• Python进阶:并发编程之Futures

    区分并发和并行

    　　并发(Concurrency).

    　　由于Python 的解释器并不是线程安全的，为了解决由此带来的 race condition 等问题，Python 便引入了全局解释器锁，也就是同一时刻，只允许一个线程执行。当然，在执行 I/O 操作时，如果一个线程被 block 了，全局解释器锁便会被释放，从而让另一个线程能够继续执行。所以在Python中，并发并不是指同一时刻有多个操作(thread、task)同时进行，而是同一时刻，只允许有一个线程或任务执行。
    　　

    　　并行(Parallelism)

    　　指多个进程完全同步同时的执行。
    　　
     

    并发编程之 Futures

    　　单线程与多线程性能比较

    　　假设我们有一个任务，是下载一些网站的内容并打印。如果用单线程的方式，它的代码实现如下所示
    import requests
import time

def download_one(url):
    resp = requests.get(url)
    print('Read {} from {}'.format(len(resp.content), url))
    
def download_all(sites):
    for site in sites:
        download_one(site)

def main():
    sites = [
        'https://en.wikipedia.org/wiki/Portal:Arts',
        'https://en.wikipedia.org/wiki/Portal:History',
        'https://en.wikipedia.org/wiki/Portal:Society',
        'https://en.wikipedia.org/wiki/Portal:Biography',
        'https://en.wikipedia.org/wiki/Portal:Mathematics',
        'https://en.wikipedia.org/wiki/Portal:Technology',
        'https://en.wikipedia.org/wiki/Portal:Geography',
        'https://en.wikipedia.org/wiki/Portal:Science',
        'https://en.wikipedia.org/wiki/Computer_science',
        'https://en.wikipedia.org/wiki/Python_(programming_language)',
        'https://en.wikipedia.org/wiki/Java_(programming_language)',
        'https://en.wikipedia.org/wiki/PHP',
        'https://en.wikipedia.org/wiki/Node.js',
        'https://en.wikipedia.org/wiki/The_C_Programming_Language',
        'https://en.wikipedia.org/wiki/Go_(programming_language)'
    ]
    start_time = time.perf_counter()
    download_all(sites)
    end_time = time.perf_counter()
    print('Download {} sites in {} seconds'.format(len(sites), end_time - start_time))
    
if __name__ == '__main__':
    main()

# 输出
Read 129196 from https://en.wikipedia.org/wiki/Portal:Arts
Read 183867 from https://en.wikipedia.org/wiki/Portal:History
Read 224161 from https://en.wikipedia.org/wiki/Portal:Society
Read 114387 from https://en.wikipedia.org/wiki/Portal:Biography
Read 152871 from https://en.wikipedia.org/wiki/Portal:Mathematics
Read 156339 from https://en.wikipedia.org/wiki/Portal:Technology
Read 162872 from https://en.wikipedia.org/wiki/Portal:Geography
Read 91504 from https://en.wikipedia.org/wiki/Portal:Science
Read 323262 from https://en.wikipedia.org/wiki/Computer_science
Read 391073 from https://en.wikipedia.org/wiki/Python_(programming_language)
Read 319710 from https://en.wikipedia.org/wiki/Java_(programming_language)
Read 470754 from https://en.wikipedia.org/wiki/PHP
Read 180774 from https://en.wikipedia.org/wiki/Node.js
Read 56799 from https://en.wikipedia.org/wiki/The_C_Programming_Language
Read 325451 from https://en.wikipedia.org/wiki/Go_(programming_language)
Download 15 sites in 67.349395015 seconds
    　　以上代码的流程：先是遍历存储网站的列表； 然后对当前网站执行下载操作；等到当前操作完成后，再对下一个网站进行同样的操作，一直到结束。
    　　接下来看多线程版本
    import concurrent.futures
import requests
import threading
import time

def download_one(url):
    try:
        resp = requests.get(url)
        print('Read {} from {}'.format(len(resp.content), url))
    except Exception as ex:
        print(ex)

def download_all(sites):
    with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
        results = executor.map(download_one, sites)
    # with concurrent.futures.ProcessPoolExecutor() as executor:
    #     results = executor.map(download_one,sites)

def main():
    sites = [
        'https://en.wikipedia.org/wiki/Portal:Arts',
        'https://en.wikipedia.org/wiki/Portal:History',
        'https://en.wikipedia.org/wiki/Portal:Society',
        'https://en.wikipedia.org/wiki/Portal:Biography',
        'https://en.wikipedia.org/wiki/Portal:Mathematics',
        'https://en.wikipedia.org/wiki/Portal:Technology',
        'https://en.wikipedia.org/wiki/Portal:Geography',
        'https://en.wikipedia.org/wiki/Portal:Science',
        'https://en.wikipedia.org/wiki/Computer_science',
        'https://en.wikipedia.org/wiki/Python_(programming_language)',
        'https://en.wikipedia.org/wiki/Java_(programming_language)',
        'https://en.wikipedia.org/wiki/PHP',
        'https://en.wikipedia.org/wiki/Node.js',
        'https://en.wikipedia.org/wiki/The_C_Programming_Language',
        'https://en.wikipedia.org/wiki/Go_(programming_language)'
    ]
    start_time = time.perf_counter()
    download_all(sites)
    end_time = time.perf_counter()
    print('Download {} sites in {} seconds'.format(len(sites), end_time - start_time))

if __name__ == '__main__':
    main()

