python 分布式进程

# -*- coding:gbk -*-
#master.py
from multiprocessing.managers import BaseManager
import random,time,queue

#定义发送任务的队列：
task_queue = queue.Queue()
#定义接受任务的队列：
result_queue = queue.Queue()


def return_task_queue():
    global task_queue
    return task_queue


def return_result_queue():
    global result_queue
    return result_queue

class QueueManager(BaseManager):
    pass
if __name__ == '__main__':
    QueueManager.register('get_task_queue', callable=return_task_queue)
    QueueManager.register('get_result_queue', callable=return_result_queue)
    manager = QueueManager(address=('127.0.0.1', 5000), authkey=b'abc')
    manager.start()
    task = manager.get_task_queue()
    result = manager.get_result_queue()
    for i in range(10):
        rand = random.randint(0,10000)
        print('Put:%s' % rand)
        task.put(rand)
    print('Try get results...')
    for i in range(10):
        r = result.get(timeout =10)
        print('result:%s' % r)
    manager.shutdown()
    print('master exit!')

# -*- coding:gbk -*-
#worker.py

from multiprocessing.managers import BaseManager
import random,time,queue
class QueueManager(BaseManager):
    pass
address = '127.0.0.1'
QueueManager.register('get_task_queue')
QueueManager.register('get_result_queue')
maneger = QueueManager(address=(address,5000),authkey=b'abc')
maneger.connect()

task = maneger.get_task_queue()
result =maneger.get_result_queue()
for i in range(10):
    # try:
        n = task.get(timeout=1)
        print('%d * %d = %d' % (n,n,n*n))
        r = '%d * %d = %d' % (n, n, n * n)
        time.sleep(1)
        result.put(r)
    # except:
    #     print('task queue is empty.')
print('exit worker!')