https://docs.python.org/3/library/typing.html
typing
— Support for type hints
New in version 3.5.
Source code: Lib/typing.py
Note
The Python runtime does not enforce function and variable type annotations. They can be used by third party tools such as type checkers, IDEs, linters, etc.
This module provides runtime support for type hints as specified by PEP 484, PEP 526, PEP 544, PEP 586, PEP 589, and PEP 591. The most fundamental support consists of the types Any
, Union
, Tuple
, Callable
, TypeVar
, and Generic
. For full specification please see PEP 484. For a simplified introduction to type hints see PEP 483.
The function below takes and returns a string and is annotated as follows:
In the function greeting
, the argument name
is expected to be of type str
and the return type str
. Subtypes are accepted as arguments.
Type aliases
A type alias is defined by assigning the type to the alias. In this example, Vector
and List[float]
will be treated as interchangeable synonyms:
Type aliases are useful for simplifying complex type signatures. For example:
Note that None
as a type hint is a special case and is replaced by type(None)
.
NewType
Use the NewType()
helper function to create distinct types:
The static type checker will treat the new type as if it were a subclass of the original type. This is useful in helping catch logical errors:
You may still perform all int
operations on a variable of type UserId
, but the result will always be of type int
. This lets you pass in a UserId
wherever an int
might be expected, but will prevent you from accidentally creating a UserId
in an invalid way:
Note that these checks are enforced only by the static type checker. At runtime, the statement Derived = NewType('Derived', Base)
will make Derived
a function that immediately returns whatever parameter you pass it. That means the expression Derived(some_value)
does not create a new class or introduce any overhead beyond that of a regular function call.
More precisely, the expression some_value is Derived(some_value)
is always true at runtime.
This also means that it is not possible to create a subtype of Derived
since it is an identity function at runtime, not an actual type:
However, it is possible to create a NewType()
based on a ‘derived’ NewType
:
and typechecking for ProUserId
will work as expected.
See PEP 484 for more details.
Note
Recall that the use of a type alias declares two types to be equivalent to one another. Doing Alias = Original
will make the static type checker treat Alias
as being exactly equivalent to Original
in all cases. This is useful when you want to simplify complex type signatures.
In contrast, NewType
declares one type to be a subtype of another. Doing Derived = NewType('Derived', Original)
will make the static type checker treat Derived
as a subclass of Original
, which means a value of type Original
cannot be used in places where a value of type Derived
is expected. This is useful when you want to prevent logic errors with minimal runtime cost.
New in version 3.5.2.
Callable
Frameworks expecting callback functions of specific signatures might be type hinted using Callable[[Arg1Type, Arg2Type], ReturnType]
.
For example:
It is possible to declare the return type of a callable without specifying the call signature by substituting a literal ellipsis for the list of arguments in the type hint: Callable[..., ReturnType]
.
Generics
Since type information about objects kept in containers cannot be statically inferred in a generic way, abstract base classes have been extended to support subscription to denote expected types for container elements.
Generics can be parameterized by using a new factory available in typing called TypeVar
.
User-defined generic types
A user-defined class can be defined as a generic class.
Generic[T]
as a base class defines that the class LoggedVar
takes a single type parameter T
. This also makes T
valid as a type within the class body.
The Generic
base class defines __class_getitem__()
so that LoggedVar[t]
is valid as a type:
A generic type can have any number of type variables, and type variables may be constrained:
Each type variable argument to Generic
must be distinct. This is thus invalid:
You can use multiple inheritance with Generic
:
When inheriting from generic classes, some type variables could be fixed:
In this case MyDict
has a single parameter, T
.
Using a generic class without specifying type parameters assumes Any
for each position. In the following example, MyIterable
is not generic but implicitly inherits from Iterable[Any]
:
User defined generic type aliases are also supported. Examples:
Changed in version 3.7: Generic
no longer has a custom metaclass.
A user-defined generic class can have ABCs as base classes without a metaclass conflict. Generic metaclasses are not supported. The outcome of parameterizing generics is cached, and most types in the typing module are hashable and comparable for equality.
