Python模块整理(五)：多进程mul

线程共享全局状态，进程完全独立。线程局限在一个处理器，线程可以发挥多个处理器的资源. 没有找到processing模块只找到multiprocessing #!/usr/bin/env python from multiprocessing import Process,Queue import time q=Queue() def f(q):         x=q.get()         print "Process number %s,sleeps for %s second" % (x,x)         time.sleep(x)         print "Process number %s finished" % x for i in range(10):         q.put(i)         i=Process(target=f,args=[q])         i.start() print "main process joins on queue" i.join() print "Main Program finished" 多进程ping扫描 #!/usr/bin/env python import subprocess import time import sys from multiprocessing import Process,Queue #multiprocessing 本身带有的Queue num_Process=50 queue=Queue() ips=['172.18.10.101','172.18.10.102','172.18.10.103','172.18.10.104','172.18.10.105'] def pinger(i,q):         while True:                 if q.empty(): #增加：Process增加了查看列队是否为空                         sys.exit()                 ip=q.get() #一样：取得队列内容threading和multiprocessing.Process一样，获取put过来的ip                 print "Process Numer: %s" % i                 ret=subprocess.call("ping -c 1 %s" % ip,shell=True,stdout=open('/dev/null','w'),stderr=subprocess.STDOUT)                 if ret==0:                         print "Process Numer %s ping:%s is alive" % (i,ip)                 else:                         print "Process Numer: %s did not find a response for %s" % (i,ip)                 #减少：没有threading的queue.task_done() for ip in ips:         queue.put(ip)  #一样：放入队列内容threading.Thread和multiprocessing.Process一样 #顺序很重要，需要先put ip for i in range(num_Process):         worker=Process(target=pinger,args=[i,queue]) #减少：没有threading.Thread的worker.setDaemon(True)         worker.start() print "Main joins on queue" worker.join() #变化：由threading.Thread队列queue的join方法变成了multiprocessing.Process实例的join方法 print "Done" multiprocessing.Process和threading.Thread比较 multiprocessing.Process没有的 queue.task_done()  worker.setDaemon(True)    两者都有的 queue.put(ip) queue.get() 有方法但变化了的 queue.join() 变成了 worker.join()#队列的连接变成进行实例的连接 multiprocessing.Process增加了的(threading.Thread没有的) queue.empty():