encountered:

raise TypeError(f'Type parameter {t!r} without a default'

' follows type parameter with a default')

parameters.append(t)

else:

if _is_unpacked_typevartuple(t):

type_var_tuple_encountered = True

for x in getattr(t, '__parameters__', ()):

if x not in parameters:

parameters.append(x)

return tuple(parameters)

def _check_generic_specialization(cls, arguments):

"""Check correct count for parameters of a generic cls (internal helper).

This gives a nice error message in case of count mismatch.

"""

expected_len = len(cls.__parameters__)

if not expected_len:

raise TypeError(f"{cls} is not a generic class")

actual_len = len(arguments)

if actual_len != expected_len:

# deal with defaults

if actual_len < expected_len:

# If the parameter at index `actual_len` in the parameters list

# has a default, then all parameters after it must also have

# one, because we validated as much in _collect_type_parameters().

# That means that no error needs to be raised here, despite

# the number of arguments being passed not matching the number

# of parameters: all parameters that aren't explicitly

# specialized in this call are parameters with default values.

if cls.__parameters__[actual_len].has_default():

return

expected_len -= sum(p.has_default() for p in cls.__parameters__)

expect_val = f"at least {expected_len}"

else:

expect_val = expected_len

raise TypeError(f"Too {'many' if actual_len > expected_len else 'few'} arguments"

f" for {cls}; actual {actual_len}, expected {expect_val}")

def _unpack_args(*args):

newargs = []

for arg in args:

subargs = getattr(arg, '__typing_unpacked_tuple_args__', None)

if subargs is not None and not (subargs and subargs[-1] is ...):

newargs.extend(subargs)

else:

newargs.append(arg)

return newargs

def _deduplicate(params, *, unhashable_fallback=False):

# Weed out strict duplicates, preserving the first of each occurrence.

try:

return dict.fromkeys(params)

except TypeError:

if not unhashable_fallback:

raise

# Happens for cases like `Annotated[dict, {'x': IntValidator()}]`

return _deduplicate_unhashable(params)

def _deduplicate_unhashable(unhashable_params):

new_unhashable = []

for t in unhashable_params:

if t not in new_unhashable:

new_unhashable.append(t)

return new_unhashable

def _compare_args_orderless(first_args, second_args):

first_unhashable = _deduplicate_unhashable(first_args)

second_unhashable = _deduplicate_unhashable(second_args)

t = list(second_unhashable)

try:

for elem in first_unhashable:

t.remove(elem)

except ValueError:

return False

return not t

def _remove_dups_flatten(parameters):

"""Internal helper for Union creation and substitution.

Flatten Unions among parameters, then remove duplicates.

"""

# Flatten out Union[Union[...], ...].

params = []

for p in parameters:

if isinstance(p, (_UnionGenericAlias, types.UnionType)):

params.extend(p.__args__)

else:

params.append(p)

return tuple(_deduplicate(params, unhashable_fallback=True))

def _flatten_literal_params(parameters):

"""Internal helper for Literal creation: flatten Literals among parameters."""

params = []

for p in parameters:

if isinstance(p, _LiteralGenericAlias):

params.extend(p.__args__)

else:

params.append(p)

return tuple(params)

_cleanups = []

_caches = {}

def _tp_cache(func=None, /, *, typed=False):

"""Internal wrapper caching __getitem__ of generic types.

For non-hashable arguments, the original function is used as a fallback.

"""

def decorator(func):

# The callback 'inner' references the newly created lru_cache

# indirectly by performing a lookup in the global '_caches' dictionary.

# This breaks a reference that can be problematic when combined with

# C API extensions that leak references to types. See GH-98253.

cache = functools.lru_cache(typed=typed)(func)

_caches[func] = cache

_cleanups.append(cache.cache_clear)

del cache

@functools.wraps(func)

def inner(*args, **kwds):

try:

return _caches[func](*args, **kwds)

except TypeError:

pass # All real errors (not unhashable args) are raised below.

return func(*args, **kwds)

return inner

if func is not None:

return decorator(func)

return decorator

def _deprecation_warning_for_no_type_params_passed(funcname: str) -> None:

import warnings

depr_message = (

f"Failing to pass a value to the 'type_params' parameter "

f"of {funcname!r} is deprecated, as it leads to incorrect behaviour "

f"when calling {funcname} on a stringified annotation "

f"that references a PEP 695 type parameter. "

f"It will be disallowed in Python 3.15."

