mirror of https://github.com/python/cpython
Issue #24272: Initial docs for typing.py (PEP 484). (Merge from 3.5.)
By Daniel Andrade Groppe and Ivan Levkivskyi.
This commit is contained in:
Guido van Rossum
commit
69afdda3a5
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@ -13,3 +13,418 @@ fundamental support consists of the type :class:`Any`, :class:`Union`,
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:class:`Tuple`, :class:`Callable`, :class:`TypeVar`, and
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:class:`Generic`. For full specification please see :pep:`484`. For
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a simplified introduction to type hints see :pep:`483`.
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The function below takes and returns a string and is annotated as follows::
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def greeting(name: str) -> str:
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return 'Hello ' + name
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In the function `greeting`, the argument `name` is expected to by of type `str`
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and the return type `str`. Subtypes are accepted as arguments.
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Type aliases
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------------
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A type alias is defined by assigning the type to the alias::
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Vector = List[float]
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Callable
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--------
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Frameworks expecting callback functions of specific signatures might be
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type hinted using `Callable[[Arg1Type, Arg2Type], ReturnType]`.
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For example::
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from typing import Callable
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def feeder(get_next_item: Callable[[], str]) -> None:
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# Body
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def async_query(on_success: Callable[[int], None],
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on_error: Callable[[int, Exception], None]) -> None:
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# Body
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It is possible to declare the return type of a callable without specifying
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the call signature by substituting a literal ellipsis
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for the list of arguments in the type hint: `Callable[..., ReturnType]`.
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`None` as a type hint is a special case and is replaced by `type(None)`.
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Generics
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--------
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Since type information about objects kept in containers cannot be statically
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inferred in a generic way, abstract base classes have been extended to support
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subscription to denote expected types for container elements.
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.. code-block:: python
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from typing import Mapping, Sequence
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def notify_by_email(employees: Sequence[Employee],
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overrides: Mapping[str, str]) -> None: ...
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Generics can be parametrized by using a new factory available in typing
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called TypeVar.
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.. code-block:: python
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from typing import Sequence, TypeVar
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T = TypeVar('T') # Declare type variable
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def first(l: Sequence[T]) -> T: # Generic function
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return l[0]
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User-defined generic types
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--------------------------
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A user-defined class can be defined as a generic class.
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.. code-block:: python
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from typing import TypeVar, Generic
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from logging import Logger
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T = TypeVar('T')
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class LoggedVar(Generic[T]):
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def __init__(self, value: T, name: str, logger: Logger) -> None:
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self.name = name
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self.logger = logger
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self.value = value
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def set(self, new: T) -> None:
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self.log('Set ' + repr(self.value))
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self.value = new
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def get(self) -> T:
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self.log('Get ' + repr(self.value))
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return self.value
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def log(self, message: str) -> None:
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self.logger.info('{}: {}'.format(self.name, message))
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`Generic[T]` as a base class defines that the class `LoggedVar` takes a single
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type parameter `T` . This also makes `T` valid as a type within the class body.
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The `Generic` base class uses a metaclass that defines `__getitem__` so that
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`LoggedVar[t]` is valid as a type::
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from typing import Iterable
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def zero_all_vars(vars: Iterable[LoggedVar[int]]) -> None:
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for var in vars:
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var.set(0)
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A generic type can have any number of type variables, and type variables may
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be constrained::
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from typing import TypeVar, Generic
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...
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T = TypeVar('T')
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S = TypeVar('S', int, str)
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class StrangePair(Generic[T, S]):
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...
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Each type variable argument to `Generic` must be distinct.
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This is thus invalid::
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from typing import TypeVar, Generic
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...
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T = TypeVar('T')
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class Pair(Generic[T, T]): # INVALID
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...
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You can use multiple inheritance with `Generic`::
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from typing import TypeVar, Generic, Sized
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T = TypeVar('T')
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class LinkedList(Sized, Generic[T]):
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...
