网络编程之python zeromq学习系列之一

    简介:

      zeromq中间件,他是一个轻量级的消息中间件,传说是世界上最快的消息中间件,为什么这么说呢?
    因为一般的消息中间件都需要启动消息服务器,但是zeromq这厮尽然没有消息服务器,他压根没有消息中间件的架子,但是这并不能掩盖他的强大。
    通过和activemq,rabbitmq对比,显然功能上没有前两者这么强大,他不支持消息的持久化,但是有消息copy功能,他也不支持崩溃恢复,而且由于他太快了,可能客户端还没启动,服务端的消息就已经发出去了,这个就容易丢消息了,但是zeromq自由他的办法,就先说这么多了。先来看看怎么在python中引入这个强大的利器。
    我自己之所以,学习体会一下,主要原因,是想在练习过程中体会其中的应用原理及逻辑,最好是能感知到其中的设计思想,为以后,自己做东西积攒点经验.
    另外最近也比较关注自动化运维的一些东西.网上说saltstack本身就用的zeromq做消息队列.所以更引起了我的兴趣.
    安装:
    我的操作系统是ubuntu 14.04的 python zeromq 环境安装参考这里的官网

    下面测试:

    一,C/S模式:
    server 端代码:
        #!/usr/bin/env python
        # coding:utf8
        #author: wangqiankun@lashou-inc.com


        import zmq
        #调用zmq相关类方法,邦定端口
        context = zmq.Context()
        socket = context.socket(zmq.REP)
        socket.bind('tcp://*:10001')



        while True:
            #循环接受客户端发来的消息
            msg = socket.recv()
            print "Msg info:%s" %msg
            #向客户端服务器发端需要执行的命令
            cmd_info = raw_input("client cmd info:").strip()
            socket.send(cmd_info)

        socket.close()

    client 端代码:
      import zmq
        import time
        import commands

        context = zmq.Context()
        socket = context.socket(zmq.REQ)
        socket.connect('tcp://127.0.0.1:10001')


        def execut_cmd(cmd):
            s,v = commands.getstatusoutput(cmd)
            return v



        while True:
            #获取当前时间
            now_time = time.strftime("%Y-%m-%d %H:%M:%S",time.localtime())

            socket.send("now time info:[%s] request execution command:'
',%s"%(now_time,result))
            recov_msg = socket.recv()
            #调用execut_cmd函数,执行服务器发过来的命令
            result = execut_cmd(recov_msg)
            print recov_msg,'
',result,
            time.sleep(1)
            #print "now time info:%s cmd status:[%s],result:[%s]" %(now_time,s,v)
            continue

        socket.close()
      注意:此模式是经典的应答模式,不能同时send多个数据,
        这种模式说是主要用于远程调用和任务分配,但我愚笨,还是理解不透.后面有时间,再回过来好好看看,

        测试:
        req端
        # python zmq-server-cs-v01.py
        rep端
        # python  zmq-client-cs-v01.py
      
    二,发布订阅模式(pub/sub)

        pub 发布端代码如下:

        #!/usr/bin/env python
        # coding:utf8
        #author: wangqiankun@lashou-inc.com

        import itertools
        import sys,time,zmq


        def main():
            if len(sys.argv) != 2:
                print 'Usage: publisher'
                sys.exit(1)
            bind_to = sys.argv[1]
            all_topics = ['sports.general','sports.football','sports.basketball','stocks.general','stocks.GOOG','stocks.AAPL','weather']

            ctx = zmq.Context()
            s = ctx.socket(zmq.PUB)
            s.bind(bind_to)

            print "Starting broadcast on topics:"
            print "%s" %all_topics
            print "Hit Ctrl-c to stop broadcasting."
            print "waiting so subscriber sockets can connect...."

            print
            time.sleep(1)
            msg_counter = itertools.count()

            try:
                for topic in itertools.cycle(all_topics):
                msg_body = str(msg_counter.next())
                #print msg_body,
                print 'Topic:%s,msg:%s' %(topic,msg_body)
                s.send_multipart([topic,msg_body])
                #s.send_pyobj([topic,msg_body])
                time.sleep(0.1)
            except KeyboardInterrupt:

                pass


            print "Wating for message queues to flush"

            time.sleep(0.5)
            s.close()
            print "Done"

        if __name__ == "__main__":
        main()

        sub  端代码:

            #!/usr/bin/env python
            # coding:utf8
            #author: wangqiankun@lashou-inc.com

            import zmq
            import time,sys


            def main():

            if len(sys.argv) < 2:
                print "Usage: subscriber [topic topic]"
                sys.exit(1)

            connect_to = sys.argv[1]
            topics = sys.argv[2:]

            ctx = zmq.Context()
            s = ctx.socket(zmq.SUB)
            s.connect(connect_to)