)

warnings.warn(depr_message, category=DeprecationWarning, stacklevel=3)

class _Sentinel:

__slots__ = ()

def __repr__(self):

return '<sentinel>'

_sentinel = _Sentinel()

def _eval_type(t, globalns, localns, type_params=_sentinel, *, recursive_guard=frozenset()):

"""Evaluate all forward references in the given type t.

For use of globalns and localns see the docstring for get_type_hints().

recursive_guard is used to prevent infinite recursion with a recursive

ForwardRef.

"""

if type_params is _sentinel:

_deprecation_warning_for_no_type_params_passed("typing._eval_type")

type_params = ()

if isinstance(t, ForwardRef):

return t._evaluate(globalns, localns, type_params, recursive_guard=recursive_guard)

if isinstance(t, (_GenericAlias, GenericAlias, types.UnionType)):

if isinstance(t, GenericAlias):

args = tuple(

ForwardRef(arg) if isinstance(arg, str) else arg

for arg in t.__args__

)

is_unpacked = t.__unpacked__

if _should_unflatten_callable_args(t, args):

t = t.__origin__[(args[:-1], args[-1])]

else:

t = t.__origin__[args]

if is_unpacked:

t = Unpack[t]

ev_args = tuple(

_eval_type(

a, globalns, localns, type_params, recursive_guard=recursive_guard

)

for a in t.__args__

)

if ev_args == t.__args__:

return t

if isinstance(t, GenericAlias):

return GenericAlias(t.__origin__, ev_args)

if isinstance(t, types.UnionType):

return functools.reduce(operator.or_, ev_args)

else:

return t.copy_with(ev_args)

return t

class _Final:

"""Mixin to prohibit subclassing."""

__slots__ = ('__weakref__',)

def __init_subclass__(cls, /, *args, **kwds):

if '_root' not in kwds:

raise TypeError("Cannot subclass special typing classes")

class _NotIterable:

"""Mixin to prevent iteration, without being compatible with Iterable.

That is, we could do::

def __iter__(self): raise TypeError()

But this would make users of this mixin duck type-compatible with

collections.abc.Iterable - isinstance(foo, Iterable) would be True.

Luckily, we can instead prevent iteration by setting __iter__ to None, which

is treated specially.

"""

__slots__ = ()

__iter__ = None

# Internal indicator of special typing constructs.

# See __doc__ instance attribute for specific docs.

class _SpecialForm(_Final, _NotIterable, _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 'typing.' + 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 Union[self, other]

def __ror__(self, other):

return 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()")

@_tp_cache

def __getitem__(self, parameters):

return self._getitem(self, parameters)

class _TypedCacheSpecialForm(_SpecialForm, _root=True):

def __getitem__(self, parameters):

if not isinstance(parameters, tuple):

parameters = (parameters,)

return self._getitem(self, *parameters)

class _AnyMeta(type):

def __instancecheck__(self, obj):

if self is Any:

raise TypeError("typing.Any cannot be used with isinstance()")

return super().__instancecheck__(obj)

def __repr__(self):

if self is Any:

return "typing.Any"

return super().__repr__() # respect to subclasses

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)

@_SpecialForm

def NoReturn(self, parameters):

"""Special type indicating functions that never return.

Example::

from typing import NoReturn

def stop() -> NoReturn:

raise Exception('no way')

NoReturn can also be used as a bottom type, a type that

has no values. Starting in Python 3.11, the Never type should

be used for this concept instead. Type checkers should treat the two

equivalently.

"""

raise TypeError(f"{self} is not subscriptable")

# This is semantically identical to NoReturn, but it is implemented

# separately so that type checkers can distinguish between the two

# if they want.

@_SpecialForm

def Never(self, parameters):

"""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 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")

@_SpecialForm

def Self(self, parameters):

"""Used to spell the type of "self" in classes.

