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大并发量，等等