python 进程间通信Queue/Pipe（42）

一.前言

1.在前一篇文章 python进程Process与线程threading区别 中讲到线程threading共享内存地址，进程与进程Peocess之间相互独立，互不影响（相当于深拷贝）；

2.在线程间通信的时候可以使用Queue模块完成，进程间通信也可以通过Queue完成，但是此Queue并非线程的Queue，进程间通信Queue是将数据 pickle 后传给另一个进程的 Queue，用于父进程与子进程之间的通信或同一父进程的子进程之间通信；

 

使用Queue线程间通信：

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#导入线程相关模块 import threading import queue     q = queue.Queue()

 

使用Queue进程间通信，适用于多个进程之间通信：

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# 导入进程相关模块 from multiprocessing import Process from multiprocessing import Queue   q = Queue()

 

使用Pipe进程间通信，适用于两个进程之间通信（一对一）：

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# 导入进程相关模块 from multiprocessing import Process from multiprocessing import Pipe   pipe = Pipe()

 

 

二.python进程间通信Queue/Pipe使用

python提供了多种进程通信的方式，主要Queue和Pipe这两种方式，Queue用于多个进程间实现通信，Pipe用于两个进程的通信；

1.使用Queue进程间通信，Queue包含两个方法：

• put()：以插入数据到队列中，他还有两个可选参数：blocked和timeout。详情自行百度

• get()：从队列读取并且删除一个元素。同样，他还有两个可选参数：blocked和timeout。详情自行百度

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# !usr/bin/env python # -*- coding:utf-8 _*- """ @Author:何以解忧 @Blog(个人博客地址): shuopython.com @WeChat Official Account(微信公众号)：猿说python @Github:www.github.com   @File:python_process_queue.py @Time:2019/12/21 21:25   @Motto:不积跬步无以至千里，不积小流无以成江海，程序人生的精彩需要坚持不懈地积累！ """   from multiprocessing import Process from multiprocessing import Queue import os,time,random   #写数据进程执行的代码 def proc_write(q,urls):     print ('Process is write....')     for url in urls:         q.put(url)         print ('put %s to queue... ' %url)         time.sleep(random.random())   #读数据进程的代码 def proc_read(q):     print('Process is reading...')     while True:         url = q.get(True)         print('Get %s from queue' %url)   if __name__ == '__main__':     #父进程创建Queue，并传给各个子进程     q = Queue()     proc_write1 = Process(target=proc_write,args=(q,['url_1','url_2','url_3']))     proc_write2 = Process(target=proc_write,args=(q,['url_4','url_5','url_6']))     proc_reader = Process(target=proc_read,args=(q,))     #启动子进程，写入     proc_write1.start()     proc_write2.start()       proc_reader.start()     #等待proc_write1结束     proc_write1.join()     proc_write2.join()     #proc_raader进程是死循环，强制结束     proc_reader.terminate()     print("mian")

输出结果：

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Process is write.... put url_1 to queue... Process is write.... put url_4 to queue... Process is reading... Get url_1 from queue Get url_4 from queue put url_5 to queue... Get url_5 from queue put url_2 to queue... Get url_2 from queue put url_3 to queue... Get url_3 from queue put url_6 to queue... Get url_6 from queue mian

 

2.使用Pipe进程间通信

Pipe常用于两个进程，两个进程分别位于管道的两端 * Pipe方法返回（conn1,conn2）代表一个管道的两个端，Pipe方法有duplex参数，默认为True，即全双工模式，若为FALSE，conn1只负责接收信息，conn2负责发送,Pipe同样也包含两个方法：

send() : 发送信息;

recv() : 接收信息;

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from multiprocessing import Process from multiprocessing import Pipe import os,time,random #写数据进程执行的代码 def proc_send(pipe,urls):     #print 'Process is write....'     for url in urls:           print ('Process is send :%s' %url)         pipe.send(url)         time.sleep(random.random())   #读数据进程的代码 def proc_recv(pipe):     while True:         print('Process rev:%s' %pipe.recv())         time.sleep(random.random())   if __name__ == '__main__':     #父进程创建pipe，并传给各个子进程     pipe = Pipe()     p1 = Process(target=proc_send,args=(pipe[0],['url_'+str(i) for i in range(10) ]))     p2 = Process(target=proc_recv,args=(pipe[1],))     #启动子进程，写入     p1.start()     p2.start()       p1.join()     p2.terminate()     print("mian")

输出结果：

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Process is send :url_0 Process rev:url_0 Process is send :url_1 Process rev:url_1 Process is send :url_2 Process rev:url_2 Process is send :url_3 Process rev:url_3 Process is send :url_4 Process rev:url_4 Process is send :url_5 Process is send :url_6 Process is send :url_7 Process rev:url_5 Process is send :url_8 Process is send :url_9 Process rev:url_6 mian

 

三.测试queue.Queue来完成进程间通信能否成功？

当然我们也可以尝试使用线程threading的Queue是否能完成线程间通信，示例代码如下：

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from multiprocessing import Process # from multiprocessing import Queue     # 进程间通信Queue，两者不要混淆 import queue                            # 线程间通信queue.Queue，两者不要混淆 import time   def p_put(q,*args):     q.put(args)     print('Has put %s' % args)     def p_get(q,*args):     print('%s wait to get...' % args)       print(q.get())     print('%s got it' % args)         if __name__ == "__main__":     q = queue.Queue()     p1 = Process(target=p_put, args=(q,'p1', ))     p2 = Process(target=p_get, args=(q,'p2', ))     p1.start()     p2.start()

直接异常报错：

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Traceback (most recent call last):   File "E:/Project/python_project/untitled10/123.py", line 38, in <module>     p1.start()   File "G:\ProgramData\Anaconda3\lib\multiprocessing\process.py", line 105, in start     self._popen = self._Popen(self)   File "G:\ProgramData\Anaconda3\lib\multiprocessing\context.py", line 223, in _Popen     return _default_context.get_context().Process._Popen(process_obj)   File "G:\ProgramData\Anaconda3\lib\multiprocessing\context.py", line 322, in _Popen     return Popen(process_obj)   File "G:\ProgramData\Anaconda3\lib\multiprocessing\popen_spawn_win32.py", line 65, in __init__     reduction.dump(process_obj, to_child)   File "G:\ProgramData\Anaconda3\lib\multiprocessing\reduction.py", line 60, in dump     ForkingPickler(file, protocol).dump(obj) TypeError: can't pickle _thread.lock objects

 

 

 

 

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