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r r' c < e Zd ZdZdZej defd ZdS )r% z*An ABC with one abstract method __float__.r r c d S r r r s r __float__zSupportsFloat.__float__ r r N) r r r r r r r floatr r r r r% r% H 88 u
r r% c < e Zd ZdZdZej defd ZdS )r$ z,An ABC with one abstract method __complex__.r r c d S r r r s r __complex__zSupportsComplex.__complex__ r r N) r r r r r r r complexr r r r r$ r$ sH ::
r r$ c < e Zd ZdZdZej defd ZdS )r# z*An ABC with one abstract method __bytes__.r r c d S r r r s r __bytes__zSupportsBytes.__bytes__ r r N) r r r r r r r bytesr r r r r# r# r r r# c 8 e Zd ZdZej defd ZdS )r& r r c d S r r r s r __index__zSupportsIndex.__index__ r r N)r r r r r r r r r r r r& r& sB s
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r r c d S r r r s r __abs__zSupportsAbs.__abs__ r r N) r r r r r r r r r r r r r" r" sN T
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r r( c B e Zd ZdZdZej ddedefd Z dS ) r) zeProtocol for simple I/O reader instances.
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r .sizer c dS )zRead data from the input stream and return it.
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r datar c dS )zIWrite *data* to the output stream and return the number of items written.Nr )r r s r writez Writer.write/ r r N)
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_& tG | _' | _( | _) | _* S )aI Create new typed dict class object.
This method is called when TypedDict is subclassed,
or when TypedDict is instantiated. This way
TypedDict supports all three syntax forms described in its docstring.
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zHcannot inherit from both a TypedDict type and a non-TypedDict base classNzCannot combine closed=z and extra_itemsc 3 J K | ] }t |t j V d S r )r r rc r s r ri z)_TypedDictMeta.__new__.<locals>.<genexpr> s. @@Q:a 00@@@@@@r r r rD __orig_bases__r !get_annotate_from_class_namespace __annotate__ownerz?TypedDict('Name', {f0: t0, f1: t1, ...}); each t must be a typec P i | ]"\ }}|t j |j #S r r re r rg ntprh tp_dicts r
<dictcomp>z*_TypedDictMeta.__new__.<locals>.<dictcomp> sD + + + 2 v)"c':LMMM+ + +r c B i | ]\ }}|t j | S r rd )rg r r rh s r r z*_TypedDictMeta.__new__.<locals>.<dictcomp> s< + + + 2 v)"c22+ + +r __required_keys____optional_keys____readonly_keys____mutable_keys____extra_items__z5Special key __extra_items__ does not support Requiredz8Special key __extra_items__ does not support NotRequiredTFc i }D ]B}|t u r |j }|t j || | }| | CIt j | }| t
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annotationlibcall_annotate_functionupdater6 STRINGitemsannotations_to_string
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= r )r r r rJ rX r r r r r rT rT sQ $ * ! ! ! ! !r rT c ~ t |t st d t d|dddt S )aq A simple typed namespace. At runtime it is equivalent to a plain dict.
TypedDict creates a dictionary type such that a type checker will expect all
instances to have a certain set of keys, where each key is
associated with a value of a consistent type. This expectation
is not checked at runtime.
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 an additional equivalent form::
Point2D = TypedDict('Point2D', {'x': int, 'y': int, 'label': str})
By default, all keys must be present in a TypedDict. It is possible
to override this by specifying totality::
class Point2D(TypedDict, total=False):
x: int
y: int
This means that a Point2D TypedDict can have any of the keys omitted. A type
checker is only expected to support a literal False or True as the value of
the total argument. True is the default, and makes all items defined in the
class body be required.
The Required and NotRequired special forms can also be used to mark
individual keys as being required or not required::
class Point2D(TypedDict):
x: int # the "x" key must always be present (Required is the default)
y: NotRequired[int] # the "y" key can be omitted
See PEP 655 for more details on Required and NotRequired.
z9TypedDict[...] should be used with a single dict argumentz<inline TypedDict>TrV )r r0 r rR rX r r s r r! r! sW b $%% K
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r c , t | t S )a 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
)r _TYPEDDICT_TYPESr s r r? r? s " .///r r- c | S )a 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.
r )r` typs r r- r- s
r rT c z t | t j rt | j S t | d r5| j t t t fv rt | j d S t | t j
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** #HL-@@ @r c t j | ||d }t j dk rt | ||| |r|S d | D S )a 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.
