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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 wrapper submodules for re and io related types.
* 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!
)abstractmethodABCMetaN) defaultdict)WrapperDescriptorTypeMethodWrapperTypeMethodDescriptorType GenericAlias)_idfuncTypeVar ParamSpec TypeVarTuple
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ByteString ContainerContextManagerHashable ItemsViewIterableIteratorKeysViewMapping MappingViewMutableMappingMutableSequence
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CollectionAsyncGeneratorAsyncContextManager
Reversible SupportsAbs
SupportsBytesSupportsComplex
SupportsFloat
SupportsIndex SupportsInt
SupportsRoundChainMapCounterDequeDict DefaultDictList OrderedDictSet FrozenSet
NamedTuple TypedDict GeneratorBinaryIOIOMatchPatternTextIOAnyStr assert_type assert_nevercastclear_overloadsdataclass_transformfinalget_args
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TYPE_CHECKING TypeAlias TypeGuardr UnpackFallow_special_formsc \ | t d S t | t rt | || S | S )z=For converting None to type(None), and strings to ForwardRef.N)moduleis_class)type
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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.
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D)%= >@ @ry c | j t j j u xr t | dk( xr t |d S )aC 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.
r )r~ collectionsabcr lenr )typargss rw _should_unflatten_callable_argsr s@ & +//222 =Ta ;N47$; <ry c V t | t r6| j dk( r | j S | j d| j S | du ryt | t j
r | j S t | t r ddj d | D z dz S t | S ) a; Return the repr() of an object, special-casing types (internal helper).
If obj is a type, we return a shorter version than the default
type.__repr__, based on the module and qualified name, which is
typically enough to uniquely identify a type. For everything
else, we fall back on repr(obj).
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|dd D ] }||vs|j | t | S )a Collect all type variables and parameter specifications in args
in order of first appearance (lexicographic order).
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>>> P = ParamSpec('P')
>>> T = TypeVar('T')
>>> _collect_parameters((T, Callable[P, T]))
(~T, ~P)
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3% 6788 z?D t|$v% @PSu U##'& D6; < < ry c g }| D ]= }t |dd }||r|d du s|j | -|j | ? |S )N __typing_unpacked_tuple_args__.)r extendr )r newargsrv subargss rw _unpack_argsr 3 sR G# ?F GBK34F NN7 # NN3 Nry unhashable_fallbackc h t j | S # t $ r |s t | cY S w xY wr )dictfromkeysr _deduplicate_unhashable)paramsr s rw _deduplicater = s6 /}}V$$ /" &v.. /s 11c D g }| D ] }||vs|j | |S r )r )unhashable_paramsnew_unhashabler s rw r r G s/ N
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a,eoo> ? MM!** % MM! f$? @@ry c g }| D ]? }t |t r |j |j /|j | A t | S )zHInternal helper for Literal creation: flatten Literals among parameters.)rt _LiteralGenericAliasr r r r r s rw _flatten_literal_paramsr i sD
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j r$t j t j | S | j# | S | S )zEvaluate 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.
r c 3 V K | ]! }t |t r t | n| # y wr )rt ru r r rv s rw r z _eval_type.. s* %C $.c3#7
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ajj H a & g6 6 a ) ##HLL': :;;w' ' Hry c e Zd ZdZdZd Zy)_Finalz Mixin to prohibit subclassing.) __weakref__c " d|vr t d y )N_rootz&Cannot subclass special typing classesr )r r r s rw __init_subclass__z_Final.__init_subclass__ s $ DE E ry N)r r r __doc__ __slots__r r ry rw r
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c e Zd Zd Zy)_LiteralSpecialFormc N t |t s|f} | j | g| S r )rt r r rB s rw rC z _LiteralSpecialForm.__getitem__ s) *e,$ J t}}T/J//ry N)r r r rC r ry rw rE rE s 0ry rE c ( e Zd Z fdZ fdZ xZS )_AnyMetac H | t u r t d t |
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" "ry rH c " e Zd ZdZ fdZ xZS )r aW 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.
