“multiprocessing”模块中的模拟“as_completed”

我正在寻找一个类似的as_completed函数（来自 Python 3concurrent.futures) 在 Python 2.7 模块中multiprocessing。我当前的解决方案：

import time
from multiprocessing import Pool
def f(x):
    time.sleep(x)
    return x
if __name__ == '__main__':
    pool = Pool()
    a = pool.apply_async(f, [4])
    b = pool.apply_async(f, [2])
    while any([a,b]):
        if a and a.ready(): print a.get(); a=False 
        if b and b.ready(): print b.get(); b=False

一种快速但肮脏的方法是将异步结果对象存储在可迭代中并定期轮询其状态。

from multiprocessing import Pool
from random import random
from time import sleep


def wrapped_sleep(n, i):
    sleep(n)
    return n, i

if __name__ == '__main__':
    pool = Pool()
    random_sleep_durations = [random() * 10 for _ in xrange(100)]
    results = [
        pool.apply_async(wrapped_sleep, (n, i, ))
        for i, n in enumerate(random_sleep_durations)
    ]

    while results:
        sleep(0.1)
        mature_indices = []
        mature_results = []

        for i, candidate in enumerate(results):
            if candidate.ready():
                mature_indices.append(i)
                break

        for i in mature_indices:
            mature_results.append(results.pop(i).get())

        for result in mature_results:
            print result