T)globalnslocalnsinclude_extrasr c 4 i | ]\ }}|t | S r rb )rg kr s r r z"get_type_hints.<locals>.<dictcomp>M s& ===1=##===r )r r< r r _clean_optionalr" )r ro rp rq hints r r< r< % sr @ $ (GD
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====r c j t | t j sdS | j d t urdS dS )z detects Union[..., None] patternFr T)r r _UnionGenericAliasr _NoneTyper s r _could_be_inserted_optionalry Q s7 !V 677 5 :b> * *5tr c ( |rt | t rd S t j | }|sd S | j }| D ]C\ }}t
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S dS )a6 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
N) r r ri r+ _BaseGenericAliasr r r r
r_ rc r] s r r9 r9 si b&0 1 1 b63V5H(/; < < !=
> !tr c T t | t j r| j g| j R S t | t j t j f rW| j }t | t j j u r.|d t ur t |dd |d f}|S dS )a 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)
r Nr r )r r ri r_ __metadata__r r r r r9 r r r\ Ellipsisr9 )r ress r r8 r8 s b&0 1 1 5M4BO44 4 b6/1DE F F +C"~~ !999c!fH>T>TCH~~s2w/Jrr rK c & t | d )a& Special marker indicating that an assignment should
be recognized as a proper type alias definition by type
checkers.
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Predicate: TypeAlias = Callable[..., bool]
It's invalid when used anywhere except as in the example above.
is not subscriptabler r s r rK rK s 4666777r c * fd| _ | _ d S )Nc t uS r )rW r s r <lambda>z _set_default.<locals>.<lambda> s WI%= r ) has_default __default__)
type_paramr s `r _set_defaultr s" = = = =J $Jr c D t d }|dk r || _ d S d S )Nr r ry )r r ) typevarlikedef_mods r _set_moduler s4 A G%%%!( &%r c e Zd ZdZdZeZdS )
_DefaultMixinz Mixin for TypeVarLike defaults.r N)r r r r r r r r r r r r s ))IHHHr r c e Zd ZdedefdZdS )_TypeVarLikeMeta_TypeVarLikeMeta__instancer c , t || j S r )r _backported_typevarlike)r r s r r z"_TypeVarLikeMeta.__instancecheck__ s *c&ABBBr N)r r r r boolr r r r r r s> C3 C4 C C C C C Cr r )r c < e Zd ZdZej ZdddedddZddZ dS ) r zType variable.NF)boundr r r infer_variancec t t d rt j |g|R ||||d n3t j |g|R |||d |r|s|rt d | _ t | t
fd}| _ S )NrL r r r r r r r z1Variance cannot be specified with infer_variance.c r6| j t | k r |j fz
}|S r )r __parameters__indexr: r )aliasr typevars r _tvar_prepare_substz,TypeVar.__new__.<locals>._tvar_prepare_subst sN ''))3 ,227;;s4yyHHW 0 22D r )r1 r r r __infer_variance__r r __typing_prepare_subst__)
r r r r r r r constraintsr r s
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< . H H H53<M8FH H H !. [ [ [53<M[ [ [! Zy ZM Z$%XYYY-;* ' * * *
0CG ,Nr r c 2 t dt d )Ntype 'z(.TypeVar' is not an acceptable base typer r s r r zTypeVar.__init_subclass__ s WX W W WXX Xr r N)
r r r r r r r rW r r r r r r r sb "(. 37 #5 %e : Y Y Y Y Y Yr r r c " e Zd ZdZdZd Zd ZdS )
_Immutablez3Mixin to indicate that object should not be copied.r c | S r r r s r __copy__z_Immutable.__copy__% Kr c | S r r )r memos r __deepcopy__z_Immutable.__deepcopy__( r r N)r r r r r r r r r r r r ! s= AA r r c $ e Zd ZdZd Zd Zd ZdS )r aQ 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.
c || _ d S r r_ r rX s r r zParamSpecArgs.__init__7
$DOOOr c | j j dS )Nz.argsr_ r r s r r zParamSpecArgs.__repr__: s o.555 5r c Z t |t st S | j |j k S r )r r r* r_ r s r r. zParamSpecArgs.__eq__= s* e]33
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% % % 6 6 6 7 7 7 7 7r c $ e Zd ZdZd Zd Zd ZdS )r
a[ 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.