The Any
type
A special kind of type is Any
. A static type checker will treat every type as being compatible with Any
and Any
as being compatible with every type.
This means that it is possible to perform any operation or method call on a value of type on Any
and assign it to any variable:
Notice that no typechecking is performed when assigning a value of type Any
to a more precise type. For example, the static type checker did not report an error when assigning a
to s
even though s
was declared to be of type str
and receives an int
value at runtime!
Furthermore, all functions without a return type or parameter types will implicitly default to using Any
:
This behavior allows Any
to be used as an escape hatch when you need to mix dynamically and statically typed code.
Contrast the behavior of Any
with the behavior of object
. Similar to Any
, every type is a subtype of object
. However, unlike Any
, the reverse is not true: object
is not a subtype of every other type.
That means when the type of a value is object
, a type checker will reject almost all operations on it, and assigning it to a variable (or using it as a return value) of a more specialized type is a type error. For example:
Use object
to indicate that a value could be any type in a typesafe manner. Use Any
to indicate that a value is dynamically typed.
Nominal vs structural subtyping
Initially PEP 484 defined Python static type system as using nominal subtyping. This means that a class A
is allowed where a class B
is expected if and only if A
is a subclass of B
.
This requirement previously also applied to abstract base classes, such as Iterable
. The problem with this approach is that a class had to be explicitly marked to support them, which is unpythonic and unlike what one would normally do in idiomatic dynamically typed Python code. For example, this conforms to the PEP 484:
PEP 544 allows to solve this problem by allowing users to write the above code without explicit base classes in the class definition, allowing Bucket
to be implicitly considered a subtype of both Sized
and Iterable[int]
by static type checkers. This is known as structural subtyping (or static duck-typing):
Moreover, by subclassing a special class Protocol
, a user can define new custom protocols to fully enjoy structural subtyping (see examples below).
Classes, functions, and decorators
The module defines the following classes, functions and decorators:
- class
typing.
TypeVar
Type variable.
Usage:
Type variables exist primarily for the benefit of static type checkers. They serve as the parameters for generic types as well as for generic function definitions. See class Generic for more information on generic types. Generic functions work as follows:
The latter example’s signature is essentially the overloading of
(str, str) -> str
and(bytes, bytes) -> bytes
. Also note that if the arguments are instances of some subclass ofstr
, the return type is still plainstr
.At runtime,
isinstance(x, T)
will raiseTypeError
. In general,isinstance()
andissubclass()
should not be used with types.Type variables may be marked covariant or contravariant by passing
covariant=True
orcontravariant=True
. See PEP 484 for more details. By default type variables are invariant. Alternatively, a type variable may specify an upper bound usingbound=<type>
. This means that an actual type substituted (explicitly or implicitly) for the type variable must be a subclass of the boundary type, see PEP 484.
- class
typing.
Generic
Abstract base class for generic types.
A generic type is typically declared by inheriting from an instantiation of this class with one or more type variables. For example, a generic mapping type might be defined as:
This class can then be used as follows:
- class
typing.
Protocol
(Generic) Base class for protocol classes. Protocol classes are defined like this:
Such classes are primarily used with static type checkers that recognize structural subtyping (static duck-typing), for example:
See PEP 544 for details. Protocol classes decorated with
runtime_checkable()
(described later) act as simple-minded runtime protocols that check only the presence of given attributes, ignoring their type signatures.Protocol classes can be generic, for example:
New in version 3.8.
- class
typing.
Type
(Generic[CT_co]) A variable annotated with
C
may accept a value of typeC
. In contrast, a variable annotated withType[C]
may accept values that are classes themselves – specifically, it will accept the class object ofC
. For example:Note that
Type[C]
is covariant:The fact that
Type[C]
is covariant implies that all subclasses ofC
should implement the same constructor signature and class method signatures asC
. The type checker should flag violations of this, but should also allow constructor calls in subclasses that match the constructor calls in the indicated base class. How the type checker is required to handle this particular case may change in future revisions of PEP 484.The only legal parameters for
Type
are classes,Any
, type variables, and unions of any of these types. For example:Type[Any]
is equivalent toType
which in turn is equivalent totype
, which is the root of Python’s metaclass hierarchy.New in version 3.5.2.