            #manage subscriptions

            if not topics:
                print "Receiving messages on ALL topics...."
                s.setsockopt(zmq.SUBSCRIBE,'')
            else:
                print "Receiving messages on topics: %s..." %topics

                for t in topics:
                s.setsockopt(zmq.SUBSCRIBE,t)

                print
            try:
                while True:
                topics,msg = s.recv_multipart()
                print 'Topic:%s,msg:%s' %(topics,msg)
            except KeyboardInterrupt:
                pass
            print "Done...."


            if __name__ == "__main__":
            main()







     注意:
     这里的发布与订阅角色是绝对的,即发布者无法使用recv,订阅者不能使用send,官网还提供了一种可能出现的问题:当订阅者消费慢于发布,
     此时就会出现数据的堆积,而且还是在发布端的堆积(有朋友指出是堆积在消费端,或许是新版本改进,需要读者的尝试和反馈,thx!),显然,
     这是不可以被接受的。至于解决方案,或许后面的"分而治之"就是吧

     测试:
     pub端: 发布端 
     #python zmq-server-pubsub-v02.py  tcp://127.0.0.1:10001
     sub端:订阅端
     #python zmq-server-cs-v01.py  tcp://127.0.0.1:10001 sports.football
     
     三,push/pull 分而治之模式.
     
     任务发布端代码
     
     #!/usr/bin/env python
        # coding:utf8
        #author: wangqiankun@lashou-inc.com



        import zmq
        import random
        import time

        context = zmq.Context()
        #socket to send messages on
        sender = context.socket(zmq.PUSH)
        sender.bind('tcp://*:5557')


        print 'Press Enter when the workers are ready:'
        _ = raw_input()
        print "Sending tasks to workers...."

        #The first messages is "0" and signals start to batch

        sender.send('0')

        #Initialize random mumber generator

        random.seed()

        #send 100 tasks

        total_msec = 0
        for task_nbr in range(100):
            #Random workload from 1 to 100 msecs
            #print task_nbr,
            workload = random.randint(1,100)
            total_msec += workload
            sender.send(str(workload))
            print "Total expected cost:%s msec:%s workload:%s" %(total_msec,task_nbr,workload)



        work端代码如下:

        #!/usr/bin/env python
        # coding:utf8
        #author: wangqiankun@lashou-inc.com

        import sys,time,zmq
        import commands


        context = zmq.Context()
        #socket to receive messages on

        receiver = context.socket(zmq.PULL)
        receiver.connect('tcp://127.0.0.1:5557')

        #Socket to send messages to

        sender = context.socket(zmq.PUSH)
        sender.connect("tcp://127.0.0.1:5558")

        #Process tasks forever

        while True:
            s = receiver.recv()

            #Simple progress indicator for the viewer
            print s,
            sys.stdout.write("%s '	' "%s)
            sys.stdout.flush()

            #Do the work
            time.sleep(int(s)*0.001)
            #Send results to sink
            sender.send(s)

    pull端代码如下:
            #!/usr/bin/env python
            # coding:utf8
            #author: wangqiankun@lashou-inc.com

            import sys
            import time
            import zmq

            context = zmq.Context()

            #Socket to receive messages on

            receiver = context.socket(zmq.PULL)
            receiver.bind("tcp://*:5558")

            #Wait for start of batch

            s = receiver.recv()

            #Start our clock now
            tstart = time.time()

            #Process 100 confirmations
            total_msec = 0

            for task_nbr in range(100):
            s = receiver.recv()

            if task_nbr % 10 == 0:
                print task_nbr,
                print s,
                sys.stdout.write(':')

            else:
                print s,
                #print task_nbr,
                sys.stdout.write('.')

            #Calculate and report duration of batch
            tend = time.time()
            print "Total elapsed time:%d msec "%((tend-tstart)*1000)

    注意点:
    这种模式与pub/sub模式一样都是单向的,区别有两点:
    1,该模式下在没有消费者的情况下,发布者的信息是不会消耗的(由发布者进程维护)
    2,多个消费者消费的是同一列信息,假设A得到了一条信息,则B将不再得到
    这种模式主要针对在消费者能力不够的情况下,提供的多消费者并行消费解决方案(也算是之前的pub/sub模式的
    那个"堵塞问题"的一个解决策略吧)

    其实所谓的分就是pull端去抢push端发出来的任务.谁抢着算谁的.

    测试:
     #python zmq-server-pushpull-v03.py
     #python zmq-work-pushpull-v03.py
     #python zmq-client-pushpull-v03.py
     
原文地址:https://www.cnblogs.com/shantu/p/4598933.html