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python 进程间通信Queue/Pipe(42)

发布时间:2020-09-02 15:30:37 来源:网络 阅读:376 作者:qq5d6f345f0205e 栏目:编程语言

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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转载请注明:猿说Python » python 进程间通信Queue

 


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