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static type checkers. At runtime, Any should not be used with instance
checks.
c H | t u r t d t |
| S )NzAny cannot be instantiated)r r rJ __new__r r kwargsrK s rw rQ z Any.__new__' s% #: 89 9ws##ry )r r r r rQ rM rN s @rw r r s $ $ry r ) metaclassc t | d )a 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.
is not subscriptabler rB s rw ra ra - s tf 12
33ry c t | d )ad 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
rV r rB s rw r] r] B s , tf 12
33ry c t | d )as 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
rV r rB s rw rh rh [ s " tf 12
33ry c t | d )a
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.
rV r rB s rw r\ r\ o s 0 tf 12
33ry c : t || d }t | |f S )a> 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().
accepts only single type.r r} r r r s rw r r ' & zdV+E#F GD w ''ry c : t || d }t | |f S )a 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.
r[ r\ r] s rw r r r^ ry c |dk( r t d t |t s|f}dt fd|D }t | }t | dk( r|d S t | dk( rt d |v rt
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| | S ) a 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].
r z Cannot take a Union of no types.z)Union[arg, ...]: each arg must be a type.c 3 6 K | ] }t | y wr r r r r s rw r zUnion.. s ?Jq{1c*J r r Nr name)r rt r r r rs r r r r s @rw r r s > R:;; j% ( ]
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DD dJ //ry c t | |f S )zUsed 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).
r2 )leftrights rw _make_unionrl s u ry c H t || d }t |t d f S )z,Optional[X] is equivalent to Union[X, None].z requires a single type.N)r r rs )r r rv s rw r r s+ jTF*B"C
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t | } t d t t t | D }t
| | S # t
$ r Y w xY w)a 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.
c 3 & K | ] \ }}| y wr r )r r _s rw r zLiteral..
s ^)]A1)]s )r r r r _value_and_type_iterr r rB s rw r r sW 2 )4J
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s -A AAc t | d )a: 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.
rV r rB s rw rk rk s tf 12
33ry c |dk( r t d t |t s|f}|d du s t |d t s t d dg fd|dd D |d }t | | S ) ac 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.
r z&Cannot take a Concatenate of no types.r .zMThe last parameter to Concatenate should be a ParamSpec variable or ellipsis.z/Concatenate[arg, ...]: each arg must be a type.c 3 6 K | ] }t | y wr rb rc s rw r z Concatenate..; s A AK3' rd N)r rt r r r rh s @rw r r % s R@AA j% ( ]
rNc !Z
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;CRACR AR:b>RJ #D* 55ry c : t || d }t | |f S )a Special typing construct for marking user-defined type guard functions.
``TypeGuard`` can be 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_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 guards is left to the user.
``TypeGuard`` also works with type variables. For more information, see
PEP 647 (User-Defined Type Guards).
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a Parameterizes a generic class.
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However, note that this method is also called when defining generic
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are wrappers around builtin collections and ABCs in collections.abc. These must
have 'name' always set. If 'inst' is False, then the alias can't be instantiated;
this is used by e.g. typing.List and typing.Dict.
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) )ry r c < t || d }t | |f S )a Type unpack operator.
The type unpack operator takes the child types from some container type,
such as `tuple[int, str]` or a `TypeVarTuple`, and 'pulls them out'.
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# 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
From Python 3.11, this can also be done using the `*` operator::
Foo[*tuple[int, str]]
class Bar(Generic[*Ts]): ...
And from Python 3.12, it can be done using built-in syntax for generics::
Foo[*tuple[int, str]]
class Bar[*Ts]: ...
The operator can also be used along with a `TypedDict` to annotate
`**kwargs` in a function signature::
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
everything the runtime allows may be accepted by static type checkers.
For more information, see PEPs 646 and 692.
