带有maxtasksperchild的池产生相等的PID [英] multiprocessing.Pool with maxtasksperchild produces equal PIDs

问题描述

我需要在一个与所有其他内存完全隔离的进程中运行一个函数几次.我想为此使用multiprocessing(因为我需要序列化来自函数的复杂输出).我将start_method设置为'spawn'并使用带有maxtasksperchild=1的池.我希望每个任务都有不同的过程，因此会看到不同的PID:

I need to run a function in a process, which is completely isolated from all other memory, several times. I would like to use multiprocessing for that (since I need to serialize a complex output coming from the functions). I set the start_method to 'spawn' and use a pool with maxtasksperchild=1. I would expect to get a different process for each task, and therefore see a different PID:

import multiprocessing
import time
import os

def f(x):
    print("PID: %d" % os.getpid())
    time.sleep(x)
    complex_obj = 5 #more complex axtually
    return complex_obj

if __name__ == '__main__':
    multiprocessing.set_start_method('spawn')
    pool = multiprocessing.Pool(4, maxtasksperchild=1)
    pool.map(f, [5]*30)
    pool.close()

但是我得到的输出是:

$ python untitled1.py 
PID: 30010
PID: 30009
PID: 30012
PID: 30011
PID: 30010
PID: 30009
PID: 30012
PID: 30011
PID: 30018
PID: 30017
PID: 30019
PID: 30020
PID: 30018
PID: 30019
PID: 30017
PID: 30020
...

因此，不会在每个任务之后重新生成进程.每次都有一种自动获取新PID的自动方法(即，无需为每个进程集启动新池)吗?

So the processes are not being respawned after every task. Is there an automatic way of getting a new PID each time (ie without starting a new pool for each set of processes)?

推荐答案

您还需要在对pool.map的调用中指定chunksize=1.否则，根据对工作进程的理解，将可迭代项中的多个项目捆绑在一起成为一个任务":

You need to also specify chunksize=1 in the call to pool.map. Otherwise, multiple items in your iterable get bundled together into one "task" from the perception of the worker processes:

import multiprocessing
import time
import os

def f(x):
    print("PID: %d" % os.getpid())
    time.sleep(x)
    complex_obj = 5 #more complex axtually
    return complex_obj

if __name__ == '__main__':
    multiprocessing.set_start_method('spawn')
    pool = multiprocessing.Pool(4, maxtasksperchild=1)
    pool.map(f, [5]*30, chunksize=1)
    pool.close()

输出现在没有重复的PID:

Output doesn't have repeated PIDs now:

PID: 4912
PID: 4913
PID: 4914
PID: 4915
PID: 4938
PID: 4937
PID: 4940
PID: 4939
PID: 4966
PID: 4965
PID: 4970
PID: 4971
PID: 4991
PID: 4990
PID: 4992
PID: 4993
PID: 5013
PID: 5014
PID: 5012

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