一、简介

typing 是 Python 标准库中的一个模块，用于支持类型提示（Type Hints）。类型提示是一种在代码中指定变量、函数参数和返回值的类型的方法，它可以提供代码的可读性、可维护性和工具支持。

二、常用类型及示例

Any：表示任意类型。

typing import Any
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test:Any = 2

def process_data(data: Any) -> None:
    # 对任意类型的数据进行处理
    pass

List：表示列表类型。

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from typing import List

test: List[int] = [2]

def process_list(items: List[int]) -> None:
    # 处理整数列表
    pass

Tuple：表示元组类型。

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from typing import Tuple

test:Tuple[int] = (2,)

def process_tuple(data: Tuple[str, int]) -> None:
    # 处理包含字符串和整数的元组
    pass

Dict：表示字典类型。

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from typing import Dict

test:Dict[str,int] = {"key":1}

def process_dict(data: Dict[str, int]) -> None:
    # 处理键为字符串，值为整数的字典
    pass

Set：表示集合类型。

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from typing import Set

test: Set[int] = {2,3}

def process_set(data: Set[str]) -> None:
    # 处理字符串集合
    pass

Union：表示多个可能的类型。

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from typing import Union

test:Union[int,str] = 2

def process_data(data: Union[int, float]) -> None:
    # 处理整数或浮点数
    pass

Optional：表示可选类型，即可以是指定类型或者 None。

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from typing import Optional

test:Optional[int] = None

def process_data(data: Optional[str]) -> None:
    # 处理可选的字符串，可以为 None
    pass

Callable：表示可调用对象的类型。

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from typing import Callable

  
def test(nu1: int, nu2: int) -> int:
    print('test')
    return nu1+nu2

def process_function(func: Callable[[int, int], int]) -> None:
    # 处理接受两个整数参数并返回整数的函数
    print(func(2,2))

process_function(test)

Iterator：表示迭代器类型。

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from typing import Iterator

test:Iterator[int] = iter([2])

def process_iterator(data: Iterator[int]) -> None:
    # 处理整数迭代器
    pass

Generator：表示生成器类型。

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from typing import Generator

def generate_numbers() -> Generator[int, None, None]:
   yield 1
   yield 2

test: Generator[int, None, None] = generate_numbers()

Iterable：表示可迭代对象的类型。

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from typing import Iterable

test:Iterable[str] = ["apple", "banana", "cherry"]

tes1:Iterable[str] = ("apple", "banana", "cherry")

def process_iterable(data: Iterable[str]) -> None:
    # 处理可迭代的字符串对象
    pass

Mapping：表示映射类型。

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from typing import Mapping

test:Mapping[str,int] = {"apple": 1, "banana": 2, "cherry": 3}

def process_mapping(data: Mapping[str, int]) -> None:
    # 处理键为字符串，值为整数的映射对象
    pass

Sequence：表示序列类型。

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from typing import Sequence

test: Sequence[int] = [1, 2, 3, 4, 5]

def process_sequence(data: Sequence[int]) -> None:
    # 处理整数序列
    pass

AnyStr：表示任意字符串类型。

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from typing import AnyStr

str:AnyStr = '213'

NoReturn：表示函数没有返回值。

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from typing import NoReturn

def my_func() -> NoReturn:
    print("This function does not return anything")

my_func()

FrozenSet: 表示不可变的集合类型。类似于 Set，但不能进行修改。

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from typing import FrozenSet

def process_data(data: FrozenSet[str]) -> None:
    for item in data:
        print(item)

test: FrozenSet[str] = frozenset(["apple", "banana", "orange"])

process_data(test)

Literal: 表示字面值类型。用于指定变量的取值范围，只能是指定的字面值之一

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from typing import Literal

def process_color(color: Literal["red", "green", "blue"]) -> None:
    print("Selected color:", color)

process_color("red")
process_color("green")
process_color("blue")

AsyncGenerator: 表示异步生成器类型。类似于 Generator，但用于异步上下文中生成值的类型

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from typing import AsyncGenerator
import asyncio

async def generate_data() -> AsyncGenerator[int, str]:
    yield 1
    yield 2
    yield 3

async def process_data() -> None:
    async for num in generate_data():
        print("Received:", num)

asyncio.run(process_data())

ContextManager: 表示上下文管理器类型。用于定义支持 with 语句的对象的类型

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from typing import ContextManager

class MyContextManager:
    def __enter__(self):
        print("Entering context")

    def __exit__(self, exc_type, exc_value, traceback):
        print("Exiting context")

def process_data(manager: ContextManager) -> None:
    with manager:
        print("Processing data")

process_data(MyContextManager())