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_ProtocolMetac 6 |dk( r |t fk( rnvt |v rn|D ]i }|t t hv r|j t j |j g v r?t |t rt |dd r]t d| t | , | |||fi |S )Nr rb Fz5Protocols can only inherit from other protocols, got ) r r rv r _PROTO_ALLOWLISTr r r r r rJ rQ )mclsrg r# namespacerS r rK s rw rQ z_ProtocolMeta.__new__? s : %G:"5
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d t | | ryt }| j D ] } ||| }||| j vs y y# t $ r Y yw xY w)Nrb Fre r T) r rs r< r rJ r r r rd r rf )r instancer r r rK s rw r< z _ProtocolMeta.__instancecheck__p s (?))#x8 8sNE27,X6 6 3U;,. < =
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|t j j s^||v sct |t stt |dd s t c S y)Nrb Frg T) r r r rd rn r rt r r r( r r )r r4 r r rr s rw r r s << NE 2 &&MMDt}}$==&.)) "$(92>K; (?(?@K' ug.75.RW3X " " ! ' ry c . e Zd ZdZdZdZdZ fdZ xZS )r a_ Base class for protocol classes.
Protocol classes are defined as::
class Proto(Protocol):
def meth(self) -> int:
...
Such classes are primarily used with static type checkers that recognize
structural subtyping (static duck-typing).
For example::
class C:
def meth(self) -> int:
return 0
def func(x: Proto) -> int:
return x.meth()
func(C()) # Passes static type check
See PEP 544 for details. Protocol classes decorated with
@typing.runtime_checkable act as simple-minded runtime protocols that check
only the presence of given attributes, ignoring their type signatures.
Protocol classes can be generic, they are defined as::
class GenProto[T](Protocol):
def meth(self) -> T:
...
r TFc : t | |i | | j j dd s!t d | j
D | _ d| j vr t | _ | j r)| j t j u r t | _ y y y )Nrb Fc 3 , K | ] }|t u y wr r r r s rw r z-Protocol.__init_subclass__.. s "H-Q1=-s rh ) rJ r r r anyr rb r rh r r ru rR s rw r zProtocol.__init_subclass__ s
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_AnnotatedAliasa 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.
The metadata itself is stored in a '__metadata__' attribute as a tuple.
c t |t r|j |z }|j }t | ||d || _ y )Nr rf )rt r __metadata__r~ rJ r )r r metadatarK s rw r z_AnnotatedAlias.__init__ sD fo . **X5H&&F
k: $ry c X t | dk( sJ |d }t || j S r )r r r )r r new_types rw r z_AnnotatedAlias.copy_with s0 6{a !9 x):):;;ry c dj t | j dj d | j D S )Nztyping.Annotated[{}, {}]r c 3 2 K | ] }t | y wr )r r s rw r z+_AnnotatedAlias.__repr__.. s 9'8!d1g'8r )formatr r~ r r r) s rw r* z_AnnotatedAlias.__repr__ s9 )00 t ' II9t'8'89 9
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"ry r c D e Zd ZdZdZd Zd Z ed d Zd Z y )
r a+ Add context-specific metadata to a type.
Example: Annotated[int, runtime_check.Unsigned] indicates to the
hypothetical runtime_check module that this type is an unsigned int.
Every other consumer of this type can ignore this metadata and treat
this type as int.
The first argument to Annotated must be a valid type.
Details:
- It's an error to call `Annotated` with less than two arguments.
- Access the metadata via the ``__metadata__`` attribute::
assert Annotated[int, '$'].__metadata__ == ('$',)
- Nested Annotated types are flattened::
assert Annotated[Annotated[T, Ann1, Ann2], Ann3] == Annotated[T, Ann1, Ann2, Ann3]
- Instantiating an annotated type is equivalent to instantiating the
underlying type::
assert Annotated[C, Ann1](5) == C(5)
- Annotated can be used as a generic type alias::
type Optimized[T] = Annotated[T, runtime.Optimize()]
# type checker will treat Optimized[int]
# as equivalent to Annotated[int, runtime.Optimize()]
type OptimizedList[T] = Annotated[list[T], runtime.Optimize()]
# type checker will treat OptimizedList[int]
# as equivalent to Annotated[list[int], runtime.Optimize()]
- Annotated cannot be used with an unpacked TypeVarTuple::
type Variadic[*Ts] = Annotated[*Ts, Ann1] # NOT valid
This would be equivalent to::
Annotated[T1, T2, T3, ..., Ann1]
where T1, T2 etc. are TypeVars, which would be invalid, because
only one type should be passed to Annotated.