- class
typing.
Iterable
(Generic[T_co]) A generic version of
collections.abc.Iterable
.
- class
typing.
Iterator
(Iterable[T_co]) A generic version of
collections.abc.Iterator
.
- class
typing.
Reversible
(Iterable[T_co]) A generic version of
collections.abc.Reversible
.
- class
typing.
SupportsInt
An ABC with one abstract method
__int__
.
- class
typing.
SupportsFloat
An ABC with one abstract method
__float__
.
- class
typing.
SupportsComplex
An ABC with one abstract method
__complex__
.
- class
typing.
SupportsBytes
An ABC with one abstract method
__bytes__
.
- class
typing.
SupportsIndex
An ABC with one abstract method
__index__
.New in version 3.8.
- class
typing.
SupportsAbs
An ABC with one abstract method
__abs__
that is covariant in its return type.
- class
typing.
SupportsRound
An ABC with one abstract method
__round__
that is covariant in its return type.
- class
typing.
Container
(Generic[T_co]) A generic version of
collections.abc.Container
.
- class
typing.
Hashable
An alias to
collections.abc.Hashable
- class
typing.
Sized
An alias to
collections.abc.Sized
- class
typing.
Collection
(Sized, Iterable[T_co], Container[T_co]) A generic version of
collections.abc.Collection
New in version 3.6.0.
- class
typing.
AbstractSet
(Sized, Collection[T_co]) A generic version of
collections.abc.Set
.
- class
typing.
MutableSet
(AbstractSet[T]) A generic version of
collections.abc.MutableSet
.
- class
typing.
Mapping
(Sized, Collection[KT], Generic[VT_co]) A generic version of
collections.abc.Mapping
. This type can be used as follows:
- class
typing.
MutableMapping
(Mapping[KT, VT]) A generic version of
collections.abc.MutableMapping
.
- class
typing.
Sequence
(Reversible[T_co], Collection[T_co]) A generic version of
collections.abc.Sequence
.
- class
typing.
MutableSequence
(Sequence[T]) A generic version of
collections.abc.MutableSequence
.
- class
typing.
ByteString
(Sequence[int]) A generic version of
collections.abc.ByteString
.This type represents the types
bytes
,bytearray
, andmemoryview
.As a shorthand for this type,
bytes
can be used to annotate arguments of any of the types mentioned above.
- class
typing.
Deque
(deque, MutableSequence[T]) A generic version of
collections.deque
.New in version 3.5.4.
New in version 3.6.1.
- class
typing.
List
(list, MutableSequence[T]) Generic version of
list
. Useful for annotating return types. To annotate arguments it is preferred to use an abstract collection type such asSequence
orIterable
.This type may be used as follows:
- class
typing.
Set
(set, MutableSet[T]) A generic version of
builtins.set
. Useful for annotating return types. To annotate arguments it is preferred to use an abstract collection type such asAbstractSet
.
- class
typing.
FrozenSet
(frozenset, AbstractSet[T_co]) A generic version of
builtins.frozenset
.
- class
typing.
MappingView
(Sized, Iterable[T_co]) A generic version of
collections.abc.MappingView
.
- class
typing.
KeysView
(MappingView[KT_co], AbstractSet[KT_co]) A generic version of
collections.abc.KeysView
.
- class
typing.
ItemsView
(MappingView, Generic[KT_co, VT_co]) A generic version of
collections.abc.ItemsView
.
- class
typing.
ValuesView
(MappingView[VT_co]) A generic version of
collections.abc.ValuesView
.
- class
typing.
Awaitable
(Generic[T_co]) A generic version of
collections.abc.Awaitable
.New in version 3.5.2.
- class
typing.
