標籤:
思路:利用ruquest發送請求,利用多線程類比並發
下面直接上代碼:
#!/user/bin/env python#coding=utf-8import requestsimport datetimeimport timeimport threadingclass 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 #擷取回應時間,單位ms myreq.times.append(ResponseTime) #將回應時間寫入數組 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 = 51#設定並發線程數 for i in range(1, nub): t = threading.Thread(target=myreq.req, args=(‘12‘,‘http://m.ctrip.com/webapp/cpage/#mypoints‘)) threads.append(t) for t in threads: time.sleep(0.5) #設定考慮時間 #print "thread %s" %t #列印線程 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))) #計算數組的平均值,保留3位小數 print "Average Response Time %s ms" %AverageTime #列印平均回應時間 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) #計算總的考慮時間+請求時間 print "Concurrent processing %s" %(nub-1) #列印並發數 print "use total time %s s" %(totaltime-(nub-1)*0.5) #列印總共消耗的時間 print "fail request %s" %myreq.error.count("0") #列印錯誤請求數
request start time 2015-02-10 18:24:14.316000request end time 2015-02-10 18:24:39.769000Average Response Time 46.700 msConcurrent processing 50use total time 25.453 s
fail request 1
還可以據此計算tps,也可以控制並發量迴圈找出符合回應時間要求的最大並發量,等等
使用python做簡單的介面效能測試