r c t d )Nz&Type Annotated cannot be instantiated.r r r rS s rw rQ zAnnotated.__new__E s @AAry c N t |t s|f} | j | g| S r )rt r _class_getitem_inner)r r s rw ri zAnnotated.__class_getitem__H s+ &%( YF's''5f55ry Tr c t | dk r t d t |d r t d d}t |d |d }t |dd }t || S ) Nr zUAnnotated[...] should be used with at least two arguments (a type and an annotation).r z?Annotated[...] should not be used with an unpacked TypeVarTuplez$Annotated[t, ...]: t must be a type.Trn re )r r r r r r )r r r r r s rw r z Annotated._class_getitem_innerM ss v;? + ,
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ry N)
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ry r c V t | t r
t | dd st d| z d| _ t | _ | j D ]7 } t t | |d }|r | j j | 9 | S # t $ r}t d|d |d}~ww xY w)a: Mark a protocol class as a runtime protocol.
Such protocol can be used with isinstance() and issubclass().
Raise TypeError if applied to a non-protocol class.
This allows a simple-minded structural check very similar to
one trick ponies in collections.abc such as Iterable.
For example::
@runtime_checkable
class Closable(Protocol):
def close(self): ...
assert isinstance(open('/some/file'), Closable)
Warning: this will check only the presence of the required methods,
not their type signatures!
rb FzB@runtime_checkable can be only applied to protocol classes, got %rTNz,Failed to determine whether protocol member z is a method member) r r r r re r rf rd callablerp r )r r is_callablees rw rg rg a s & c7 #73+N "$'( ) ) #C
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s B
B(B##B(c |S )zCast a value to a type.
This returns the value unchanged. To the type checker this
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runtime we intentionally don't check anything (we want this
to be as fast as possible).
r )r r s rw rS rS s Jry c | S )a Ask a static type checker to confirm that the value is of the given type.
At runtime this does nothing: it returns the first argument unchanged with no
checks or side effects, no matter the actual type of the argument.
When a static 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
r )r r s rw rQ rQ s Jry c t | dd ri S t | t r?i }t | j D ] }|6t t
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a
Return type hints for an object.
This is often the same as obj.__annotations__, but it handles
forward references encoded as string literals and recursively replaces all
'Annotated[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. For classes, the search
order is globals first then locals.
- 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.
__no_type_check__Nr rg FT)r rr __wrapped__ __globals__z1{!r} is not a module, class, method, or function.rc r )r rt rs reversedrn r r r r r r GetSetDescriptorTyper varsitemsru r r rc _strip_annotations
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+# *0 'u`RWR]R]R_,`R_$!QQ0B10E-ER_,`` c5++ ,||HE% / )) % / umR8H ? G C*D 1E } c> *I ++16#;8
8 KE# 0"5K {{} e =JE eS ! *30@0@ A A E
!';Gd % #5\ekkm(\mda,>q,A)Am(\\K -aJ )]s J7 J=c t | t rt | j S t | d r0| j t
t fv rt | j d S t | t r>t d | j D }|| j k( r| S | j | S t | t rCt d | j D }|| j k( r| S t | j | S t | t j rQt d | j D }|| j k( r| S t j t j" | S | S )z(Strip the annotations from a given type.r~ r c 3 2 K | ] }t | y wr r r s rw r z%_strip_annotations.. HZ 0 3Zr c 3 2 K | ] }t | y wr r r s rw r z%_strip_annotations.. r r c 3 2 K | ] }t | y wr r r s rw r z%_strip_annotations.. r r )rt r r r~ r re rb r r} r r r r r r r r r )r
stripped_argss rw r r s !_%!!,,//q, ALLX{4K$K!!**Q-00!]# HQZZ HH
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AJJ &H m<< Hry c t | t rt S t | t t t
t f r | j S | t u rt S t | t j rt j S y)a Get the unsubscripted version of a type.
