python内置模块typing 类型提示

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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

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2. List：表示列表类型。

欢迎大家来到IT世界,在知识的湖畔探索吧!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。

欢迎大家来到IT世界,在知识的湖畔探索吧!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)