concurrency multiprocessing subclass

import multiprocessing
import time

class Consumer( multiprocessing.Process ):

    def __init__( self , task_queue , result_queue ):
        multiprocessing.Process.__init__( self )
        self.task_queue = task_queue
        self.result_queue = result_queue

    def run( self ):
        proc_name = self.name
        while True:
            next_task = self.task_queue.get()
            if next_task is None:                               # Poison pill means shutdown
                print '%s: Exiting' % proc_name
                self.task_queue.task_done()
                break
            print '%s: %s' % ( proc_name , next_task )
            answer = next_task()
            self.task_queue.task_done()
            self.result_queue.put( answer )
        return


class Task( object ):
    def __init__( self , a ,  b ):
        self.a = a
        self.b = b
    def __call__( self ):
        time.sleep( 0.1 )  # pretend to take some time to do the work
        return '%s * %s = %s' % (self.a, self.b, self.a * self.b)
    def __str__(self):
        return '%s * %s' % (self.a, self.b)


if __name__ == '__main__':

    tasks = multiprocessing.JoinableQueue()
    results = multiprocessing.Queue()

    # Start consumers
    num_consumers = multiprocessing.cpu_count() * 2
    print 'Creating %d consumers' % num_consumers
    consumers = [ Consumer(tasks, results)   for i in xrange(num_consumers) ]
    for w in consumers:
        w.start()


    num_jobs = 10
    for i in xrange(num_jobs):
        tasks.put( Task( i , i ) )


    for i in xrange(num_consumers):
        tasks.put(None)                     # Add a poison pill for each consumer

    tasks.join()            # Wait for all of the tasks to finish, optionally add a timeout


    while num_jobs:
        result = results.get()
        print 'Result:', result
        num_jobs -= 1