This supports generic types, Callable, Tuple, Union, Literal, Final, ClassVar,
Annotated, and others. Return None for unsupported types.
Examples::
>>> P = ParamSpec('P')
>>> assert get_origin(Literal[42]) is Literal
>>> assert get_origin(int) is None
>>> assert get_origin(ClassVar[int]) is ClassVar
>>> assert get_origin(Generic) is Generic
>>> assert get_origin(Generic[T]) is Generic
>>> assert get_origin(Union[T, int]) is Union
>>> assert get_origin(List[Tuple[T, T]][int]) is list
>>> assert get_origin(P.args) is P
N) rt r r r r r r r~ r r r tps rw rX rX ( s^ $ "o&"(,$o7 8}} W}"eoo& ry c * t | t r| j f| j z S t | t t
f r-| j }t | | rt |dd |d f}|S t | t j r | j S y)a Get type arguments with all substitutions performed.
For unions, basic simplifications used by Union constructor are performed.
Examples::
>>> T = TypeVar('T')
>>> assert get_args(Dict[str, int]) == (str, int)
>>> assert get_args(int) == ()
>>> assert get_args(Union[int, Union[T, int], str][int]) == (int, str)
>>> assert get_args(Union[int, Tuple[T, int]][str]) == (int, Tuple[str, int])
>>> assert get_args(Callable[[], T][int]) == ([], int)
Nr r ) rt r r~ r r} r r r r r r )r r s rw rW rW F s~ "o&
"//11"}l34kk *2s 3CR>3r7+C
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ry c " t | t S )a+ Check if an annotation is a TypedDict class.
For example::
>>> from typing import TypedDict
>>> class Film(TypedDict):
... title: str
... year: int
...
>>> is_typeddict(Film)
True
>>> is_typeddict(dict)
False
)rt r r s rw r[ r[ ` s b. ))ry d rv c p t | }t | t kD r |dt dz }t d| )a Statically assert 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.
Nr z*Expected code to be unreachable, but got: )r r _ASSERT_NEVER_REPR_MAX_LENGTHAssertionError)rv r s rw rR rR u s@ &
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| S # t $ r Y | S w xY w)aI Decorator to indicate that annotations are not type hints.
The argument must be a class or function; if it is a class, it
applies recursively to all methods and classes defined in that class
(but not to methods defined in its superclasses or subclasses).
This mutates the function(s) or class(es) in place.
r r| r NT)rt rs r r r r r r r r r
MethodType__func__r_ r )rv keyr s rw r_ r_ s #t s8C#s#CC 0###*:*:);1S\\N'KK3 d3s~~E
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s %C. . C;:C;c B t j fd }|S )zDecorator to give another decorator the @no_type_check effect.
This wraps the decorator with something that wraps the decorated
function in @no_type_check.
c . | i |}t | }|S r )r_ )r r r r s rw wrapped_decoratorz2no_type_check_decorator..wrapped_decorator s! $'$' T" ry )r r )r r s ` rw r` r` s( __Y
ry c t d )z*Helper for @overload to raise when called.zYou should not call an overloaded function. A series of @overload-decorated functions outside a stub module should always be followed by an implementation that is not @overload-ed.)NotImplementedError)r r s rw _overload_dummyr s
9 : :ry c t | d| } | t |j |j |j j
< t S # t $ r Y t S w xY w)a 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::
@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.
r )r _overload_registryr r __code__co_firstlinenor r )r fs rw rc rc sa @ j$'A
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s 7A A A c t | d| }|j t vrg S t |j }|j |vrg S t ||j j S )z6Return all defined overloads for *func* as a sequence.r )r r r r r values)r r mod_dicts rw rY rY s` j$'A||-- !!,,/H~~X% (//1 22ry c , t j y)z$Clear all overloads in the registry.N)r clearr ry rw rT rT
s ry c B d| _ | S # t t f$ r Y | S w xY w)a Decorator to indicate final methods and final classes.
