Python多处理池: how to join the reasults in a parallel way?

Question

我已阅读Python multiprocessing.Pool: when to use apply, apply_async or map?它很有用，但仍然有我自己的问题。在下面的代码中，我希望 result_list.append(result) 以并行方式，我希望 4 个处理器并行附加结果并将 4 个列表转换为 1 个列表。

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(4)
    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()

Answer 1

Multiprocessing pool将是您的选择。

以下是一些示例代码，希望对您有所帮助。您也可以查看我的另一个答案以查看更多详细信息。 How can I make my python code run faster

    from multiprocessing import Pool
    import time

    def foo_pool(x):
        return x*x

    def main():
         pool = Pool(4)
         sampleData = [x for x in range(9)]
         results = pool.map(foo_pool, sampleData)
         pool.close()
         pool.join()
         print(results)

    if __name__ == '__main__':
         main()