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  • python多进程并发

    由于Python下调用Linux的Shell命令都需要等待返回,所以常常我们设置的多线程都达不到效果,
    因此在调用shell命令不需要返回时,使用threading模块并不是最好的方法。
       http://www.coder4.com/archives/3352

    Python提供了非常好用的多进程包multiprocessing,你只需要定义一个函数,Python会替你完成其他所有事情。
    借助这个包,可以轻松完成从单进程到并发执行的转换。

    1、新建单一进程
    如果我们新建少量进程,可以如下:
    import multiprocessing
    import time
    
    def func(msg):
        for i in xrange(3):
            print msg
            time.sleep(1)
    
    if __name__ == "__main__":
        p = multiprocessing.Process(target=func, args=("hello", ))
        p.start()
        p.join()
        print "Sub-process done."

    2、使用进程池
    是的,你没有看错,不是线程池。它可以让你跑满多核CPU,而且使用方法非常简单。
    注意要用apply_async,如果落下async,就变成阻塞版本了。

    processes=4是最多并发进程数量。

    import multiprocessing
    import time
    
    def func(msg):
        for i in xrange(3):
            print msg
            time.sleep(1)
    
    if __name__ == "__main__":
        pool = multiprocessing.Pool(processes=4)
        for i in xrange(10):
            msg = "hello %d" %(i)
            pool.apply_async(func, (msg, ))
        pool.close()
        pool.join()
        print "Sub-process(es) done."

    3、使用Pool,并需要关注结果

    更多的时候,我们不仅需要多进程执行,还需要关注每个进程的执行结果,如下:

    import multiprocessing
    import time
    
    def func(msg):
        for i in xrange(3):
            print msg
            time.sleep(1)
        return "done " + msg
    
    if __name__ == "__main__":
        pool = multiprocessing.Pool(processes=4)
        result = []
        for i in xrange(10):
            msg = "hello %d" %(i)
            result.append(pool.apply_async(func, (msg, )))
        pool.close()
        pool.join()
        for res in result:
            print res.get()
        print "Sub-process(es) done."

    根据网友评论中的反馈,在Windows下运行有可能崩溃(开启了一大堆新窗口、进程),可以通过如下调用来解决:

    multiprocessing.freeze_support()

    附录(自己的脚本):

    #!/usr/bin/python
    import threading
    import subprocess
    import datetime
    import multiprocessing
    
    def dd_test(round, th):
        test_file_arg = 'of=/zbkc/test_mds_crash/1m_%s_%s_{}' %(round, th)
        command = "seq 100 | xargs -i dd if=/dev/zero %s  bs=1M count=1"  %test_file_arg 
        print command
        subprocess.call(command,shell=True,stdout=open('/dev/null','w'),stderr=subprocess.STDOUT)
    
    
    def mds_stat(round):
        p = subprocess.Popen("zbkc mds stat", shell = True, stdout = subprocess.PIPE)
        out = p.stdout.readlines()
        if out[0].find('active') != -1:
            command = "echo '0205pm %s round mds status OK, %s' >> /round_record" %(round, datetime.datetime.now())
            command_2 = "time (ls /zbkc/test_mds_crash/) 2>>/round_record"
            command_3 = "ls /zbkc/test_mds_crash | wc -l >> /round_record"
            subprocess.call(command,shell=True)
            subprocess.call(command_2,shell=True)
            subprocess.call(command_3,shell=True)
            return 1
        else:
            command = "echo '0205 %s round mds status abnormal, %s, %s' >> /round_record" %(round, out[0], datetime.datetime.now())
            subprocess.call(command,shell=True)
            return 0
    
    
    #threads = []
    for round in range(1, 1600):
        pool = multiprocessing.Pool(processes = 10) #使用进程池
        for th in range(10):
    #        th_name = "thread-" + str(th)
    #        threads.append(th_name)   #添加线程到线程列表
    #        threading.Thread(target = dd_test, args = (round, th), name = th_name).start()  #创建多线程任务
            pool.apply_async(dd_test, (round, th))
        pool.close()
        pool.join()
        #等待线程完成
    #    for t in threads:
    #        t.join()    
    
        if mds_stat(round) == 0: 
            subprocess.call("zbkc -s",shell=True)
            break
    原文: http://blog.csdn.net/werm520/article/details/43730593
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  • 原文地址:https://www.cnblogs.com/garfieldcgf/p/8324852.html
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