我们一起聊聊Python协程和异步编程

协程和异步编程是Python中处理并发和异步任务的重要概念。协程是一种轻量级的并发编程方式，它允许程序在执行过程中暂停和恢复，以便处理其他任务。异步编程模型则是基于协程的一种编程风格，它通过使用非阻塞的异步IO操作来提高程序的并发性能。

Python中的异步编程主要依赖于`asyncio`模块。`asyncio`提供了一套用于编写异步代码的工具和框架，包括协程、事件循环和异步IO操作等。

代码示例：

1. 使用`async`和`await`定义协程函数：

import asyncio


async def my_coroutine():
    await asyncio.sleep(1)
    print("Coroutine executed")


asyncio.run(my_coroutine())

2. 使用`asyncio.create_task()`并发运行多个协程：

import asyncio


async def coroutine1():
    await asyncio.sleep(1)
    print("Coroutine 1 executed")


async def coroutine2():
    await asyncio.sleep(2)
    print("Coroutine 2 executed")


async def main():
    task1 = asyncio.create_task(coroutine1())
    task2 = asyncio.create_task(coroutine2())
    await asyncio.gather(task1, task2)


asyncio.run(main())

3. 使用`asyncio.wait()`等待多个协程完成：

import asyncio


async def coroutine1():
    await asyncio.sleep(1)
    print("Coroutine 1 executed")


async def coroutine2():
    await asyncio.sleep(2)
    print("Coroutine 2 executed")


async def main():
    tasks = [coroutine1(), coroutine2()]
    done, pending = await asyncio.wait(tasks)
    for task in done:
        print(f"Task {task} completed")


asyncio.run(main())

4. 使用`asyncio.Lock()`实现协程间的互斥访问：

import asyncio


async def counter(lock):
    async with lock:
        for _ in range(5):
            print("Counting")
            await asyncio.sleep(1)


async def main():
    lock = asyncio.Lock()
    tasks = [counter(lock) for _ in range(3)]
    await asyncio.gather(*tasks)


asyncio.run(main())

5. 使用`asyncio.Queue()`实现协程间的消息传递：

import asyncio


async def producer(queue):
    for i in range(5):
        await queue.put(i)
        print(f"Produced: {i}")
        await asyncio.sleep(1)


async def consumer(queue):
    while True:
        item = await queue.get()
        print(f"Consumed: {item}")
        await asyncio.sleep(2)


async def main():
    queue = asyncio.Queue()
    producer_task = asyncio.create_task(producer(queue))
    consumer_task = asyncio.create_task(consumer(queue))
    await asyncio.gather(producer_task, consumer_task)


asyncio.run(main())

6. 使用`asyncio.TimeoutError`设置协程的超时：

import asyncio


async def my_coroutine():
    await asyncio.sleep(2)
    print("Coroutine executed")


async def main():
    try:
        await asyncio.wait_for(my_coroutine(), timeout=1)
    except asyncio.TimeoutError:
        print("Coroutine timed out")


asyncio.run(main())

7. 使用`asyncio.run_in_executor()`在协程中执行阻塞的同步操作：

import asyncio


def sync_operation():
    # 阻塞的同步操作
    return "Sync result"


async def main():
    loop = asyncio.get_running_loop()
    result = await loop.run_in_executor(None, sync_operation)
    print(f"Result: {result}")


asyncio.run(main())

8. 使用`aiohttp`库进行异步HTTP请求：

import asyncio
import aiohttp


async def fetch_data(url):
    async with aiohttp.ClientSession() as session:
        async with session.get(url) as response:
            return await response.text()


async def main():
    url = "https://api.example.com/data"
    data = await fetch_data(url)
    print(f"Data: {data}")


asyncio.run(main())

9. 使用`asyncio.sleep()`模拟异步计时器：

import asyncio


async def timer(duration):
    await asyncio.sleep(duration)
    print(f"Timer finished after {duration} seconds")


async def main():
    tasks = [timer(1), timer(2), timer(3)]
    await asyncio.gather(*tasks)


asyncio.run(main())

10. 使用`asyncio`实现并发的文件IO操作：

import asyncio


async def read_file(file):
    async with asyncio.open_file(file, "r") as f:
        contents = await f.read()
        print(f"Read from {file}: {contents}")


async def write_file(file, data):
    async with asyncio.open_file(file, "w") as f:
        await f.write(data)
        print(f"Wrote to {file}")


async def main():
    file = "data.txt"
    await write_file(file, "Hello, world!")
    await read_file(file)


asyncio.run(main())

这些场景代码展示了协程和异步编程的使用方式。通过使用`asyncio`模块和相关的工具，我们可以轻松地编写并发和异步任务处理的代码，提高程序的性能和响应能力。