如何将multiprocessing.Pool实例传递给apply_async回调函数？

Question

这是我的质因数分解程序，我在pool.apply_async（findK，args =（N，begin，end））中添加了回调函数，当分解结束时，会弹出消息提示prime factorization is over，它正常工作。

import math
import multiprocessing 

def findK(N,begin,end):
    for k in range(begin,end):
        if N% k == 0:
            print(N,"=" ,k ,"*", N/k)
            return True
    return False


def prompt(result):
    if result:
        print("prime factorization is over")


def mainFun(N,process_num):
    pool = multiprocessing.Pool(process_num)
    for i in range(process_num):
        if i ==0 :
            begin =2
        else:
            begin = int(math.sqrt(N)/process_num*i)+1
        end = int(math.sqrt(N)/process_num*(i+1))
        pool.apply_async(findK, args=(N,begin,end) , callback = prompt)    
    pool.close()
    pool.join()    

if __name__ == "__main__":
    N = 684568031001583853
    process_num = 16
    mainFun(N,process_num)

现在我想在apply_async中更改回调函数，将提示更改为关闭函数以杀死所有其他进程。

def prompt(result):
    if result:
        pool.terminate()

提示作用域中未定义池实例或未传入提示功能。
pool.terminate() 无法在提示函数中运行。
如何将 multiprocessing.Pool 实例传递给 apply_async 的回调函数？
（我已将其制作成类格式，只需添加一个类方法并调用 self.pool.terminate 即可杀死所有其他进程， 如何在函数格式中完成工作？）

如果没有将池设为全局变量，则可以将池传递到回调函数中吗？

- showkey

Answer 1

目前不支持向回调函数传递额外的参数。但是您有许多优雅的方法来解决这个问题。

您可以将池逻辑封装到一个对象中：

class Executor:
    def __init__(self, process_num):
        self.pool = multiprocessing.Pool(process_num)

    def prompt(self, result):
        if result:
            print("prime factorization is over")
            self.pool.terminate()

    def schedule(self, function, args):
        self.pool.apply_async(function, args=args, callback=self.prompt)

    def wait(self):
        self.pool.close()
        self.pool.join() 


def main(N,process_num):
    executor = Executor(process_num)
    for i in range(process_num):
        ...
        executor.schedule(findK, (N,begin,end))   
    executor.wait()

或者您可以使用concurrent.futures.Executor实现，该实现返回一个Future对象。在设置回调之前，只需将池附加到Future对象即可。

def prompt(future):
    if future.result():
        print("prime factorization is over")
        future.pool_executor.shutdown(wait=False)

def main(N,process_num):
    executor = concurrent.futures.ProcessPoolExecutor(max_workers=process_num)
    for i in range(process_num):
        ...
        future = executor.submit(findK, N,begin,end)
        future.pool_executor = executor
        future.add_done_callback(prompt)

- noxdafox

Answer 2

您可以简单地定义一个本地的close函数作为回调函数：

import math
import multiprocessing 


def findK(N, begin, end):
    for k in range(begin, end):
        if N % k == 0:
            print(N, "=", k, "*", N / k)
            return True
    return False


def mainFun(N, process_num):
    pool = multiprocessing.Pool(process_num)

    def close(result):
        if result:
            print("prime factorization is over")
            pool.terminate()
    for i in range(process_num):
        if i == 0:
            begin = 2
        else:
            begin = int(math.sqrt(N) / process_num * i) + 1
        end = int(math.sqrt(N) / process_num * (i + 1))
        pool.apply_async(findK, args=(N, begin, end), callback=close)
    pool.close()
    pool.join()


if __name__ == "__main__":
    N = 684568031001583853
    process_num = 16
    mainFun(N, process_num)

你可以使用functools库中的partial函数，格式如下：partial。

import functools

def close_pool(pool, results):
    if result:
        pool.terminate()

def mainFun(N, process_num):
    pool = multiprocessing.Pool(process_num)

    close = funtools.partial(close_pool, pool)
....

- Thomas Moreau

Answer 3

您需要让“pool”进入“prompt”的环境中。一种可能的方法是将“pool”移至全局范围（尽管这不是最佳实践）。看起来这样可以解决问题：

import math
import multiprocessing 

pool = None

def findK(N,begin,end):
    for k in range(begin,end):
        if N% k == 0:
            print(N,"=" ,k ,"*", N/k)
            return True
    return False


def prompt(result):
    if result:
        print("prime factorization is over")
        pool.terminate()


def mainFun(N,process_num):
    global pool
    pool = multiprocessing.Pool(process_num)
    for i in range(process_num):
        if i ==0 :
            begin =2
        else:
            begin = int(math.sqrt(N)/process_num*i)+1
        end = int(math.sqrt(N)/process_num*(i+1))
        pool.apply_async(findK, args=(N,begin,end) , callback = prompt)    
    pool.close()
    pool.join()    

if __name__ == "__main__":
    N = 684568031001583853
    process_num = 16
    mainFun(N,process_num)

- Christian Ternus

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如果没有将池设置为全局变量，那么池能被传递到回调函数中吗？ - showkey