Python 多进程池.当其中一个工作进程确定不再需要完成工作时,如何退出脚本?

2022-01-12 00:00:00 python multiprocessing pool worker

问题描述

mp.set_start_method('spawn')
total_count = Counter(0)
pool = mp.Pool(initializer=init, initargs=(total_count,), processes=num_proc)    

pool.map(part_crack_helper, product(seed_str, repeat=4))
pool.close()
pool.join()

所以我有一个工作进程池来做一些工作.它只需要找到一种解决方案.因此,当其中一个工作进程找到解决方案时,我想停止一切.

So I have a pool of worker process that does some work. It just needs to find one solution. Therefore, when one of the worker processes finds the solution, I want to stop everything.

我想到的一种方法就是调用 sys.exit().但是,这似乎无法正常工作,因为其他进程正在运行.

One way I thought of was just calling sys.exit(). However, that doesn't seem like it's working properly since other processes are running.

另一种方法是检查每个进程调用的返回值(part_crack_helper 函数的返回值)并在该进程上调用终止.但是,我不知道在使用该地图功能时该怎么做.

One other way was to check for the return value of each process calls (the return value of part_crack_helper function) and call terminate on that process. However, I don't know how to do that when using that map function.

我应该如何做到这一点?

How should I achieve this?


解决方案

您可以使用来自 Pool.apply_async 的回调.

You can use callbacks from Pool.apply_async.

这样的事情应该可以为您完成这项工作.

Something like this should do the job for you.

from multiprocessing import Pool


def part_crack_helper(args):
    solution = do_job(args)
    if solution:
        return True
    else:
        return False


class Worker():
    def __init__(self, workers, initializer, initargs):
        self.pool = Pool(processes=workers, 
                         initializer=initializer, 
                         initargs=initargs)

    def callback(self, result):
        if result:
            print("Solution found! Yay!")
            self.pool.terminate()

    def do_job(self):
        for args in product(seed_str, repeat=4):
            self.pool.apply_async(part_crack_helper, 
                                  args=args, 
                                  callback=self.callback)

        self.pool.close()
        self.pool.join()
        print("good bye")


w = Worker(num_proc, init, [total_count])
w.do_job()

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