Joseph Herlant
version 1.0.0, 2014-06-26 : Initial version

This script shows how to simply use apply_async to delegate tasks to a pool of workers using the multiprocessing module.

There’s another article that shows how to also do this unsing queues.

from  multiprocessing import Pool
from os import getpid
from time import sleep
from random import random


class TestingMpApplyAsync(object):
    def __init__(self):
        Initiates a pool of processes.
        self.pool = Pool(processes=MAX_WORKERS,)

    def generate_some_work(self):
        This method writes some messages to the queue.
        for i in range(50):
            self.pool.apply_async(worker_main, ["First item for loop %d" % i])
            self.pool.apply_async(worker_main, ["2nd item for loop %d" % i])

def worker_main(msg):
    This function will be executed by a subprocess of the pool.
    It can't be integrated to a class because you can't pass a method of
    an object instance to apply_async(), you need to use a function.
    print "{0} retrieved: {1}".format(getpid(), msg)
    # simulate some random length operations

# Warning from Python documentation:
# Functionality within this package requires that the __main__ module be
# importable by the children. This means that some examples, such as the
# multiprocessing.Pool examples will not work in the interactive interpreter.
if __name__ == '__main__':
    mp_class = TestingMpApplyAsync()
    # Waits a bit for the child processes to do some work
    # because when the parent exits, childs are terminated.