Use this decorator to indicate to type checkers that the decorated
method cannot be overridden, and decorated class cannot be subclassed.
For example::
class Base:
@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
attempts to set the ``__final__`` attribute to ``True`` on the decorated
object to allow runtime introspection.
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contravariantCT_co)r boundrP a Deprecated alias to collections.abc.Callable.
Callable[[int], str] signifies a function that takes a single
parameter of type int and returns a str.
The subscription syntax must always be used with exactly two
values: the argument list and the return type.
The argument list must be a list of types, a ParamSpec,
Concatenate or ellipsis. The return type must be a single type.
There is no syntax to indicate optional or keyword arguments;
such function types are rarely used as callback types.
r rf )r )r1 r r r a] Deprecated alias to builtins.tuple.
Tuple[X, Y] is the cross-product type of X and Y.
Example: Tuple[T1, T2] is a tuple of two elements corresponding
to type variables T1 and T2. Tuple[int, float, str] is a tuple
of an int, a float and a string.
To specify a variable-length tuple of homogeneous type, use Tuple[T, ...].
rD rA rF rG r" r6 rB rC r a Deprecated alias to builtins.type.
builtins.type or typing.Type can be used to annotate class objects.
For example, suppose we have the following classes::
class User: ... # Abstract base for User classes
class BasicUser(User): ...
class ProUser(User): ...
class TeamUser(User): ...
And a function that takes a class argument that's a subclass of
User and returns an instance of the corresponding class::
def new_user[U](user_class: Type[U]) -> U:
user = user_class()
# (Here we could write the user object to a database)
return user
joe = new_user(BasicUser)
At this point the type checker knows that joe has type BasicUser.
c * e Zd ZdZdZedefd Zy)r= z(An ABC with one abstract method __int__.r r c y r r r) s rw __int__zSupportsInt.__int__
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ry r= c * e Zd ZdZdZedefd Zy)r; z*An ABC with one abstract method __float__.r r c y r r r) s rw __float__zSupportsFloat.__float__
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s# 6I
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ry r: c * e Zd ZdZdZedefd Zy)r9 z*An ABC with one abstract method __bytes__.r r c y r r r) s rw __bytes__zSupportsBytes.__bytes__
r ry N)r r r r r r bytesr r ry rw r9 r9
r ry r9 c * e Zd ZdZdZedefd Zy)r< z*An ABC with one abstract method __index__.r r c y r r r) s rw __index__zSupportsIndex.__index__
r ry N)r r r r r r r r r ry rw r< r<
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} t | S )r c 4 e Zd ZW ZdZdZedW fd Zy)r8 zMAn ABC with one abstract method __abs__ that is covariant in its return type.r r c y r r r) s rw __abs__zSupportsAbs.__abs__
r ry N)r r r rc r r r r .type_paramsr s rw r8 r8
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} t | S )r c : e Zd ZW ZdZdZeddedW fd Zy)r> zOAn ABC with one abstract method __round__ that is covariant in its return type.r ndigitsr c y r r )r r% s rw __round__zSupportsRound.__round__
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ry r c |D cg c] \ }}| }}}|D ci c] \ }}|t |d| d }}}t j | ||| }|x|_ |j _ |S c c}}w c c}}w )Nzfield z annotation must be a typedefaultsrq )r r
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| z | t vs"| | j" vs1t% | | || B t |v r| j' | S c c}w )Nz3can only inherit from a NamedTuple type and Genericc 3 < K | ] }|t u rt n| y wr ) _NamedTupler )r r s rw r z)NamedTupleMeta.__new__.. s Ot{ 2e< rg z Non-default namedtuple field z cannot follow default fieldre sr r r r+ z&Cannot overwrite NamedTuple attribute )r= r r r r r r r r1 r r r classmethodri _prohibitedr _specialr4 r r ) r typenamer# nsr r
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s ry r: c ||j }n
|r t d t | |t }t f|_ |S )a? 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)])
zIEither list of fields or keywords can be provided to NamedTuple, not bothrq )r r r1 r~ rH r )rD r/ rS nts rw rH rH ! sK ( ~ C D D x :B#
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|_ t3 | |_ t |d s||_ |S c c} } w )a7 Create a 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.
