python 使用多线程进行压力测试

#coding=utf-8

import urllib2

import threading

import time

 

TOTAL = 0 #总数  

SUCC = 0 #响应成功数  

FAIL = 0 #响应失败数  

EXCEPT = 0 #响应异常数  

MAXTIME=0 #最大响应时间  

MINTIME=100 #最小响应时间，初始值为100秒

# 子类化Thread

class Mythread(threading.Thread):

    def __init__(self, func, args, name=''):

        threading.Thread.__init__(self)

        self.name = name

        self.func = func

        self.args = args

    

    def getResult(self):

        return self.res

    

    def run(self):

        self.res = apply(self.func, self.args)

 

def request_url(url, r):

    global TOTAL  

    global SUCC  

    global FAIL  

    global EXCEPT

    try:

        st = time.time()

        res = urllib2.urlopen(url)

        status = res.getcode()

        if status == 200:

            TOTAL+=1  

            SUCC+=1  

        else:

            TOTAL+=1  

            FAIL+=1

        time_span = time.time()-st 

        maxtime(time_span)

        self.mintime(time_span) 

    except Exception, e:

        TOTAL+=1  

        EXCEPT+=1

 

def maxtime(ts):  

    global MAXTIME  

    if ts>MAXTIME:  

        MAXTIME=ts  

def mintime(ts):  

    global MINTIME  

    if ts<MINTIME:  

         MINTIME=ts

    

 

def main():

    print '===========task start==========='  

    # 开始的时间  

    start_time = time.time()  

    # 并发的线程数  

    thread_count = 100

    i = 0  

    while i <= thread_count:  

        t = Mythread(request_url, ("http://www.baidu.com", "x"))

        t.start()

        i += 1

    t=0  

    #并发数所有都完成或大于20秒就结束  

    while TOTAL<thread_count|t>2:  

        print "total:%d,succ:%d,fail:%d,except:%d\n"%(TOTAL,SUCC,FAIL,EXCEPT)  

        t+=1  

        time.sleep(1)

 

    print '===========task end==========='  

    print "total:%d,succ:%d,fail:%d,except:%d"%(TOTAL,SUCC,FAIL,EXCEPT)  

    print 'response maxtime:',MAXTIME  

    print 'response mintime',MINTIME

    s = raw_input("Press any key")

    print "bay!"

    pass

 

if __name__ == "__main__":

    main()

 

文章内容来源：

http://www.runoob.com/python/python-multithreading.html