Example::

from typing import Self

class Foo:

def return_self(self) -> Self:

...

return self

This is especially useful for:

- classmethods that are used as alternative constructors

- annotating an `__enter__` method which returns self

"""

raise TypeError(f"{self} is not subscriptable")

@_SpecialForm

def LiteralString(self, parameters):

"""Represents an arbitrary literal string.

Example::

from typing import LiteralString

def run_query(sql: LiteralString) -> None:

...

def caller(arbitrary_string: str, literal_string: LiteralString) -> None:

run_query("SELECT * FROM students") # OK

run_query(literal_string) # OK

run_query("SELECT * FROM " + literal_string) # OK

run_query(arbitrary_string) # type checker error

run_query( # type checker error

f"SELECT * FROM students WHERE name = {arbitrary_string}"

)

Only string literals and other LiteralStrings are compatible

with LiteralString. This provides a tool to help prevent

security issues such as SQL injection.

"""

raise TypeError(f"{self} is not subscriptable")

@_SpecialForm

def ClassVar(self, parameters):

"""Special type construct to mark class variables.

An annotation wrapped in ClassVar indicates that a given

attribute is intended to be used as a class variable and

should not be set on instances of that class.

Usage::

class Starship:

stats: ClassVar[dict[str, int]] = {} # class variable

damage: int = 10 # instance variable

ClassVar accepts only types and cannot be further subscribed.

Note that ClassVar is not a class itself, and should not

be used with isinstance() or issubclass().

"""

item = _type_check(parameters, f'{self} accepts only single type.', allow_special_forms=True)

return _GenericAlias(self, (item,))

@_SpecialForm

def Final(self, parameters):

"""Special typing construct to indicate final names to type checkers.

A final name cannot be re-assigned or overridden in a subclass.

For example::

MAX_SIZE: Final = 9000

MAX_SIZE += 1 # Error reported by type checker

class Connection:

TIMEOUT: Final[int] = 10

class FastConnector(Connection):

TIMEOUT = 1 # Error reported by type checker

There is no runtime checking of these properties.

"""

item = _type_check(parameters, f'{self} accepts only single type.', allow_special_forms=True)

return _GenericAlias(self, (item,))

@_SpecialForm

def Union(self, parameters):

"""Union type; Union[X, Y] means either X or Y.

On Python 3.10 and higher, the | operator

can also be used to denote unions;

X | Y means the same thing to the type checker as Union[X, 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.::

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

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

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

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

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

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

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

- You cannot subclass or instantiate a union.

- You can use Optional[X] as a shorthand for Union[X, None].

"""

if parameters == ():

raise TypeError("Cannot take a Union of no types.")

if not isinstance(parameters, tuple):

parameters = (parameters,)

msg = "Union[arg, ...]: each arg must be a type."

parameters = tuple(_type_check(p, msg) for p in parameters)

parameters = _remove_dups_flatten(parameters)

if len(parameters) == 1:

return parameters[0]

if len(parameters) == 2 and type(None) in parameters:

return _UnionGenericAlias(self, parameters, name="Optional")

return _UnionGenericAlias(self, parameters)

def _make_union(left, right):

"""Used from the C implementation of TypeVar.

TypeVar.__or__ calls this instead of returning types.UnionType

because we want to allow unions between TypeVars and strings

(forward references).

"""

return Union[left, right]

@_SpecialForm

def Optional(self, parameters):

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

arg = _type_check(parameters, f"{self} requires a single type.")

return Union[arg, type(None)]

@_TypedCacheSpecialForm

@_tp_cache(typed=True)

def Literal(self, *parameters):

"""Special typing form to define literal types (a.k.a. value types).

This form can be used to indicate to type checkers that the corresponding

variable or function parameter has a value equivalent to the provided

literal (or one of several literals)::

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

...

MODE = Literal['r', 'rb', 'w', 'wb']

def open_helper(file: str, mode: MODE) -> str:

...

open_helper('/some/path', 'r') # Passes type check

open_helper('/other/path', 'typo') # Error in type checker

Literal[...] cannot be subclassed. At runtime, an arbitrary value

is allowed as type argument to Literal[...], but type checkers may

impose restrictions.

