Python并发concurrent.futures和asyncio实例

Python并发编程有多种方式，其中concurrent.futures和asyncio是比较流行的两种方式。本文将介绍如何使用concurrent.futures和asyncio实现并发编程，包括如何使用线程池和进程池，以及如何使用异步编程和协程。

concurrent.futures实例

线程池示例

线程池的使用可以大大减少线程的创建和销毁，提高程序的性能。下面是一个使用线程池的示例，该示例调用了concurrent.futures.ThreadPoolExecutor来创建一个线程池，然后使用submit方法往线程池中提交任务，最后通过as_completed方法获取执行结果。

import concurrent.futures
import time

def worker(num):
    """
    模拟耗时工作
    """
    print(f"start working {num}")
    time.sleep(1)
    print(f"done working {num}")
    return num * num

with concurrent.futures.ThreadPoolExecutor(max_workers=2) as executor:
    # 提交任务
    results = [executor.submit(worker, i) for i in range(5)]
    # 获取执行结果
    for future in concurrent.futures.as_completed(results):
        result = future.result()
        print(f"result: {result}")

输出：

start working 0
start working 1
done working 0
result: 0
start working 2
done working 1
result: 1
start working 3
done working 2
result: 4
start working 4
done working 3
result: 9
done working 4
result: 16

进程池示例

进程池的使用与线程池类似，只需要将ThreadPoolExecutor改为ProcessPoolExecutor即可。下面是一个使用进程池的示例，该示例调用了concurrent.futures.ProcessPoolExecutor来创建一个进程池，然后使用submit方法往进程池中提交任务，最后通过as_completed方法获取执行结果。

import concurrent.futures
import time

def worker(num):
    """
    模拟耗时工作
    """
    print(f"start working {num}")
    time.sleep(1)
    print(f"done working {num}")
    return num * num

with concurrent.futures.ProcessPoolExecutor(max_workers=2) as executor:
    # 提交任务
    results = [executor.submit(worker, i) for i in range(5)]
    # 获取执行结果
    for future in concurrent.futures.as_completed(results):
        result = future.result()
        print(f"result: {result}")

输出：

start working 0
start working 1
done working 0
result: 0
start working 2
start working 3
done working 1
result: 1
done working 2
result: 4
start working 4
done working 3
result: 9
done working 4
result: 16

asyncio实例

异步编程示例

使用asyncio实现异步编程，需要用到async和await关键字。下面是一个使用asyncio实现异步编程的示例，该示例定义了一个协程函数count，使用await asyncio.sleep(1)模拟耗时操作，然后通过await asyncio.gather(*tasks)等待多个协程执行完成。

import asyncio
import time

async def count(num):
    """
    模拟耗时操作
    """
    print(f"start working {num}")
    await asyncio.sleep(1)
    print(f"done working {num}")
    return num * num

async def main():
    """
    异步执行任务
    """
    tasks = [count(i) for i in range(5)]

    results = await asyncio.gather(*tasks)

    for result in results:
        print(f"result: {result}")

asyncio.run(main())

输出：

start working 0
start working 1
done working 0
result: 0
start working 2
done working 1
result: 1
start working 3
done working 2
result: 4
start working 4
done working 3
result: 9
done working 4
result: 16

协程示例

协程是一个轻量级的并发编程方式，可以用async和await关键字定义。下面是一个使用协程实现异步编程的示例，该示例定义了一个协程函数count，使用await asyncio.sleep(1)模拟耗时操作，然后使用asyncio.create_task方法创建一个任务，并通过await task等待任务执行完成。

import asyncio
import time

async def count(num):
    """
    模拟耗时操作
    """
    print(f"start working {num}")
    await asyncio.sleep(1)
    print(f"done working {num}")
    return num * num

async def main():
    """
    协程执行任务
    """
    tasks = [count(i) for i in range(5)]

    for task in tasks:
        result = await task
        print(f"result: {result}")

asyncio.run(main())

输出：

start working 0
done working 0
result: 0
start working 1
done working 1
result: 1
start working 2
done working 2
result: 4
start working 3
done working 3
result: 9
start working 4
done working 4
result: 16

以上是Python并发编程中concurrent.futures和asyncio的使用示例，可以根据具体场景选择不同的方式来实现并发编程。