本文實例講述了Python多進程機制。分享給大家供大家參考。具體如下:
在以前只是接觸過PYTHON的多線程機制,今天搜了一下多進程,相關文章好像不是特別多??戳藥灼≡嚵艘话选3绦蛉缦?,主要內容就是通過PRODUCER讀一個本地文件,一行一行的放到隊列中去。然后會有相應的WORKER從隊列中取出這些行。
import multiprocessingimport osimport sysimport Queueimport timedef 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 retdef producer(q): time.sleep(5) #讓進行休息幾秒 方便ps命令看到相關內容 pid = os.getpid() handle_file = '/home/dwapp/joe.wangh/test/multiprocess/datafile' with open(handle_file,'r') as f: #with...as... 這個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) #讓進行休息幾秒 方便ps命令看到相關內容 pid = os.getpid() empty_count = 0 while True: try: task = readQ(q) print "worker <" , pid , "> is doing: " ,task ''' 如果這里不休眠的話 一般情況下所有行都會被同一個子進程讀取到 為了使實驗效果更加清楚 在這里讓每個進程讀取完一行內容時候休眠5s 這樣就可以讓其他的進程到隊列中進行讀取 ''' 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()
實驗結果如下:
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 startproducer < 28320 > is doing: line 1put size: 1producer < 28320 > is doing: line 2put size: 2producer < 28320 > is doing: line 3put size: 3producer < 28320 > is doing: line 4put size: 3producer < 28320 > is doing: line 5get size: 3put size: 4worker < 28321 > is doing: line 1get size: 3worker < 28322 > is doing: line 2get size: 2worker < 28323 > is doing: line 3get size: 1worker < 28321 > is doing: line 4get size: 0worker < 28322 > is doing: line 5queue is empty, quitqueue is empty, quitqueue is empty, quitall DONE
程序運行期間在另外一個窗口進行ps命令 可以觀測到一些進程的信息
dwapp@pttest1:/home/dwapp/joe.wangh/test/multiprocess>ps -ef | grep pythondwapp 13735 11830 0 Nov20 pts/12 00:00:05 pythondwapp 28319 27481 8 14:04 pts/0 00:00:00 python 1.pydwapp 28320 28319 0 14:04 pts/0 00:00:00 python 1.pydwapp 28321 28319 0 14:04 pts/0 00:00:00 python 1.pydwapp 28322 28319 0 14:04 pts/0 00:00:00 python 1.pydwapp 28323 28319 0 14:04 pts/0 00:00:00 python 1.pydwapp 28325 27849 0 14:04 pts/13 00:00:00 grep pythondwapp@pttest1:/home/dwapp/joe.wangh/test/multiprocess>ps -ef | grep pythondwapp 13735 11830 0 Nov20 pts/12 00:00:05 python #此時28320進程 也就是PRODUCER進程已經結束dwapp 28319 27481 1 14:04 pts/0 00:00:00 python 1.pydwapp 28321 28319 0 14:04 pts/0 00:00:00 python 1.pydwapp 28322 28319 0 14:04 pts/0 00:00:00 python 1.pydwapp 28323 28319 0 14:04 pts/0 00:00:00 python 1.pydwapp 28328 27849 0 14:04 pts/13 00:00:00 grep pythondwapp@pttest1:/home/dwapp/joe.wangh/test/multiprocess>ps -ef | grep pythondwapp 13735 11830 0 Nov20 pts/12 00:00:05 pythondwapp 28319 27481 0 14:04 pts/0 00:00:00 python 1.pydwapp 28321 28319 0 14:04 pts/0 00:00:00 python 1.pydwapp 28322 28319 0 14:04 pts/0 00:00:00 python 1.pydwapp 28323 28319 0 14:04 pts/0 00:00:00 [python] <defunct> #這里應該是代表28323進程(WORKER)已經運行結束了dwapp 28331 27849 0 14:04 pts/13 00:00:00 grep pythondwapp@pttest1:/home/dwapp/joe.wangh/test/multiprocess>ps -ef | grep pythondwapp 13735 11830 0 Nov20 pts/12 00:00:05 pythondwapp 28337 27849 0 14:05 pts/13 00:00:00 grep python
希望本文所述對大家的Python程序設計有所幫助。
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