"""

# There is no '_type_check' call because arguments to Literal[...] are

# values, not types.

parameters = _flatten_literal_params(parameters)

try:

parameters = tuple(p for p, _ in _deduplicate(list(_value_and_type_iter(parameters))))

except TypeError: # unhashable parameters

pass

return _LiteralGenericAlias(self, parameters)

@_SpecialForm

def TypeAlias(self, parameters):

"""Special form for marking type aliases.

Use TypeAlias to indicate 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")

@_SpecialForm

def Concatenate(self, parameters):

"""Special form for annotating higher-order functions.

``Concatenate`` can be used in conjunction with ``ParamSpec`` and

``Callable`` to represent a higher-order function which adds, removes or

transforms the parameters of a callable.

For example::

Callable[Concatenate[int, P], int]

See PEP 612 for detailed information.

"""

if parameters == ():

raise TypeError("Cannot take a Concatenate of no types.")

if not isinstance(parameters, tuple):

parameters = (parameters,)

if not (parameters[-1] is ... or isinstance(parameters[-1], ParamSpec)):

raise TypeError("The last parameter to Concatenate should be a "

"ParamSpec variable or ellipsis.")

msg = "Concatenate[arg, ...]: each arg must be a type."

parameters = (*(_type_check(p, msg) for p in parameters[:-1]), parameters[-1])

return _ConcatenateGenericAlias(self, parameters)

@_SpecialForm

def TypeGuard(self, parameters):

"""Special typing construct for marking user-defined type predicate functions.

``TypeGuard`` can be used to annotate the return type of a user-defined

type predicate 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 predicate".

Sometimes it would be convenient to use a user-defined boolean function

as a type predicate. Such a function should use ``TypeGuard[...]`` or

``TypeIs[...]`` as its return type to alert static type checkers to

this intention. ``TypeGuard`` should be used over ``TypeIs`` when narrowing

from an incompatible type (e.g., ``list[object]`` to ``list[int]``) or when

the function does not return ``True`` for all instances of the narrowed type.

Using ``-> TypeGuard[NarrowedType]`` 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 ``NarrowedType``.

For example::

def is_str_list(val: list[object]) -> TypeGuard[list[str]]:

'''Determines whether all objects in the list are strings'''

return all(isinstance(x, str) for x in val)

def func1(val: list[object]):

if is_str_list(val):

# Type of ``val`` is narrowed to ``list[str]``.

print(" ".join(val))

else:

# Type of ``val`` remains as ``list[object]``.

print("Not a list of strings!")

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 predicates is left to the user.

``TypeGuard`` also works with type variables. For more information, see

PEP 647 (User-Defined Type Guards).

"""

item = _type_check(parameters, f'{self} accepts only single type.')

return _GenericAlias(self, (item,))

@_SpecialForm

def TypeIs(self, parameters):

"""Special typing construct for marking user-defined type predicate functions.

``TypeIs`` can be used to annotate the return type of a user-defined

type predicate function. ``TypeIs`` only accepts a single type argument.

At runtime, functions marked this way should return a boolean and accept

at least one argument.

``TypeIs`` 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 predicate".

Sometimes it would be convenient to use a user-defined boolean function

as a type predicate. Such a function should use ``TypeIs[...]`` or

``TypeGuard[...]`` as its return type to alert static type checkers to

this intention. ``TypeIs`` usually has more intuitive behavior than

``TypeGuard``, but it cannot be used when the input and output types

are incompatible (e.g., ``list[object]`` to ``list[int]``) or when the

function does not return ``True`` for all instances of the narrowed type.

Using ``-> TypeIs[NarrowedType]`` 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 intersection of the argument's original type and

``NarrowedType``.

3. If the return value is ``False``, the type of its argument

is narrowed to exclude ``NarrowedType``.

For example::

from typing import assert_type, final, TypeIs

class Parent: pass

class Child(Parent): pass

@final

class Unrelated: pass

def is_parent(val: object) -> TypeIs[Parent]:

return isinstance(val, Parent)

def run(arg: Child | Unrelated):

if is_parent(arg):

# Type of ``arg`` is narrowed to the intersection

# of ``Parent`` and ``Child``, which is equivalent to

# ``Child``.

assert_type(arg, Child)

else:

# Type of ``arg`` is narrowed to exclude ``Parent``,

# so only ``Unrelated`` is left.

assert_type(arg, Unrelated)