python内置模块typing 类型提示

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

1. Any：表示任意类型。

   from typing import Any
   
   test:Any = 2
   
   def process_data(data: Any) -> None:
       # 对任意类型的数据进行处理
       pass
   

2. List：表示列表类型。

   from typing import List
   
   test: List[int] = [2]
   
   def process_list(items: List[int]) -> None:
       # 处理整数列表
       pass
   

3. Tuple：表示元组类型。

   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
   

4. Dict：表示字典类型。

   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
   

5. Set：表示集合类型。

   from typing import Set
   
   test: Set[int] = {2,3}
   
   def process_set(data: Set[str]) -> None:
       # 处理字符串集合
       pass
   

6. Union：表示多个可能的类型。

   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
   

7. Optional：表示可选类型，即可以是指定类型或者 None。

   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
   

8. Callable：表示可调用对象的类型。

   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)
   

9. Iterator：表示迭代器类型。

   from typing import Iterator
   
   test:Iterator[int] = iter([2])
   
   def process_iterator(data: Iterator[int]) -> None:
       # 处理整数迭代器
       pass
   

10. Generator：表示生成器类型。

    from typing import Generator
    
    def generate_numbers() -> Generator[int, None, None]:
       yield 1
       yield 2
    
    test: Generator[int, None, None] = generate_numbers()
    

11. Iterable：表示可迭代对象的类型。

    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
    

12. Mapping：表示映射类型。

    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
    

13. Sequence：表示序列类型。

    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
    

14. AnyStr：表示任意字符串类型。

    from typing import AnyStr
    
    str:AnyStr = '213'
    

15. NoReturn：表示函数没有返回值。

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

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

    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)
    

17. 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

    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")
    

18. 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

    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())
    

19. 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

    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())
    

20. 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

    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())
    
    

21. 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

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

22. 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

    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)
    

23. 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。

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()))

24. 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。

    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())
    

25. 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。

    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())
    

26. 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

    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()))
    

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

    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)
    

28. MutableSet: 可变的集合类型，它是 Set 的子类

    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)
    

29. MappingView: 映射视图类型，它提供了对映射对象的只读访问

    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())
    
    

30. Match: 正则表达式匹配对象类型，用于表示匹配的结果

    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")
    

31. 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)