Python多进程机制实例详解


            本文实例讲述了Python多进程机制。分享给大家供大家参考。具体如下：

在以前只是接触过PYTHON的多线程机制，今天搜了一下多进程，相关文章好像不是特别多。看了几篇，小试了一把。程序如下，主要内容就是通过PRODUCER读一个本地文件，一行一行的放到队列中去。然后会有相应的WORKER从队列中取出这些行。







import multiprocessing

import os

import sys

import Queue

import time

def writeQ(q,obj):

    q.put(obj,True,None)

    print "put size: ",q.qsize()

def readQ(q):

    ret = q.get(True,1)

    print "get size: ",q.qsize()

    return ret

def producer(q):

    time.sleep(5)  #让进行休息几秒 方便ps命令看到相关内容

    pid = os.getpid()

    handle_file = '/home/dwapp/joe.wangh/test/multiprocess/datafile'

    with open(handle_file,'r') as f:   #with...as... 这个用法今天也是第一次看到的

        for line in f:

            print "producer <" ,pid , "> is doing: ",line

            writeQ(q,line.strip())

    q.close()

def worker(q):

    time.sleep(5)  #让进行休息几秒 方便ps命令看到相关内容

    pid = os.getpid()

    empty_count = 0

    while True:

        try:

            task = readQ(q)

            print "worker <" , pid , "> is doing: " ,task

            '''

            如果这里不休眠的话 一般情况下所有行都会被同一个子进程读取到 为了使实验效果更加清楚 在这里让每个进程读取完

一行内容时候休眠5s 这样就可以让其他的进程到队列中进行读取

            '''

            time.sleep(5)  

        except Queue.Empty:

            empty_count += 1

            if empty_count == 3:

                print "queue is empty, quit"

                q.close()

                sys.exit(0)

def main():

    concurrence = 3

    q = multiprocessing.Queue(10)

    funcs = [producer , worker]

    for i in range(concurrence-1):

        funcs.append(worker)

    for item in funcs:

        print str(item)

    nfuncs = range( len(funcs) )

    processes = []    

    for i in nfuncs:

        p = multiprocessing.Process(target=funcs[i] , args=(q,))

        processes.append(p)

    print "concurrence worker is : ",concurrence," working start"

    for i in nfuncs:

        processes[i].start()

    for i in nfuncs:

        processes[i].join()

    print "all DONE"

if __name__ == '__main__':

    main()





实验结果如下：





dwapp@pttest1:/home/dwapp/joe.wangh/test/multiprocess>python 1.py 

<function producer at 0xb7b9141c>

<function worker at 0xb7b91454>

<function worker at 0xb7b91454>

<function worker at 0xb7b91454>

concurrence worker is : 3 working start

producer < 28320 > is doing: line 1

put size: 1

producer < 28320 > is doing: line 2

put size: 2

producer < 28320 > is doing: line 3

put size: 3

producer < 28320 > is doing: line 4

put size: 3

producer < 28320 > is doing: line 5

get size: 3

put size: 4

worker < 28321 > is doing: line 1

get size: 3

worker < 28322 > is doing: line 2

get size: 2

worker < 28323 > is doing: line 3

get size: 1

worker < 28321 > is doing: line 4

get size: 0

worker < 28322 > is doing: line 5

queue is empty, quit

queue is empty, quit

queue is empty, quit

all DONE





程序运行期间在另外一个窗口进行ps命令 可以观测到一些进程的信息





dwapp@pttest1:/home/dwapp/joe.wangh/test/multiprocess>ps -ef | grep python

dwapp  13735 11830 0 Nov20 pts/12  00:00:05 python

dwapp  28319 27481 8 14:04 pts/0  00:00:00 python 1.py

dwapp  28320 28319 0 14:04 pts/0  00:00:00 python 1.py

dwapp  28321 28319 0 14:04 pts/0  00:00:00 python 1.py

dwapp  28322 28319 0 14:04 pts/0  00:00:00 python 1.py

dwapp  28323 28319 0 14:04 pts/0  00:00:00 python 1.py

dwapp  28325 27849 0 14:04 pts/13  00:00:00 grep python

dwapp@pttest1:/home/dwapp/joe.wangh/test/multiprocess>ps -ef | grep python

dwapp  13735 11830 0 Nov20 pts/12  00:00:05 python     #此时28320进程 也就是PRODUCER进程已经结束

dwapp  28319 27481 1 14:04 pts/0  00:00:00 python 1.py

dwapp  28321 28319 0 14:04 pts/0  00:00:00 python 1.py

dwapp  28322 28319 0 14:04 pts/0  00:00:00 python 1.py

dwapp  28323 28319 0 14:04 pts/0  00:00:00 python 1.py

dwapp  28328 27849 0 14:04 pts/13  00:00:00 grep python

dwapp@pttest1:/home/dwapp/joe.wangh/test/multiprocess>ps -ef | grep python

dwapp  13735 11830 0 Nov20 pts/12  00:00:05 python

dwapp  28319 27481 0 14:04 pts/0  00:00:00 python 1.py

dwapp  28321 28319 0 14:04 pts/0  00:00:00 python 1.py

dwapp  28322 28319 0 14:04 pts/0  00:00:00 python 1.py

dwapp  28323 28319 0 14:04 pts/0  00:00:00 [python] <defunct>  #这里应该是代表28323进程（WORKER）已经运行结束了

dwapp  28331 27849 0 14:04 pts/13  00:00:00 grep python

dwapp@pttest1:/home/dwapp/joe.wangh/test/multiprocess>ps -ef | grep python

dwapp  13735 11830 0 Nov20 pts/12  00:00:05 python

dwapp  28337 27849 0 14:05 pts/13  00:00:00 grep python



希望本文所述对大家的Python程序设计有所帮助。