使用Python中的curl对网站进行压力测试

Question

I have a Flask application running on port 5000 that supports 7 different endpoints that support GET requests. So I can do a

curl http://localhost:5000/get_species_interactions?q=tiger

And it returns a page after some computation. There are 6 other such endpoints each with varying degrees of computation at the back end. It works fine with one user but I want to get metrics for how well it can perform under load. I am trying to stress test this by simulating a large number of requests and I was thinking of using a python script. The rough algorithm I had in mind is the following:

 while (num_tests < 1000):
   e = get_random_end_point_to_test() # pick one out of 7 end points
   d = get_random_data_for_get(e) # pick relevant random data to send in curl command
   resp = curl(e/q?d)
   num_tests++

My question is - is this general approach on the right track? Does it simulate a large number of simultaneous users? I was planning to store the amount of time it took to execute each request and compute stats. Otherwise is there a free utility I can use to do this kind of stress test on Mac OS? I saw a tool called siege but its not available on mac easily.

Answer 1

I would suggest Apache jmeter. The tool has everything you need for Stresstests and is good documented online.

You'll need to install Java though

Answer 2

No, you need to parallelize your requests. The libcurl can do this using the multi interface.

Check this out. Pythonic interface to libcurl/pycurl .