New in version 3.5.

26.1.1. Type aliases

A type alias is defined by assigning the type to the alias:

Vector = List[float]

26.1.2. Callable

Frameworks expecting callback functions of specific signatures might be type hinted using Callable[[Arg1Type, Arg2Type], ReturnType].

For example:

from typing import Callable

def feeder(get_next_item: Callable[[], str]) -> None:
    # Body

def async_query(on_success: Callable[[int], None],
                on_error: Callable[[int, Exception], None]) -> None:
    # Body

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]. None as a type hint is a special case and is replaced by type(None).

26.1.3. 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.

from typing import Mapping, Sequence

def notify_by_email(employees: Sequence[Employee],
                    overrides: Mapping[str, str]) -> None: ...

Generics can be parametrized by using a new factory available in typing called TypeVar.

from typing import Sequence, TypeVar

T = TypeVar('T')      # Declare type variable

def first(l: Sequence[T]) -> T:   # Generic function
    return l[0]

26.1.4. User-defined generic types

A user-defined class can be defined as a generic class.

from typing import TypeVar, Generic
from logging import Logger

T = TypeVar('T')

class LoggedVar(Generic[T]):
    def __init__(self, value: T, name: str, logger: Logger) -> None:
        self.name = name
        self.logger = logger
        self.value = value

    def set(self, new: T) -> None:
        self.log('Set ' + repr(self.value))
        self.value = new

    def get(self) -> T:
        self.log('Get ' + repr(self.value))
        return self.value

    def log(self, message: str) -> None:
        self.logger.info('{}: {}'.format(self.name, message))

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 uses a metaclass that defines __getitem__() so that LoggedVar[t] is valid as a type:

from typing import Iterable

def zero_all_vars(vars: Iterable[LoggedVar[int]]) -> None:
    for var in vars:
        var.set(0)

A generic type can have any number of type variables, and type variables may be constrained:

from typing import TypeVar, Generic
...

T = TypeVar('T')
S = TypeVar('S', int, str)

class StrangePair(Generic[T, S]):
    ...

Each type variable argument to Generic must be distinct. This is thus invalid:

from typing import TypeVar, Generic
...

T = TypeVar('T')

class Pair(Generic[T, T]):   # INVALID
    ...

You can use multiple inheritance with Generic:

from typing import TypeVar, Generic, Sized

T = TypeVar('T')

class LinkedList(Sized, Generic[T]):
    ...

When inheriting from generic classes, some type variables could be fixed:

from typing import TypeVar, Mapping

T = TypeVar('T')

class MyDict(Mapping[str, T]):
    ...

In this case MyDict has a single parameter, T.

Subclassing 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]:

from typing import Iterable

class MyIterable(Iterable): # Same as Iterable[Any]

The metaclass used by Generic is a subclass of abc.ABCMeta. A generic class can be an ABC by including abstract methods or properties, and generic classes can also have ABCs as base classes without a metaclass conflict. Generic metaclasses are not supported.

26.1.5. The Any type

A special kind of type is Any. Every type is a subtype of Any. This is also true for the builtin type object. However, to the static type checker these are completely different.

When the type of a value is object, the 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. On the other hand, when a value has type Any, the type checker will allow all operations on it, and a value of type Any can be assigned to a variable (or used as a return value) of a more constrained type.

26.1.6. Classes, functions, and decorators

The module defines the following classes, functions and decorators:

class typing.Any

Special type indicating an unconstrained type.

• Any object is an instance of Any.
• Any class is a subclass of Any.
• As a special case, Any and object are subclasses of each other.

class typing.TypeVar

Type variable.

Usage:

T = TypeVar('T')  # Can be anything
A = TypeVar('A', str, bytes)  # Must be str or bytes

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:

def repeat(x: T, n: int) -> Sequence[T]:
    """Return a list containing n references to x."""
    return [x]*n

def longest(x: A, y: A) -> A:
    """Return the longest of two strings."""
    return x if len(x) >= len(y) else y

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 of str, the return type is still plain str.

At runtime, isinstance(x, T) will raise TypeError. In general, isinstance() and issubclass() should not be used with types.