Coroutine
(Awaitable[V_co], Generic[T_co T_contra, V_co]) A generic version of
collections.abc.Coroutine
. The variance and order of type variables correspond to those ofGenerator
, for example:New in version 3.5.3.
- class
typing.
AsyncIterable
(Generic[T_co]) A generic version of
collections.abc.AsyncIterable
.New in version 3.5.2.
- class
typing.
AsyncIterator
(AsyncIterable[T_co]) A generic version of
collections.abc.AsyncIterator
.New in version 3.5.2.
- class
typing.
ContextManager
(Generic[T_co]) A generic version of
contextlib.AbstractContextManager
.New in version 3.5.4.
New in version 3.6.0.
- class
typing.
AsyncContextManager
(Generic[T_co]) A generic version of
contextlib.AbstractAsyncContextManager
.New in version 3.5.4.
New in version 3.6.2.
- class
typing.
Dict
(dict, MutableMapping[KT, VT]) A generic version of
dict
. Useful for annotating return types. To annotate arguments it is preferred to use an abstract collection type such asMapping
.This type can be used as follows:
- class
typing.
DefaultDict
(collections.defaultdict, MutableMapping[KT, VT]) A generic version of
collections.defaultdict
.New in version 3.5.2.
- class
typing.
OrderedDict
(collections.OrderedDict, MutableMapping[KT, VT]) A generic version of
collections.OrderedDict
.New in version 3.7.2.
- class
typing.
Counter
(collections.Counter, Dict[T, int]) A generic version of
collections.Counter
.New in version 3.5.4.
New in version 3.6.1.
- class
typing.
ChainMap
(collections.ChainMap, MutableMapping[KT, VT]) A generic version of
collections.ChainMap
.New in version 3.5.4.
New in version 3.6.1.
- class
typing.
Generator
(Iterator[T_co], Generic[T_co, T_contra, V_co]) A generator can be annotated by the generic type
Generator[YieldType, SendType, ReturnType]
. For example:Note that unlike many other generics in the typing module, the
SendType
ofGenerator
behaves contravariantly, not covariantly or invariantly.If your generator will only yield values, set the
SendType
andReturnType
toNone
:Alternatively, annotate your generator as having a return type of either
Iterable[YieldType]
orIterator[YieldType]
:
- class
typing.
AsyncGenerator
(AsyncIterator[T_co], Generic[T_co, T_contra]) An async generator can be annotated by the generic type
AsyncGenerator[YieldType, SendType]
. For example:Unlike normal generators, async generators cannot return a value, so there is no
ReturnType
type parameter. As withGenerator
, theSendType
behaves contravariantly.If your generator will only yield values, set the
SendType
toNone
:Alternatively, annotate your generator as having a return type of either
AsyncIterable[YieldType]
orAsyncIterator[YieldType]
:New in version 3.6.1.
- class
typing.
Text
Text
is an alias forstr
. It is provided to supply a forward compatible path for Python 2 code: in Python 2,Text
is an alias forunicode
.Use
Text
to indicate that a value must contain a unicode string in a manner that is compatible with both Python 2 and Python 3:New in version 3.5.2.
- class
typing.
IO
- class
typing.
TextIO
- class
typing.
BinaryIO
Generic type
IO[AnyStr]
and its subclassesTextIO(IO[str])
andBinaryIO(IO[bytes])
represent the types of I/O streams such as returned byopen()
.
- class
typing.
Pattern
- class
typing.
Match
These type aliases correspond to the return types from
re.compile()
andre.match()
. These types (and the corresponding functions) are generic inAnyStr
and can be made specific by writingPattern[str]
,Pattern[bytes]
,Match[str]
, orMatch[bytes]
.
- class
typing.
NamedTuple
Typed version of
collections.namedtuple()
.Usage:
This is equivalent to:
To give a field a default value, you can assign to it in the class body:
Fields with a default value must come after any fields without a default.
