思路：利用ruquest发送请求，利用多线程模拟并发
下面直接上代码：
#!/user/bin/env python #coding=utf-8 import requests import datetime import time import threading class url_request(): times = [] error = [] def req(self,AppID,url): myreq=url_request() headers = {'User-Agent' : 'Mozilla/5.0 (Linux; Android 4.2.1; en-us; Nexus 4 Build/JOP40D) AppleWebKit/535.19 (KHTML, like Gecko) Chrome/18.0.1025.166 Mobile Safari/535.19'} payload = {'AppID':AppID,'CurrentURL':url} r = requests.post("http://xx.xxx.com/WeiXinJSAccessToken/json/WeChatJSTicket",headers=headers,data=payload) ResponseTime=float(r.elapsed.microseconds)/1000 #获取响应时间，单位ms myreq.times.append(ResponseTime) #将响应时间写入数组 if r.status_code !=200 : myreq.error.append("0") if __name__=='__main__': myreq=url_request() threads = [] starttime = datetime.datetime.now() print "request start time %s" %starttime nub = 50#设置并发线程数 ThinkTime = 0.5#设置思考时间 for i in range(1, nub+1): t = threading.Thread(target=myreq.req, args=('12','http://m.ctrip.com/webapp/cpage/#mypoints')) threads.append(t) for t in threads: time.sleep(ThinkTime) #print "thread %s" %t #打印线程 t.setDaemon(True) t.start() t.join() endtime = datetime.datetime.now() print "request end time %s" %endtime time.sleep(3) AverageTime = "{:.3f}".format(float(sum(myreq.times))/float(len(myreq.times))) #计算数组的平均值，保留3位小数 print "Average Response Time %s ms" %AverageTime #打印平均响应时间 usetime = str(endtime - starttime) hour = usetime.split(':').pop(0) minute = usetime.split(':').pop(1) second = usetime.split(':').pop(2) totaltime = float(hour)*60*60 + float(minute)*60 + float(second) #计算总的思考时间+请求时间 print "Concurrent processing %s" %nub #打印并发数 print "use total time %s s" %(totaltime-float(nub*ThinkTime)) #打印总共消耗的时间 print "fail request %s" %myreq.error.count("0") #打印错误请求数 request start time 2015-02-10 18:24:14.316000 request end time 2015-02-10 18:24:39.769000 Average Response Time 46.700 ms Concurrent processing 50 use total time 25.453 s fail request 1 |
还可以据此计算tps，也可以控制并发量循环找出符合响应时间要求的最大并发量，等等