Type variables may be marked covariant or contravariant by passing covariant=True or contravariant=True. See PEP 484 for more details. By default type variables are invariant. Alternatively, a type variable may specify an upper bound using bound=<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.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.:

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

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

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

• Redundant arguments are skipped, e.g.:

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

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

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

• If Any is present it is the sole survivor, e.g.:

  Union[int, Any] == Any
  

• You cannot subclass or instantiate a union.

• You cannot write Union[X][Y].

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

class typing.Optional

Optional type.

Optional[X] is equivalent to Union[X, type(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 needn’t use the Optional qualifier on its type annotation (although it is inferred if the default is None). A mandatory argument may still have an Optional type if an explicit value of None is allowed.

class 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.

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, ...].

class 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; 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] could be used to type hint a callable taking any number of arguments and returning ReturnType. A plain Callable is equivalent to Callable[..., Any].

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:

class Mapping(Generic[KT, VT]):
    def __getitem__(self, key: KT) -> VT:
        ...
        # Etc.

This class can then be used as follows:

X = TypeVar('X')
Y = TypeVar('Y')

def lookup_name(mapping: Mapping[X, Y], key: X, default: Y) -> Y:
    try:
        return mapping[key]
    except KeyError:
        return default

class typing.Iterable(Generic[T_co])

A generic version of the collections.abc.Iterable.

class typing.Iterator(Iterable[T_co])

A generic version of the collections.abc.Iterator.

class typing.SupportsInt

An ABC with one abstract method __int__.

class typing.SupportsFloat

An ABC with one abstract method __float__.

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.Reversible

An ABC with one abstract method __reversed__ returning an Iterator[T_co].

class typing.Container(Generic[T_co])

A generic version of collections.abc.Container.

class typing.AbstractSet(Sized, Iterable[T_co], Container[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, Iterable[KT], Container[KT], Generic[VT_co])

A generic version of collections.abc.Mapping.

class typing.MutableMapping(Mapping[KT, VT])

A generic version of collections.abc.MutableMapping.

class typing.Sequence(Sized, Iterable[T_co], Container[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, and memoryview.

As a shorthand for this type, bytes can be used to annotate arguments of any of the types mentioned above.

class typing.List(list, MutableSequence[T])

Generic version of list. Useful for annotating return types. To annotate arguments it is preferred to use abstract collection types such as Mapping, Sequence, or AbstractSet.

This type may be used as follows:

T = TypeVar('T', int, float)

def vec2(x: T, y: T) -> List[T]:
    return [x, y]

def slice__to_4(vector: Sequence[T]) -> List[T]:
    return vector[0:4]

class typing.Set(set, MutableSet[T])

A generic version of builtins.set.

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.Dict(dict, MutableMapping[KT, VT])

A generic version of dict. The usage of this type is as follows:

def get_position_in_index(word_list: Dict[str, int], word: str) -> int:
    return word_list[word]

class typing.Generator(Iterator[T_co], Generic[T_co, T_contra, V_co])

class typing.io

Wrapper namespace for I/O stream types.

This defines the generic type IO[AnyStr] and aliases TextIO and BinaryIO for respectively IO[str] and IO[bytes]. These representing the types of I/O streams such as returned by open().

class typing.re

Wrapper namespace for regular expression matching types.

This defines the type aliases Pattern and Match which correspond to the return types from re.compile() and re.match(). These types (and the corresponding functions) are generic in AnyStr and can be made specific by writing Pattern[str], Pattern[bytes], Match[str], or Match[bytes].

typing.NamedTuple(typename, fields)

Typed version of namedtuple.

Usage:

Employee = typing.NamedTuple('Employee', [('name', str), ('id', int)])

This is equivalent to:

Employee = collections.namedtuple('Employee', ['name', 'id'])

The resulting class has one extra attribute: _field_types, giving a dict mapping field names to types. (The field names are in the _fields attribute, which is part of the namedtuple API.)

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)

Return type hints for a function or method object.

This is often the same as obj.__annotations__, but it handles forward references encoded as string literals, and if necessary adds Optional[t] if a default value equal to None is set.

@typing.no_type_check(arg)

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 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)

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().