The resulting class has an extra attribute
__annotations__
giving a dict that maps the field names to the field types. (The field names are in the_fields
attribute and the default values are in the_field_defaults
attribute both of which are part of the namedtuple API.)NamedTuple
subclasses can also have docstrings and methods:Backward-compatible usage:
Changed in version 3.6: Added support for PEP 526 variable annotation syntax.
Changed in version 3.6.1: Added support for default values, methods, and docstrings.
Changed in version 3.8: Deprecated the
_field_types
attribute in favor of the more standard__annotations__
attribute which has the same information.Changed in version 3.8: The
_field_types
and__annotations__
attributes are now regular dictionaries instead of instances ofOrderedDict
.
- class
typing.
TypedDict
(dict) A simple typed namespace. At runtime it is equivalent to a plain
dict
.TypedDict
creates a dictionary type that expects all of its instances to have a certain set of keys, where each key is associated with a value of a consistent type. This expectation is not checked at runtime but is only enforced by type checkers. Usage:The type info for introspection can be accessed via
Point2D.__annotations__
andPoint2D.__total__
. To allow using this feature with older versions of Python that do not support PEP 526,TypedDict
supports two additional equivalent syntactic forms:See PEP 589 for more examples and detailed rules of using
TypedDict
with type checkers.New in version 3.8.
- class
typing.
ForwardRef
A class used for internal typing representation of string forward references. For example,
List["SomeClass"]
is implicitly transformed intoList[ForwardRef("SomeClass")]
. This class should not be instantiated by a user, but may be used by introspection tools.
typing.
NewType
(typ)A helper function to indicate a distinct types to a typechecker, see NewType. At runtime it returns a function that returns its argument. Usage:
New in version 3.5.2.
typing.
cast
(typ, val)Cast a value to a type.
This returns the value unchanged. To the type checker this signals that the return value has the designated type, but at runtime we intentionally don’t check anything (we want this to be as fast as possible).
typing.
get_type_hints
(obj[, globals[, locals]])Return a dictionary containing type hints for a function, method, module or class object.
This is often the same as
obj.__annotations__
. In addition, forward references encoded as string literals are handled by evaluating them inglobals
andlocals
namespaces. If necessary,Optional[t]
is added for function and method annotations if a default value equal toNone
is set. For a classC
, return a dictionary constructed by merging all the__annotations__
alongC.__mro__
in reverse order.
typing.
get_origin
(tp)
typing.
get_args
(tp)Provide basic introspection for generic types and special typing forms.
For a typing object of the form
X[Y, Z, ...]
these functions returnX
and(Y, Z, ...)
. IfX
is a generic alias for a builtin orcollections
class, it gets normalized to the original class. For unsupported objects returnNone
and()
correspondingly. Examples:New in version 3.8.
@
typing.
overload
The
@overload
decorator allows describing functions and methods that support multiple different combinations of argument types. A series of@overload
-decorated definitions must be followed by exactly one non-@overload
-decorated definition (for the same function/method). The@overload
-decorated definitions are for the benefit of the type checker only, since they will be overwritten by the non-@overload
-decorated definition, while the latter is used at runtime but should be ignored by a type checker. At runtime, calling a@overload
-decorated function directly will raiseNotImplementedError
. An example of overload that gives a more precise type than can be expressed using a union or a type variable:See PEP 484 for details and comparison with other typing semantics.
@
typing.
final
A decorator to indicate to type checkers that the decorated method cannot be overridden, and the decorated class cannot be subclassed. For example:
There is no runtime checking of these properties. See PEP 591 for more details.
New in version 3.8.
@
typing.
no_type_check
Decorator to indicate that annotations are not type hints.
This works as class or function decorator. With a class, it applies recursively to all methods defined in that class (but not to methods defined in its superclasses or subclasses).
This mutates the function(s) in place.
@
typing.
no_type_check_decorator
Decorator to give another decorator the
no_type_check()
effect.This wraps the decorator with something that wraps the decorated function in
no_type_check()
.
@
typing.
type_check_only
Decorator to mark a class or function to be unavailable at runtime.
