分布式进程--错误解决

廖雪峰Python教程–分布式进程

PicklingError：不能pickle <函数在0x02747DB0>：没有找到main 。

解决链接

task_master.py

#!/usr/bin/env python3# -*- coding: utf-8 -*-import random, time, queuefrom multiprocessing import freeze_supportfrom multiprocessing.managers import BaseManager# 发送任务的队列:task_queue = queue.Queue()# 接收结果的队列:result_queue = queue.Queue()# 从BaseManager继承的QueueManager:class QueueManager(BaseManager):    passdef return_task_queue():    global task_queue    return task_queuedef return_result_queue():    global result_queue    return result_queuedef test():    # 把两个Queue都注册到网络上, callable参数关联了Queue对象:    # QueueManager.register('get_task_queue', callable=lambda: task_queue)    # QueueManager.register('get_result_queue', callable=lambda: result_queue)    QueueManager.register('get_task_queue', callable=return_task_queue)    QueueManager.register('get_result_queue', callable=return_result_queue)    # 绑定端口5000, 设置验证码'abc':    manager = QueueManager(address=('127.0.0.1', 5000), authkey=b'abc')    # 启动Queue:    manager.start()    # 获得通过网络访问的Queue对象:    task = manager.get_task_queue()    result = manager.get_result_queue()    # 放几个任务进去:    for i in range(10):        n = random.randint(0, 10000)        print('Put task %d...' % n)        task.put(n)    # 从result队列读取结果:    print('Try get results...')    for i in range(10):        r = result.get(timeout=10)        print('Result: %s' % r)    # 关闭:    manager.shutdown()    print('master exit.')if __name__ == '__main__':    freeze_support()    test()

task_worker.py

#!/usr/bin/env python3# -*- coding: utf-8 -*-import time, sys, queuefrom multiprocessing.managers import BaseManager# 创建类似的QueueManager:class QueueManager(BaseManager):    pass# 由于这个QueueManager只从网络上获取Queue，所以注册时只提供名字:QueueManager.register('get_task_queue')QueueManager.register('get_result_queue')# 连接到服务器，也就是运行task_master.py的机器:server_addr = '127.0.0.1'print('Connect to server %s...' % server_addr)# 端口和验证码注意保持与task_master.py设置的完全一致:m = QueueManager(address=(server_addr, 5000), authkey=b'abc')# 从网络连接:m.connect()# 获取Queue的对象:task = m.get_task_queue()result = m.get_result_queue()# 从task队列取任务,并把结果写入result队列:for i in range(10):    try:        n = task.get(timeout=1)        print('run task %d * %d...' % (n, n))        r = '%d * %d = %d' % (n, n, n*n)        time.sleep(1)        result.put(r)    except Queue.Empty:        print('task queue is empty.')# 处理结束:print('worker exit.')

同时打开两个shell。
先运行task_master.py
然后运行task_worker.py。
（间隔时间长会出现Empty Queue）

C:\Users\K\Desktop\x>python task_master.pyPut task 8323...Put task 2381...Put task 3692...Put task 5614...Put task 8008...Put task 3851...Put task 8920...Put task 4314...Put task 5676...Put task 4413...Try get results...Result: 8323 * 8323 = 69272329Result: 2381 * 2381 = 5669161Result: 3692 * 3692 = 13630864Result: 5614 * 5614 = 31516996Result: 8008 * 8008 = 64128064Result: 3851 * 3851 = 14830201Result: 8920 * 8920 = 79566400Result: 4314 * 4314 = 18610596Result: 5676 * 5676 = 32216976Result: 4413 * 4413 = 19474569master exit.C:\Users\K\Desktop\x>

C:\Users\K\Desktop\x>python task_worker.pyConnect to server 127.0.0.1...run task 8323 * 8323...run task 2381 * 2381...run task 3692 * 3692...run task 5614 * 5614...run task 8008 * 8008...run task 3851 * 3851...run task 8920 * 8920...run task 4314 * 4314...run task 5676 * 5676...run task 4413 * 4413...worker exit.C:\Users\K\Desktop\x>