Subclasses and instances of TypedDict return actual dictionaries.
zHcannot inherit from both a TypedDict type and a non-TypedDict base classc 3 < K | ] }t |t y wr )r r r s rw r z)_TypedDictMeta.__new__..U s 5u!z!W%ur> r r rg z?TypedDict('Name', {f0: t0, f1: t1, ...}); each t must be a typerJ __required_keys____optional_keys__r TFz,Required keys overlap with optional keys in z: required_keys=z, optional_keys= __total__) rs r r r r rQ r r r r r r r r updater rX r rW re rb rp discard
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| d|| }t f|_ |S ) a* 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
>>> Point2D(x=1, y=2, label='first') == dict(x=1, y=2, label='first')
True
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.
z@TypedDict takes either a dict or keyword arguments, but not bothzThe kwargs-based syntax for TypedDict definitions is deprecated in Python 3.11, will be removed in Python 3.13, and may not be understood by third-party type checkers.r
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_TypedDictrM s rw ro s :-ry c N t || j d }t | |f S )a Special typing construct to mark a TypedDict key as required.
This is mainly useful for total=False TypedDicts.
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.
accepts only a single type.r r r} r] s rw re re s+ ( zdjj\1M#N OD w ''ry c N t || j d }t | |f S )a7 Special typing construct to mark a TypedDict key as potentially missing.
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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,
)
rq rr r] s rw rb rb s+ zdjj\1M#N OD w ''ry c 8 e Zd ZdZeZd Zd Zd Zd Z d Z
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Usage::
UserId = NewType('UserId', int)
def name_by_id(user_id: UserId) -> str:
...
UserId('user') # Fails type check
name_by_id(42) # Fails type check
name_by_id(UserId(42)) # OK
num = UserId(5) + 1 # type: int
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r r c y r r r) s rw modezIO.modej
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s 0'"GG Ery r z.rec d x}fd|d|fdcS )r r r c h t dt | j t j | S )a Ask a static type checker to reveal the inferred type of an expression.
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x: int = 1
reveal_type(x)
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order_defaultkw_only_defaultfrozen_defaultfield_specifiersr r r r r .rS c & fd}|S )as Decorator to mark an object as providing dataclass-like behaviour.
The decorator can be applied to a function, class, or metaclass.
Example usage with a decorator function::
@dataclass_transform()
def create_model[T](cls: type[T]) -> type[T]:
...
return cls
@create_model
class CustomerModel:
id: int
name: str
On a base class::
@dataclass_transform()
class ModelBase: ...
class CustomerModel(ModelBase):
id: int
name: str
On a metaclass::
@dataclass_transform()
class ModelMeta(type): ...
class ModelBase(metaclass=ModelMeta): ...
class CustomerModel(ModelBase):
id: int
name: str
The ``CustomerModel`` classes defined above will
be treated by type checkers similarly to classes created with
``@dataclasses.dataclass``.
For example, type checkers will assume these classes have
``__init__`` methods that accept ``id`` and ``name``.
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()``.
- Arbitrary other keyword arguments are accepted in order to allow for
possible future extensions.
At runtime, this decorator records its arguments in the
``__dataclass_transform__`` attribute on the decorated object.
It has no other runtime effect.
See PEP 681 for more details.
c $ d| _ | S )N)r r r r r rS )__dataclass_transform__) cls_or_fnr r r r rS r s rw r z&dataclass_transform..decoratorv
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s Xry methodr c B d| _ | S # t t f$ r Y | S w xY w)a Indicate that a method is intended to override a method in a base class.
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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 or attribute 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 this property. The decorator attempts to
set the ``__override__`` attribute to ``True`` on the decorated object to
allow runtime introspection.
See PEP 698 for details.
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