c || _ d S r r r s r r zParamSpecKwargs.__init__N r r c | j j dS )Nz.kwargsr r s r r zParamSpecKwargs.__repr__Q s o.777 7r c Z t |t st S | j |j k S r )r r
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fd}|_ S )NrL r r c | j }| }|t | k r r g |j }|t | k rt d| t | dk r&t
j |d s |dk sJ |f}nJt || t r/g |d | t || ||dz d R }|S )NToo few arguments for r r ) r r r: r r r r _is_param_exprr r9 r" )r r r# i paramspecs r _paramspec_prepare_substz3ParamSpec.__new__.<locals>._paramspec_prepare_substx s -LL++D >>i&;&;&=&=>9T99#89DD >>#$DU$D$DEEEv;;!##F,A$q',J,J# 6666 7DD Q.. FET"1"XEuT!W~~EQUVV EED r )r1 r r r r r r r ) r r r r r r r r r s @r r zParamSpec.__new__f s v//
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r r r r r r r rW r r r r r r r a sd &&"("2 (, #5#()# # # # # J [ [ [ [ [ [r c e Zd ZdZej Zed Zed Z dddde
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Zd Zd ZddZdS )r a' 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.
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callable.
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Callable[Concatenate[int, P], int]
See PEP 612 for detailed information.
)r/ r s r r r s $D*555r rN c ^ t j || d }t j | |f S )a Special typing form used to annotate the return type of a user-defined
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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``.
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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``.
...
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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).
accepts only a single type.r re r r r r s r rN rN s5 X !*.S.S.STT#D4'222r rO c ^ t j || d }t j | |f S )aw Special typing form used to annotate the return type of a user-defined
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def is_awaitable(val: object) -> TypeIs[Awaitable[Any]]:
return hasattr(val, '__await__')
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if is_awaitable(val):
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r2 r3 r4 s r rO rO s5 L !*.S.S.STT#D4'222r rM c e Zd Zd ZdS )
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It accepts a single type argument, which must be a valid type expression.
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the type T or types that are assignable to T.
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def cast[T](typ: TypeForm[T], value: Any) -> T: ...
reveal_type(cast(int, "x")) # int
See PEP 747 for more information.
r2 r3 r4 s r rM rM M s4 & !*.S.S.STT#D4'222r r
c & t | d )aD 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.
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r r r
s r r r s 4666777r rR c & t | d )a The bottom type, a type that has no members.
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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")
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never_call_me(arg) # ok, arg is of type Never
r r r
s r rR rR s 0 4666777r rU c h t j || j d }t j | |f S )a 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.
r2 r re r r r4 s r rU rU s6 " !*.Y.Y.YZZ#D4'222r c h t j || j d }t j | |f S )a` A special typing construct to mark a key of a TypedDict as
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class Movie(TypedDict):
title: str
year: NotRequired[int]
m = Movie(
title='The Matrix', # typechecker error if key is omitted
year=1999,
)
r2 r? r4 s r rV rV s6 !*.Y.Y.YZZ#D4'222r c h t j || j d }t j | |f S )a A special typing construct to mark an item of a TypedDict as read-only.
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class Movie(TypedDict):
title: ReadOnly[str]
year: int
def mutate_movie(m: Movie) -> None:
m["year"] = 1992 # allowed
m["title"] = "The Matrix" # typechecker error
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r2 r? r4 s r rT rT s6 !*.Y.Y.YZZ#D4'222r a Type unpack operator.
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example:
# For some generic class `Foo`:
Foo[Unpack[tuple[int, str]]] # Equivalent to Foo[int, str]
Ts = TypeVarTuple('Ts')
# Specifies that `Bar` is generic in an arbitrary number of types.
# (Think of `Ts` as a tuple of an arbitrary number of individual
# `TypeVar`s, which the `Unpack` is 'pulling out' directly into the
# `Generic[]`.)
class Bar(Generic[Unpack[Ts]]): ...
Bar[int] # Valid
Bar[int, str] # Also valid
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Foo[*tuple[int, str]]
class Bar(Generic[*Ts]): ...