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Subclassing a generic class without specifying type parameters assumes `Any`
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for each position. In the following example, `MyIterable` is not generic but
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implicitly inherits from `Iterable[Any]`::
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from typing import Iterable
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class MyIterable(Iterable): # Same as Iterable[Any]
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Generic metaclasses are not supported.
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The `Any` type
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--------------
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A special kind of type is `Any`. Every type is a subtype of `Any`.
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This is also true for the builtin type object. However, to the static type
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checker these are completely different.
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When the type of a value is `object`, the type checker will reject almost all
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operations on it, and assigning it to a variable (or using it as a return value)
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of a more specialized type is a type error. On the other hand, when a value has
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type `Any`, the type checker will allow all operations on it, and a value of
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type `Any` can be assigned to a variable (or used as a return value) of a more
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constrained type.
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Default argument values
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-----------------------
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Use a literal ellipsis `...` to declare an argument as having a default value::
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from typing import AnyStr
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def foo(x: AnyStr, y: AnyStr = ...) -> AnyStr: ...
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Classes, functions, and decorators
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----------------------------------
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The module defines the following classes, functions and decorators:
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.. class:: Any
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Special type indicating an unconstrained type.
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* Any object is an instance of `Any`.
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* Any class is a subclass of `Any`.
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* As a special case, `Any` and `object` are subclasses of each other.
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.. class:: TypeVar
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Type variable.
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Usage::
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T = TypeVar('T') # Can be anything
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A = TypeVar('A', str, bytes) # Must be str or bytes
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Type variables exist primarily for the benefit of static type
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checkers. They serve as the parameters for generic types as well
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as for generic function definitions. See class Generic for more
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information on generic types. Generic functions work as follows:
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.. code-block:: python
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def repeat(x: T, n: int) -> Sequence[T]:
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"""Return a list containing n references to x."""
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return [x]*n
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def longest(x: A, y: A) -> A:
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"""Return the longest of two strings."""
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return x if len(x) >= len(y) else y
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The latter example's signature is essentially the overloading
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of `(str, str) -> str` and `(bytes, bytes) -> bytes`. Also note
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that if the arguments are instances of some subclass of `str`,
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the return type is still plain `str`.
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At runtime, `isinstance(x, T)` will raise `TypeError`. In general,
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`isinstance` and `issublass` should not be used with types.
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Type variables may be marked covariant or contravariant by passing
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`covariant=True` or `contravariant=True`. See :pep:`484` for more
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details. By default type variables are invariant.
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.. class:: Union
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Union type; `Union[X, Y]` means either X or Y.
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To define a union, use e.g. `Union[int, str]`. Details:
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* The arguments must be types and there must be at least one.
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* Unions of unions are flattened, e.g.::
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Union[Union[int, str], float] == Union[int, str, float]
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* Unions of a single argument vanish, e.g.::
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Union[int] == int # The constructor actually returns int
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* Redundant arguments are skipped, e.g.::
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Union[int, str, int] == Union[int, str]
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* When comparing unions, the argument order is ignored, e.g.::
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Union[int, str] == Union[str, int]
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* If `Any` is present it is the sole survivor, e.g.::
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Union[int, Any] == Any
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* You cannot subclass or instantiate a union.
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* You cannot write `Union[X][Y]`
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* You can use `Optional[X]` as a shorthand for `Union[X, None]`.
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.. class:: Optional
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Optional type.
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`Optional[X]` is equivalent to `Union[X, type(None)]`.
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.. class:: Tuple
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Tuple type; `Tuple[X, Y]` is the is the type of a tuple of two items
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with the first item of type X and the second of type Y.
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Example: `Tuple[T1, T2]` is a tuple of two elements corresponding
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to type variables T1 and T2. `Tuple[int, float, str]` is a tuple
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of an int, a float and a string.
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To specify a variable-length tuple of homogeneous type,
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use literal ellipsis, e.g. `Tuple[int, ...]`.