# 输出
Read 114387 from https://en.wikipedia.org/wiki/Portal:Biography
Read 129196 from https://en.wikipedia.org/wiki/Portal:Arts
Read 183867 from https://en.wikipedia.org/wiki/Portal:History
Read 152871 from https://en.wikipedia.org/wiki/Portal:Mathematics
Read 224161 from https://en.wikipedia.org/wiki/Portal:Society
Read 156339 from https://en.wikipedia.org/wiki/Portal:Technology
Read 91504 from https://en.wikipedia.org/wiki/Portal:Science
Read 391073 from https://en.wikipedia.org/wiki/Python_(programming_language)
Read 162872 from https://en.wikipedia.org/wiki/Portal:Geography
Read 323262 from https://en.wikipedia.org/wiki/Computer_science
Read 56799 from https://en.wikipedia.org/wiki/The_C_Programming_Language
Read 319710 from https://en.wikipedia.org/wiki/Java_(programming_language)
Read 325451 from https://en.wikipedia.org/wiki/Go_(programming_language)
Read 180774 from https://en.wikipedia.org/wiki/Node.js
Read 470754 from https://en.wikipedia.org/wiki/PHP
Download 15 sites in 10.022916933 seconds
    　　以上代码效率提高了6倍。使用ThreadPoolExecutor创建了一个线程池，max_workers分配了5个线程，executor.map(download_one, sites)对sites的元素并发的调用download_one函数。其中requests.get()方法是线程安全的(thread-safe)，在多线程环境中可以安全地使用。线程的数量虽可以自定，但过多的线程会造成系统的开销增大。可以根据实际需求做测试，寻找最优线程数量。
    　　以上代码也可以用并行的方法来实现。在download_all()函数中：
    with futures.ThreadPoolExecutor(workers) as executor
=>
with futures.ProcessPoolExecutor() as executor:

    　　对于这种IO场景，用并行的方式并不会比并发的方式效率高.

    到底什么是 Futures ？

     　　Python 中的 Futures 模块，位于 concurrent.futures 和 asyncio 中，它们都表示带有延迟的操作。Futures 会将处于等待状态的操作包裹起来放到队列中，这些操作的状态随时可以查询，当然，它们的结果或是异常，也能够在操作完成后被获取。
    import concurrent.futures
import requests
import time

def download_one(url):
    resp = requests.get(url)
    print('Read {} from {}'.format(len(resp.content), url))
    return f'download {len(resp.content)} ok'

# def over(arg):
#     print(arg)
#     print('over')

def download_all(sites):
    #future列表中每个future完成的顺序，和它在列表中的顺序并不一定完全一致。
    #到底哪个先完成、哪个后完成，取决于系统的调度和每个future的执行时间
    with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
        to_do = []
        for site in sites:
            #executor.submit返回future实例
            future = executor.submit(download_one, site)
            to_do.append(future)
            #future.add_done_callback(over)
        
        #在futures完成后打印结果
        for future in concurrent.futures.as_completed(to_do):
            if future.exception() is not None:
                print(future.exception())
            else:
                print(future.result())

def main():
    sites = [
        'https://en.wikipedia.org/wiki/Portal:Arts',
        'https://en.wikipedia.org/wiki/Portal:History',
        'https://en.wikipedia.org/wiki/Portal:Society',
        'https://en.wikipedia.org/wiki/Portal:Biography',
        'https://en.wikipedia.org/wiki/Portal:Mathematics',
        'https://en.wikipedia.org/wiki/Portal:Technology',
        'https://en.wikipedia.org/wiki/Portal:Geography',
        'https://en.wikipedia.org/wiki/Portal:Science',
        'https://en.wikipedia.org/wiki/Computer_science',
        'https://en.wikipedia.org/wiki/Python_(programming_language)',
        'https://en.wikipedia.org/wiki/Java_(programming_language)',
        'https://en.wikipedia.org/wiki/PHP',
        'https://en.wikipedia.org/wiki/Node.js',
        'https://en.wikipedia.org/wiki/The_C_Programming_Language',
        'https://en.wikipedia.org/wiki/Go_(programming_language)'
    ]
    start_time = time.perf_counter()
    download_all(sites)
    end_time = time.perf_counter()
    print('Download {} sites in {} seconds'.format(len(sites), end_time - start_time))

if __name__ == '__main__':
    main()

# 输出
Read 129886 from https://en.wikipedia.org/wiki/Portal:Arts
Read 107634 from https://en.wikipedia.org/wiki/Portal:Biography
Read 224118 from https://en.wikipedia.org/wiki/Portal:Society
Read 158984 from https://en.wikipedia.org/wiki/Portal:Mathematics
Read 184343 from https://en.wikipedia.org/wiki/Portal:History
Read 157949 from https://en.wikipedia.org/wiki/Portal:Technology
Read 167923 from https://en.wikipedia.org/wiki/Portal:Geography
Read 94228 from https://en.wikipedia.org/wiki/Portal:Science
Read 391905 from https://en.wikipedia.org/wiki/Python_(programming_language)
Read 321352 from https://en.wikipedia.org/wiki/Computer_science
Read 180298 from https://en.wikipedia.org/wiki/Node.js
Read 321417 from https://en.wikipedia.org/wiki/Java_(programming_language)
Read 468421 from https://en.wikipedia.org/wiki/PHP
Read 56765 from https://en.wikipedia.org/wiki/The_C_Programming_Language
Read 324039 from https://en.wikipedia.org/wiki/Go_(programming_language)
Download 15 sites in 0.21698231499976828 seconds

    　　future列表中每个future完成的顺序，和它在列表中的顺序并不一定完全一致。到底哪个先完成、哪个后完成，取决于系统的调度和每个future的执行时间。

    　　并发通常用于 I/O 操作频繁的场景，而并行则适用于 CPU heavy 的场景。

     参考

     　　极客时间《Python核心技术与实战》专栏
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  • 原文地址：https://www.cnblogs.com/xiaoguanqiu/p/11136665.html
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