The operator can also be used along with a `TypedDict` to annotate
`**kwargs` in a function signature. For instance:
class Movie(TypedDict):
name: str
year: int
# This function expects two keyword arguments - *name* of type `str` and
# *year* of type `int`.
def foo(**kwargs: Unpack[Movie]): ...
Note that there is only some runtime checking of this operator. Not
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For more information, see PEP 646 and PEP 692.
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type such as ``Tuple[int, str]``.
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class Array(Generic[*Ts]): ...
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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
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us to parameterise the class with an *arbitrary* number of type parameters.
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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]
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reveal_type(x)
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r _ASSERT_NEVER_REPR_MAX_LENGTHd r, r c t | }t | t k r|dt dz }t d| )a1 Assert to the type checker that a line of code is unreachable.
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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.
N...z*Expected code to be unreachable, but got: )r r: rq AssertionError)r r s r r, r, ' sN ( S u::5 5 58889EAE Q% Q QRRRr )
eq_default
order_defaultkw_only_defaultfrozen_defaultfield_specifiersrv rw rx ry rz .r c & fd}|S )a 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.
- ``frozen_default`` indicates whether the ``frozen`` 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.
c $ d| _ | S )N)rv rw rx ry rz r )__dataclass_transform__) cls_or_fnrv rz ry rx r rw s r decoratorz&dataclass_transform.<locals>.decorator s, (!.#2"0$4
1 1I - r r )rv rw rx ry rz r r s `````` r r/ r/ F sC R r rC _F)r c F d| _ n# t t f$ r Y nw xY w| S )aH 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.
There is no runtime checking of these properties. The decorator
sets the ``__override__`` attribute to ``True`` on the decorated object
to allow runtime introspection.
See PEP 698 for details.
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xZS ) r0 a Indicate that a class, function or overload is deprecated.
When this decorator is applied to an object, the type checker
will generate a diagnostic on usage of the deprecated object.
Usage:
@deprecated("Use B instead")
class A:
pass
@deprecated("Use g instead")
def f():
pass
@overload
@deprecated("int support is deprecated")
def g(x: int) -> int: ...
@overload
def g(x: str) -> int: ...
The warning specified by *category* will be emitted at runtime
on use of deprecated objects. For functions, that happens on calls;
for classes, on instantiation and on creation of subclasses.
If the *category* is ``None``, no warning is emitted at runtime.
The *stacklevel* determines where the
warning is emitted. If it is ``1`` (the default), the warning
is emitted at the direct caller of the deprecated object; if it
is higher, it is emitted further up the stack.
Static type checker behavior is not affected by the *category*
and *stacklevel* arguments.
The deprecation message passed to the decorator is saved in the
``__deprecated__`` attribute on the decorated object.
If applied to an overload, the decorator
must be after the ``@overload`` decorator for the attribute to
exist on the overload as returned by ``get_overloads()``.
See PEP 702 for details.
r categoryr messager r r Nc t |t s$t dt | j || _ || _ || _ d S )Nz2Expected an object of type str for 'message', not )r r r r r r r r )r r r r s r r zdeprecated.__init__ s^ gs++
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zCollect all type variables and parameter specifications in args
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assert _collect_parameters((T, Callable[P, T])) == (T, P)
F__typing_subst__r r Tr r r r ) r r r r" _collect_parametersr! r1 rB rW r r ) r r r r r r r r r s r r r &
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r > r r r c e Zd Zd ZdS )_NamedTupleMetac < t |v sJ |D ](}|t ur |t j urt d )t d |D }dv r d }ndv r d d }ni }g }|D ]^}|v r| | |r@t d| dt
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s0 SST4;#6#6%%DSSSSSSr r r
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s U""""~ r c |t u r|rd}d}nLd}d| d| d}d|z dz }n8|%|rt d
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|S )ao Typed version of namedtuple.
Usage::
class Employee(NamedTuple):
name: str
id: int
This is equivalent to::
Employee = collections.namedtuple('Employee', ['name', 'id'])
The resulting class has an extra __annotations__ attribute, giving a
dict that maps field names to types. (The field names are also in
the _fields attribute, which is part of the namedtuple API.)
