This is a short example of the python async pool I created for a friend. Maybe it is useful to you too

async_multiprocessing.py

#!/usr/bin/env python
__author__ = 'jules'
from multiprocessing import Pool
import random
import time

class Job:
    """
    Representation of a Job. Used to pass data to the pool and to return the result.
    You can add all the information you need to this object
    """
    def __init__(self, data, callback):
        self.data = data
        self.result = 0


def main():

    p = Pool(processes=2) # creation of the pool. The number of processes should not exceed the number of physical cpu cores available
    while True: # run in a loop forever
        try:
            job_data = int(raw_input('Input:')) # get a new int from the user
            the_job = Job( job_data ) # create a new Job object
            p.apply_async(process_job, args=[the_job], callback=callback_function) # perform the task asynchronously, call the callback function after you're done
        except ValueError:
            print "Not a number" # exception handler for when the user does not enter a valid integer



def process_job(job): # function that gets called in a seperate process
    print("Processing job. The given data was: %d" % (job.data))
    job.result = random.randint(1,5)
    time.sleep(job.result)
    return job # it is important that you return the job object because it is given as a parameter to the callback function

def callback_function(job): # the function called after the task is finished
    print("Job is done! The result was %s" % (job.result))



if __name__ == "__main__":
    main()