AsyncIterator: 表示异步迭代器类型。类似于 Iterator，但用于异步上下文中进行迭代的类型

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from typing import AsyncIterator
import asyncio

async def async_range(n: int) -> AsyncIterator[int]:
    for i in range(n):
        yield i
        await asyncio.sleep(1)

async def process_data() -> None:
    async for num in async_range(5):
        print("Received:", num)

asyncio.run(process_data())

Annotated: 用于添加类型注解的装饰器。可以在类型提示中添加额外的元数据信息

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from typing import Annotated

def process_data(data: Annotated[str, "user input"]) -> None:
    print("Received data:", data)

process_data("Hello")

AbstractSet: 表示抽象集合类型。是 Set 的基类，用于指定集合的抽象接口。通常用作父类或类型注解

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from typing import AbstractSet

def process_data(data: AbstractSet[str]) -> None:
    for item in data:
        print(item)

my_set: AbstractSet[str] = {"apple", "banana", "orange"}
process_data(my_set)

Awaitable: 表示可等待对象的类型。用于指定可以使用 await 关键字等待的对象的类型。

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from typing import Awaitable
import asyncio

async def async_task() -> int:
    await asyncio.sleep(1)
    return 42

async def process_task(task: Awaitable[int]) -> None:
    result = await task
    print("Task result:", result)

asyncio.run(process_task(async_task()))

AsyncIterable: 表示异步可迭代对象的类型。类似于 Iterable，但用于异步上下文中进行迭代的类型。

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from typing import AsyncIterable
import asyncio

async def async_range(n: int) -> AsyncIterable[int]:
    for i in range(n):
        yield i
        await asyncio.sleep(1)

async def process_data() -> None:
    async for num in async_range(5):
        print("Received:", num)

asyncio.run(process_data())

AwaitableGenerator: 表示可等待生成器类型。结合了 Generator 和 Awaitable，用于异步上下文中生成值并可使用 await 等待的类型。

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from typing import AwaitableGenerator
import asyncio

async def async_generator() -> AwaitableGenerator[int, str, int]:
    yield 1
    await asyncio.sleep(1)
    yield 2
    await asyncio.sleep(1)
    yield 3

async def process_generator() -> None:
    async for num in async_generator():
        print("Received:", num)

asyncio.run(process_generator())

AsyncContextManager: 表示异步上下文管理器类型。类似于 ContextManager，但用于异步上下文中支持 async with 语句的对象的类型

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from typing import AsyncContextManager
import asyncio

class MyAsyncContextManager:
    async def __aenter__(self):
        print("Entering async context")

    async def __aexit__(self, exc_type, exc_value, traceback):
        print("Exiting async context")

async def process_data(manager: AsyncContextManager) -> None:
    async with manager:
        print("Processing data")

asyncio.run(process_data(MyAsyncContextManager()))

MutableMapping: 可变的键值对映射类型，它是 Mapping 的子类

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from typing import MutableMapping

def process_data(data: MutableMapping[str, int]) -> None:
    data["count"] = 10

my_dict: MutableMapping[str, int] = {"name":  "John", "age": 30}
process_data(my_dict)
print(my_dict)

MutableSet: 可变的集合类型，它是 Set 的子类

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from typing import MutableSet

def process_data(data: MutableSet[int]) -> None:
    data.add(4)

my_set: MutableSet[int] = {1, 2, 3}
process_data(my_set)
print(my_set)

MappingView: 映射视图类型，它提供了对映射对象的只读访问

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from typing import MappingView

def process_data(data: MappingView[str, int]) -> None:
    for key, value in data.items():
        print(key, value)

my_dict = {"name": "John", "age": 30}
process_data(my_dict.items())

Match: 正则表达式匹配对象类型，用于表示匹配的结果

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from typing import Match
import re

def process_data(pattern: str, text: str) -> None:
    match: Match = re.search(pattern, text)
    if match:
        print("Match found:", match.group())
    else:
        print("No match found")

process_data(r"\d+", "abc123def")

MutableSequence: 可变的序列类型，它是 Sequence 的子类

`
from typing import MutableSequence

def process_data(data: MutableSequence[int]) -> None:
data.append(4)

my_list: MutableSequence[int] = [1, 2, 3]
process_data(my_list)
print(my_list)
···