This decorator is itself not available at runtime. It is mainly intended to mark classes that are defined in type stub files if an implementation returns an instance of a private class:
Note that returning instances of private classes is not recommended. It is usually preferable to make such classes public.
@
typing.
runtime_checkable
Mark a protocol class as a runtime protocol.
Such a protocol can be used with
isinstance()
andissubclass()
. This raisesTypeError
when applied to a non-protocol class. This allows a simple-minded structural check, very similar to “one trick ponies” incollections.abc
such asIterable
. For example:Warning: this will check only the presence of the required methods, not their type signatures!
New in version 3.8.
typing.
Any
Special type indicating an unconstrained type.
typing.
NoReturn
Special type indicating that a function never returns. For example:
New in version 3.5.4.
New in version 3.6.2.
typing.
Union
Union type;
Union[X, Y]
means either X or Y.To define a union, use e.g.
Union[int, str]
. Details:The arguments must be types and there must be at least one.
Unions of unions are flattened, e.g.:
Unions of a single argument vanish, e.g.:
Redundant arguments are skipped, e.g.:
When comparing unions, the argument order is ignored, e.g.:
You cannot subclass or instantiate a union.
You cannot write
Union[X][Y]
.You can use
Optional[X]
as a shorthand forUnion[X, None]
.
Changed in version 3.7: Don’t remove explicit subclasses from unions at runtime.
typing.
Optional
Optional type.
Optional[X]
is equivalent toUnion[X, None]
.Note that this is not the same concept as an optional argument, which is one that has a default. An optional argument with a default does not require the
Optional
qualifier on its type annotation just because it is optional. For example:On the other hand, if an explicit value of
None
is allowed, the use ofOptional
is appropriate, whether the argument is optional or not. For example:
typing.
Tuple
Tuple type;
Tuple[X, Y]
is the type of a tuple of two items with the first item of type X and the second of type Y. The type of the empty tuple can be written asTuple[()]
.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 literal ellipsis, e.g.
Tuple[int, ...]
. A plainTuple
is equivalent toTuple[Any, ...]
, and in turn totuple
.
typing.
Callable
Callable type;
Callable[[int], str]
is a function of (int) -> str.The subscription syntax must always be used with exactly two values: the argument list and the return type. The argument list must be a list of types or an 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.
Callable[..., ReturnType]
(literal ellipsis) can be used to type hint a callable taking any number of arguments and returningReturnType
. A plainCallable
is equivalent toCallable[..., Any]
, and in turn tocollections.abc.Callable
.
typing.
Literal
A type that 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). For example:
Literal[...]
cannot be subclassed. At runtime, an arbitrary value is allowed as type argument toLiteral[...]
, but type checkers may impose restrictions. See PEP 586 for more details about literal types.New in version 3.8.
typing.
ClassVar
Special type construct to mark class variables.
As introduced in PEP 526, a variable 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:
ClassVar
accepts only types and cannot be further subscribed.ClassVar
is not a class itself, and should not be used withisinstance()
orissubclass()
.ClassVar
does not change Python runtime behavior, but it can be used by third-party type checkers. For example, a type checker might flag the following code as an error:New in version 3.5.3.
typing.
Final
A special typing construct to indicate to type checkers that a name cannot be re-assigned or overridden in a subclass. For example:
There is no runtime checking of these properties. See PEP 591 for more details.
New in version 3.8.
typing.
AnyStr
AnyStr
is a type variable defined asAnyStr = TypeVar('AnyStr', str, bytes)
.It is meant to be used for functions that may accept any kind of string without allowing different kinds of strings to mix. For example:
typing.
TYPE_CHECKING
A special constant that is assumed to be
True
by 3rd party static type checkers. It isFalse
at runtime. Usage:Note that the first type annotation must be enclosed in quotes, making it a “forward reference”, to hide the
expensive_mod
reference from the interpreter runtime. Type annotations for local variables are not evaluated, so the second annotation does not need to be enclosed in quotes.New in version 3.5.2.
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