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.. class:: Callable
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Callable type; `Callable[[int], str]` is a function of (int) -> str.
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The subscription syntax must always be used with exactly two
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values: the argument list and the return type. The argument list
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must be a list of types; the return type must be a single type.
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There is no syntax to indicate optional or keyword arguments,
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such function types are rarely used as callback types.
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`Callable[..., ReturnType]` could be used to type hint a callable
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taking any number of arguments and returning `ReturnType`.
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A plain `Callable` is equivalent to `Callable[..., Any]`.
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.. class:: Generic
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Abstract base class for generic types.
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A generic type is typically declared by inheriting from an
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instantiation of this class with one or more type variables.
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For example, a generic mapping type might be defined as::
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class Mapping(Generic[KT, VT]):
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def __getitem__(self, key: KT) -> VT:
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...
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# Etc.
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This class can then be used as follows::
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X = TypeVar('X')
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Y = TypeVar('Y')
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def lookup_name(mapping: Mapping[X, Y], key: X, default: Y) -> Y:
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try:
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return mapping[key]
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except KeyError:
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return default
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.. class:: Iterable(Generic[T_co])
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.. class:: Iterator(Iterable[T_co])
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.. class:: SupportsInt
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.. class:: SupportsFloat
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.. class:: SupportsAbs
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.. class:: SupportsRound
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.. class:: Reversible
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.. class:: Container(Generic[T_co])
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.. class:: AbstractSet(Sized, Iterable[T_co], Container[T_co])
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.. class:: MutableSet(AbstractSet[T])
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.. class:: Mapping(Sized, Iterable[KT_co], Container[KT_co], Generic[KT_co, VT_co])
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.. class:: MutableMapping(Mapping[KT, VT])
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.. class:: Sequence(Sized, Iterable[T_co], Container[T_co])
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.. class:: MutableSequence(Sequence[T])
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.. class:: ByteString(Sequence[int])
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.. class:: List(list, MutableSequence[T])
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.. class:: Set(set, MutableSet[T])
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.. class:: MappingView(Sized, Iterable[T_co])
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.. class:: KeysView(MappingView[KT_co], AbstractSet[KT_co])
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.. class:: ItemsView(MappingView, Generic[KT_co, VT_co])
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.. class:: ValuesView(MappingView[VT_co])
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.. class:: Dict(dict, MutableMapping[KT, VT])
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.. class:: Generator(Iterator[T_co], Generic[T_co, T_contra, V_co])
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.. class:: io
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Wrapper namespace for IO generic classes.
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.. class:: re
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Wrapper namespace for re type classes.
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.. function:: NamedTuple(typename, fields)
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Typed version of namedtuple.
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Usage::
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Employee = typing.NamedTuple('Employee', [('name', str), 'id', int)])
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This is equivalent to::
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Employee = collections.namedtuple('Employee', ['name', 'id'])
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The resulting class has one extra attribute: _field_types,
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giving a dict mapping field names to types. (The field names
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are in the _fields attribute, which is part of the namedtuple
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API.)
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.. function:: cast(typ, val)
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Cast a value to a type.
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This returns the value unchanged. To the type checker this
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signals that the return value has the designated type, but at
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runtime we intentionally don't check anything (we want this
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to be as fast as possible).
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.. function:: get_type_hints(obj)
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Return type hints for a function or method object.
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This is often the same as obj.__annotations__, but it handles
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forward references encoded as string literals, and if necessary
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adds Optional[t] if a default value equal to None is set.
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.. decorator:: no_type_check(arg)
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Decorator to indicate that annotations are not type hints.
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The argument must be a class or function; if it is a class, it
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applies recursively to all methods defined in that class (but not
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to methods defined in its superclasses or subclasses).
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This mutates the function(s) in place.
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.. decorator:: no_type_check_decorator(decorator)
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Decorator to give another decorator the @no_type_check effect.
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This wraps the decorator with something that wraps the decorated
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function in @no_type_check.
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