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本文實例講述了Python多過程機制。分享給年夜家供年夜家參考。詳細以下：
在之前只是接觸過PYTHON的多線程機制，明天搜了一下多過程，相干文章似乎不是特殊多。看了幾篇，小試了一把。法式以下，重要內容就是經由過程PRODUCER讀一個當地文件，一行一行的放到隊列中去。然後會有響應的WORKER從隊列中掏出這些行。
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) #讓停止歇息幾秒 便利ps敕令看到相干內容
pid = os.getpid()
handle_file = '/home/dwapp/joe.wangh/test/multiprocess/datafile'
with open(handle_file,'r') as f: #with...as... 這個用法明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) #讓停止歇息幾秒 便利ps敕令看到相干內容
pid = os.getpid()
empty_count = 0
while True:
try:
task = readQ(q)
print "worker <" , pid , "> is doing: " ,task
'''
假如這裡不休眠的話 普通情形下一切行都邑被統一個子過程讀取到 為了使試驗後果加倍清晰 在這裡讓每一個過程讀取完
一行內容時刻休眠5s 如許便可以讓其他的過程到隊列中停止讀取
'''
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()
試驗成果以下：
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
法式運轉時代在別的一個窗口停止ps敕令 可以不雅測到一些過程的信息
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 #此時28320過程 也就是PRODUCER過程曾經停止 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> #這裡應當是代表28323過程（WORKER）曾經運轉停止了 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
願望本文所述對年夜家的Python法式設計有所贊助。
