Python 分布式进程Master

Posted 2020-09-14

#!/usr/bin/env python

# -*- coding:utf-8 -*-

# author: Changhua Gong

import random, time, queue

from multiprocessing.managers import BaseManager

from multiprocessing import freeze_support

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master进程：调度进程，作用分配任务和接收结果

这部分内容与官网教程，有些出入

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# 发送任务的对列

queue_t = queue.Queue()

# 接收结果的对列

queue_rs = queue.Queue()

# 从BaseManager继承QueueManager

class QueueManager(BaseManager):

    pass

def return_queue_t():

    global queue_t

    return queue_t

def return_queue_r():

    global queue_rs

    return queue_rs

def master():

    # 把两个Queue都注册到网络上, callable参数关联了Queue对象:

    QueueManager.register("get_queue_t", callable=return_queue_t)

    QueueManager.register("get_queue_rs", callable=return_queue_r)

    # 绑定端口5000, 设置验证码love8013

    manager = QueueManager(address=("127.0.0.1", 5000), authkey=b"love8013")

    # 启动Queue

    manager.start()

    # 获得通过网络访问的Queue对象

    t = manager.get_queue_t()

    rs = manager.get_queue_rs()

    # 放几个任务进去，计算每个数的4次方

    for i in range(10):

        n = random.randint(0, 10000)

        print("Put %d into the task queue." % n)

        t.put(n)  # 把每个数放进任务队列中，放在队列中的是int

    # 从result队列读取结果

    print("Try to get results.")

    for i in range(10):

        r = rs.get(timeout=10)

        print("Result: %s" % r)

    # 关闭:

    manager.shutdown()

    print(‘master exit.‘)

if __name__ == "__main__":

    freeze_support()

    master()