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python 多线程处理实验

时间:2016-10-23 12:14:20      阅读:266      评论:0      收藏:0      [点我收藏+]

标签:主线程   imp   timediff   import   append   比较   div   threading   清除   

最近要做个东西,没优化之前。跑一次要11个小时。跑的时候看cpu,内存都有富裕,就考虑用python 多线程来做。

多线程要是能省时间,也是省在等待IO 的时候,让机器做点其他的事。否则如果只是计算循环1+1=2 ,用多线程也不会提高效率,因为cpu很忙。每起一个线程,就会占一块内存,线程也不能起多了,起多了,分不到CPU时间,也没有那么多内存。

 

多线程实验如下:

1. 用循环来做。主线程循环50次,每循环一次,执行一次处理数据计算,休息5秒(模拟读取文件)

2. 启线程来做。做个线程列表,每循环一次,就新起一个线程,存到列表。列表存满5个或3个时,就等着。检查是否有完成的线程,如果有就清除出列表。

最后比较1与2用的时间差

实验1的代码

import threading
import time


# Define a function for the thread
def print_time(name,delay):
    #print "%s worker started\n"%name
    for i in range(1,10000):
        for j in range(1,1000):
            data = i*j
        
    #print "%swork finshed\n"%name
    return
    
count =0
startTime = time.time()
while count <30:
    count +=1
    print "current record :",count
    print_time("hello",1)
    time.sleep(5)
    

endTime = time.time()

timeDiff = endTime-startTime
print "all work is done cost:",timeDiff

实验1 执行时间约178秒

实验2:启线程的方式

 1 import threading
 2 import time
 3 
 4 
 5 # Define a function for the thread
 6 def print_time(name,delay):
 7     #print "%s worker started\n"%name
 8     for i in range(1,10000):
 9         for j in range(1,1000):
10             data = i*j
11      
12     #print "%swork finshed\n"%name
13     return
14     
15     
16 
17 class myThread(threading.Thread):
18     def __init__(self,threadID,name,counter):
19         threading.Thread.__init__(self)
20         self.threadID = threadID
21         self.name = name
22         self.counter = counter
23     def run(self):
24         print "Starting %s\n"%self.name
25         print_time(self.name,self.counter)
26         print "Exiting %s\n"%self.name
27 
28 """
29 threadLock = threading.Lock()
30 threads = []
31 thread1 = myThread(1,"Thread-1",2)
32 thread2 = myThread(2,"Thread-2",2)
33 thread1.start()
34 thread2.start()
35 threads.append(thread1)
36 threads.append(thread2)
37 for t in threads:
38     t.join()
39 print "Exiting Main Thread"
40 """
41 
42 def readfile():
43     print "read file...."
44     time.sleep(5)
45     
46 threadLock = threading.Lock()
47 threads = []
48 count =0
49 startTime = time.time()
50 while count <30:
51     print "current record :",count
52     name="Thread"+str(count)
53     thread = myThread(count,name,2)
54     if len(threads) <5:
55         thread.start()
56         threads.append(thread)
57         count +=1
58         readfile()
59         
60         #thread.join()
61     if len(threads)>=5:
62         for t in threads:
63             if not t.isAlive():
64                 print t.name,"need remove"
65                 threads.remove(t)
66     
67 
68 endTime = time.time()
69 
70 timeDiff = endTime-startTime
71 print "all work is done cost:",timeDiff

实验2跑完后,大概用了151秒,基本上计算利用了主线程休息的时间。

如果主线程没有sleep ,只是count+=1 ,那么用多线程反而跑的更慢。

 

python 多线程处理实验

标签:主线程   imp   timediff   import   append   比较   div   threading   清除   

原文地址:http://www.cnblogs.com/xna40/p/5989101.html

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