运行多个异步函数并获取每个函数的返回值 [英] Running multiple asynchronous function and get the returned value of each function

问题描述

我试图创建一个可以异步运行多个进程并发送响应的函数.由于multiprocessing.Process()不返回响应，因此我考虑将函数创建为:

I was trying to create a function which can run multiple processes asynchronous and will send the response. Since multiprocessing.Process() do not return the response, I thought of creating a function as:

from multiprocessing import Process

def async_call(func_list):
    """
    Runs the list of function asynchronously.

    :param func_list: Expects list of lists to be of format
        [[func1, args1, kwargs1], [func2, args2, kwargs2], ...]
    :return: List of output of the functions
        [output1, output2, ...]
    """
    response_list = []
    def worker(function, f_args, f_kwargs, response_list):
        """
        Runs the function and appends the output to list
        """
        response = function(*f_args, **f_kwargs)
        response_list.append(response)

    processes = [Process(target=worker, args=(func, args, kwargs, response_list)) \
                    for func, args, kwargs in func_list]

    for process in processes:
        process.start()
    for process in processes:
        process.join()
    return response_list

在此函数中，我异步调用worker，它接受其他参数作为list.由于列表是作为参考传递的，所以我认为我可以在列表中附加实际功能的响应.然后async_call将返回我所有功能的响应.

Within this function, I call worker asynchronously which accepts additional parameter as list. Since, lists are passed as reference, I thought I can append the response of actual function within the list. And async_call will return me the response of all the function.

但是，这并不符合我的预期.值被附加到worker()内的list上，但在工作程序response_list列表之外仍为空.

But this is not behaving the way I expected. Value gets appended to the list within the worker(), but outside the worker response_list list remains empty.

知道我在做什么错吗?而且，有没有其他选择可以实现我正在做的事情?

Any idea what I am doing wrong? And, is there any alternative to achieve what I am doing?

推荐答案

您不能直接在进程之间共享对象.您需要使用为传递值而专门设计的类之一，即Queue和Pipe；参见文档.

You can't share objects directly across processes. You need to use one of the classes especially designed for communicating values, Queue and Pipe; see the documentation.

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