我是用新的闪亮试验concurrent.futures在Python
3.2模块引起，而我注意到，几乎相同的代码，使用泳池从concurrent.futures的 方式
比使用慢multiprocessing.Pool。

这是使用多重处理的版本：

def hard_work(n):
    # Real hard work here
    pass

if __name__ == '__main__':
    from multiprocessing import Pool, cpu_count

    try:
        workers = cpu_count()
    except NotImplementedError:
        workers = 1
    pool = Pool(processes=workers)
    result = pool.map(hard_work, range(100, 1000000))

这是使用current.futures：

def hard_work(n):
    # Real hard work here
    pass

if __name__ == '__main__':
    from concurrent.futures import ProcessPoolExecutor, wait
    from multiprocessing import cpu_count
    try:
        workers = cpu_count()
    except NotImplementedError:
        workers = 1
    pool = ProcessPoolExecutor(max_workers=workers)
    result = pool.map(hard_work, range(100, 1000000))

使用从Eli Bendersky文章中获得的简单分解函数，这些就是我计算机（i7、64位，Arch Linux）上的结果：

[juanlu@nebulae]─[~/Development/Python/test]
└[10:31:10] $ time python pool_multiprocessing.py

real    0m10.330s
user    1m13.430s
sys 0m0.260s
[juanlu@nebulae]─[~/Development/Python/test]
└[10:31:29] $ time python pool_futures.py

real    4m3.939s
user    6m33.297s
sys 0m54.853s

我无法使用Python探查器对它们进行探查，因为出现泡菜错误。有任何想法吗？