Python 多进程

与相比Pool.apply，该Pool.apply_async方法还具有一个回调，如果提供该回调，则在函数完成时调用该回调。可以使用它来代替get()。

例如：

import multiprocessing as mp
import time
def foo_pool(x):
    time.sleep(2)
    return x*x
result_list = []
def log_result(result):
    # This is called whenever foo_pool(i) returns a result.
    # result_list is modified only by the main process, not the pool workers.
    result_list.append(result)
def apply_async_with_callback():
    pool = mp.Pool()
    for i in range(10):
        pool.apply_async(foo_pool, args = (i, ), callback = log_result)
    pool.close()
    pool.join()
    print(result_list)
if __name__ == '__main__':
    apply_async_with_callback()

可能会产生如下结果

[1, 0, 4, 9, 25, 16, 49, 36, 81, 64]

请注意，与不同pool.map，结果的顺序可能与pool.apply_async调用的顺序不同。但是有一个技巧可以排序：

import multiprocessing as mp
import time
def foo_pool(index,x):
    time.sleep(2)
    return [index, x*x]  # 返回之中加入 index
result_list = []
def log_result(result):
    # This is called whenever foo_pool(i) returns a result.
    # result_list is modified only by the main process, not the pool workers.
    result_list.append(result)
def apply_async_with_callback():
    pool = mp.Pool()
    for i in range(10):
        pool.apply_async(foo_pool, args = (index, i,), callback = log_result)
    pool.close()
    pool.join()
    # 然后根据 result_list 每个元素的第一个值（即我们放入的index）排序
    result_list = sorted(result_list, key=lambda k: dic[0])
    print(result_list)
if __name__ == '__main__':
    apply_async_with_callback()