An alternative equivalent functional syntax is also accepted::
Employee = NamedTuple('Employee', [('name', str), ('id', int)])
z3Creating NamedTuple classes using keyword argumentszq{name} is deprecated and will be disallowed in Python {remove}. Use the class-based or functional syntax instead.rF rH z = NamedTuple(z, [])`z{name} is deprecated and will be disallowed in Python {remove}. To create a NamedTuple class with 0 fields using the functional syntax, pass an empty list, e.g. r Nz\Cannot pass `None` as the 'fields' parameter and also specify fields using keyword argumentsrG zIEither list of fields or keywords can be provided to NamedTuple, not bothz3.15)r r; r r r ) rJ r r r r' r r" r r r r )rK rL r rN rP rO nts r r r
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> 'M r c e Zd ZdZdS )r a Base class for classes that implement the buffer protocol.
The buffer protocol allows Python objects to expose a low-level
memory buffer interface. Before Python 3.12, it is not possible
to implement the buffer protocol in pure Python code, or even
to check whether a class implements the buffer protocol. In
Python 3.12 and higher, the ``__buffer__`` method allows access
to the buffer protocol from Python code, and the
``collections.abc.Buffer`` ABC allows checking whether a class
implements the buffer protocol.
To indicate support for the buffer protocol in earlier versions,
inherit from this ABC, either in a stub file or at runtime,
or use ABC registration. This ABC provides no methods, because
there is no Python-accessible methods shared by pre-3.12 buffer
classes. It is useful primarily for static checks.
N)r r r r r r r r r
s r r: c | j d| j S # t $ r& t dt | j dw xY w)a Return the class's "original" bases prior to modification by `__mro_entries__`.
Examples::
from typing import TypeVar, Generic
from typing_extensions import NamedTuple, TypedDict
T = TypeVar("T")
class Foo(Generic[T]): ...
class Bar(Foo[int], float): ...
class Baz(list[str]): ...
Eggs = NamedTuple("Eggs", [("a", int), ("b", str)])
Spam = TypedDict("Spam", {"a": int, "b": str})
assert get_original_bases(Bar) == (Foo[int], float)
assert get_original_bases(Baz) == (list[str],)
assert get_original_bases(Eggs) == (NamedTuple,)
assert get_original_bases(Spam) == (TypedDict,)
assert get_original_bases(int) == (object,)
r z"Expected an instance of type, not N)r r r r r r r r s r r: r: ( sf * <##$4cmDD D KT#YY5GKK
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UserId = NewType('UserId', int)
def name_by_id(user_id: UserId) -> str:
...
UserId('user') # Fails type check
name_by_id(42) # Fails type check
name_by_id(UserId(42)) # OK
num = UserId(5) + 1 # type: int
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d Zd Z xZS xZS )rL a Create named, parameterized type aliases.
This provides a backport of the new `type` statement in Python 3.12:
type ListOrSet[T] = list[T] | set[T]
is equivalent to:
T = TypeVar("T")
ListOrSet = TypeAliasType("ListOrSet", list[T] | set[T], type_params=(T,))
The name ListOrSet can then be used as an alias for the type it refers to.
The type_params argument should contain all the type parameters used
in the value of the type alias. If the alias is not generic, this
argument is omitted.
Static type checkers should only support type aliases declared using
TypeAliasType that follow these rules:
- The first argument (the name) must be a string literal.
- The TypeAliasType instance must be immediately assigned to a variable
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r ) type_paramsr c t |t st d t |t st d || _ || _ d}g }|D ]}t |t t t f rt | rt d| t |dt t u}|r|st d|d |rd}t |t r| | |
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Raise a TypeError for arguments that are not Protocols.
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This complements docstrings.
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https://docs.python.org/3/library/inspect.html#inspect.get_annotations
This backport adds the *format* argument introduced by PEP 649. The
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* VALUE: the annotations are returned as-is. This is the default and
it is compatible with the behavior on previous Python versions.
* FORWARDREF: return annotations as-is if possible, but replace any
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PEP 649 relies on language changes that cannot be backported; the
typing-extensions implementation simply returns the same result as VALUE.
* STRING: return annotations as strings, in a format close to the original
source. Again, this behavior cannot be replicated directly in a backport.
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VALUE semantics and then stringifies them.
The purpose of this backport is to allow users who would like to use
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|||j < t j dk r!t j ||||| j hz S t j |||||| j hz S )a Evaluate a forward reference as a type hint.
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