Date Tags python

Over the past year, my team has been making the transition from Flask to aiohttp. We're making this transition because of a lot of the situations where non-blocking I/O theoretically scales better:

  • large numbers of simultaneous connections
  • remote http requests with long response times

There is agreement that asyncio scales better memory-wise: a green thread in Python consumes less memory than a system thread.

However, performance for latency and load is a bit more contentious. The best way to find out is to run a practical experiment.

To find out, I forked py-frameworks-benchmark, and designed an experiment.

The Experiment

The conditions of the web application, and the work performed, are identical:

  • a route on a web server that: 1. returns the response as json 2. queries a
  • http request to an nginx server returning back html.
  • a wrk benchmark run, with 400 concurrent requests for 20 seconds
  • running under gunicorn, with two worker processes.
  • python3.6

The Variants

The variants are:

  • aiohttp
  • flask + meinheld
  • flask + gevent
  • flask + multithreading, varying from 10 to 1000.

Results

variant min p50 p99 p99.9 max mean duration requests
aiohttp 163.27 247.72 352.75 404.59 1414.08 257.59 20.10 30702
flask:gevent 85.02 945.17 6587.19 8177.32 8192.75 1207.66 20.08 7491
flask:meinheld 124.99 2526.55 6753.13 6857.55 6857.55 3036.93 20.10 190
flask:10 163.05 4419.11 4505.59 4659.46 4667.55 3880.05 20.05 1797
flask:20 110.23 2368.20 3140.01 3434.39 3476.06 2163.02 20.09 3364
flask:50 122.17 472.98 3978.68 8599.01 9845.94 541.13 20.10 4606
flask:100 118.26 499.16 4428.77 8714.60 9987.37 556.77 20.10 4555
flask:200 112.06 459.85 4493.61 8548.99 9683.27 527.02 20.10 4378
flask:400 121.63 526.72 3195.23 8069.06 9686.35 580.54 20.06 4336
flask:800 127.94 430.07 4503.95 8653.69 9722.19 514.47 20.09 4381
flask:1000 184.76 732.21 1919.72 5323.73 7364.60 786.26 20.04 4121

You can probably get a sense that aiohttp can server more requests than any other. To get a real sense of how threads scale we can put the request count on a chart:

The interesting note is that the meinheld worker didn't scale very well at all. Gevent handled requests faster than any threading implementation.

But nothing handled nearly as many requests as aiohttp.

These are the results on my machine. I'd strongly suggest you try the experiment for yourself: the code is available in my fork.

If anyone has any improvements on the multithreading side, or can explain the discrepency in performance, I'd love to understand more.


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About Yusuke Tsutsumi
I work at Zillow. I focus on tools and services for developer productivity, including build and testing.

My other interests include programming language design, game development, and learning languages (the non-programming ones).