https://github.com/python/cpython/commit/d9ab95ff1fe81efdf70e545d536d9f6927d... commit: d9ab95ff1fe81efdf70e545d536d9f6927d1ba81 branch: master author: Andre Delfino <adelfino@gmail.com> committer: GitHub <noreply@github.com> date: 2020-09-27T12:07:04-07:00 summary: [doc] Leverage the fact that the actual types can now be indexed for typing (GH-22340) This shows users that they can use the actual types. Using deprecated types is confusing. This also prefers colections.abc.Sized instead of the alias typing.Sized. I guess the aliases were created to make it convenient to import all collections related types from the same place. This should be backported to 3.9. Automerge-Triggered-By: @gvanrossum files: M Doc/glossary.rst M Doc/library/typing.rst diff --git a/Doc/glossary.rst b/Doc/glossary.rst index 7be755e411310..9fdbdb1a83f28 100644 --- a/Doc/glossary.rst +++ b/Doc/glossary.rst @@ -1084,19 +1084,15 @@ Glossary Type aliases are useful for simplifying :term:`type hints <type hint>`. For example:: - from typing import List, Tuple - def remove_gray_shades( - colors: List[Tuple[int, int, int]]) -> List[Tuple[int, int, int]]: + colors: list[tuple[int, int, int]]) -> list[tuple[int, int, int]]: pass could be made more readable like this:: - from typing import List, Tuple - - Color = Tuple[int, int, int] + Color = tuple[int, int, int] - def remove_gray_shades(colors: List[Color]) -> List[Color]: + def remove_gray_shades(colors: list[Color]) -> list[Color]: pass See :mod:`typing` and :pep:`484`, which describe this functionality. diff --git a/Doc/library/typing.rst b/Doc/library/typing.rst index d31c65d38e1ab..3b824d0a4a8da 100644 --- a/Doc/library/typing.rst +++ b/Doc/library/typing.rst @@ -38,10 +38,9 @@ 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:: +``Vector`` and ``list[float]`` will be treated as interchangeable synonyms:: - from typing import List - Vector = List[float] + Vector = list[float] def scale(scalar: float, vector: Vector) -> Vector: return [scalar * num for num in vector] @@ -51,11 +50,11 @@ A type alias is defined by assigning the type to the alias. In this example, Type aliases are useful for simplifying complex type signatures. For example:: - from typing import Dict, Tuple, Sequence + from collections.abc import Sequence - ConnectionOptions = Dict[str, str] - Address = Tuple[str, int] - Server = Tuple[Address, ConnectionOptions] + ConnectionOptions = dict[str, str] + Address = tuple[str, int] + Server = tuple[Address, ConnectionOptions] def broadcast_message(message: str, servers: Sequence[Server]) -> None: ... @@ -64,7 +63,7 @@ Type aliases are useful for simplifying complex type signatures. For example:: # being exactly equivalent to this one. def broadcast_message( message: str, - servers: Sequence[Tuple[Tuple[str, int], Dict[str, str]]]) -> None: + servers: Sequence[tuple[tuple[str, int], dict[str, str]]]) -> None: ... Note that ``None`` as a type hint is a special case and is replaced by @@ -157,7 +156,7 @@ type hinted using ``Callable[[Arg1Type, Arg2Type], ReturnType]``. For example:: - from typing import Callable + from collections.abc import Callable def feeder(get_next_item: Callable[[], str]) -> None: # Body @@ -181,7 +180,7 @@ subscription to denote expected types for container elements. :: - from typing import Mapping, Sequence + from collections.abc import Mapping, Sequence def notify_by_email(employees: Sequence[Employee], overrides: Mapping[str, str]) -> None: ... @@ -191,7 +190,8 @@ called :class:`TypeVar`. :: - from typing import Sequence, TypeVar + from collections.abc import Sequence + from typing import TypeVar T = TypeVar('T') # Declare type variable @@ -235,7 +235,7 @@ class body. The :class:`Generic` base class defines :meth:`__class_getitem__` so that ``LoggedVar[t]`` is valid as a type:: - from typing import Iterable + from collections.abc import Iterable def zero_all_vars(vars: Iterable[LoggedVar[int]]) -> None: for var in vars: @@ -266,7 +266,8 @@ This is thus invalid:: You can use multiple inheritance with :class:`Generic`:: - from typing import TypeVar, Generic, Sized + from collections.abc import Sized + from typing import TypeVar, Generic T = TypeVar('T') @@ -275,7 +276,8 @@ You can use multiple inheritance with :class:`Generic`:: When inheriting from generic classes, some type variables could be fixed:: - from typing import TypeVar, Mapping + from collections.abc import Mapping + from typing import TypeVar T = TypeVar('T') @@ -288,13 +290,14 @@ Using a generic class without specifying type parameters assumes :data:`Any` for each position. In the following example, ``MyIterable`` is not generic but implicitly inherits from ``Iterable[Any]``:: - from typing import Iterable + from collections.abc import Iterable class MyIterable(Iterable): # Same as Iterable[Any] User defined generic type aliases are also supported. Examples:: - from typing import TypeVar, Iterable, Tuple, Union + from collections.abc import Iterable + from typing import TypeVar, Union S = TypeVar('S') Response = Union[Iterable[S], int] @@ -303,9 +306,9 @@ User defined generic type aliases are also supported. Examples:: ... T = TypeVar('T', int, float, complex) - Vec = Iterable[Tuple[T, T]] + Vec = Iterable[tuple[T, T]] - def inproduct(v: Vec[T]) -> T: # Same as Iterable[Tuple[T, T]] + def inproduct(v: Vec[T]) -> T: # Same as Iterable[tuple[T, T]] return sum(x*y for x, y in v) .. versionchanged:: 3.7 @@ -408,7 +411,7 @@ 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`:: - from typing import Sized, Iterable, Iterator + from collections.abc import Sized, Iterable, Iterator class Bucket(Sized, Iterable[int]): ... @@ -421,7 +424,7 @@ 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):: - from typing import Iterator, Iterable + from collections.abc import Iterator, Iterable class Bucket: # Note: no base classes ... @@ -1371,10 +1374,10 @@ Asynchronous programming The variance and order of type variables correspond to those of :class:`Generator`, for example:: - from typing import List, Coroutine - c = None # type: Coroutine[List[str], str, int] + from collections.abc import Coroutine + c = None # type: Coroutine[list[str], str, int] ... - x = c.send('hi') # type: List[str] + x = c.send('hi') # type: list[str] async def bar() -> None: x = await c # type: int