Locust is an easy-to-use, distributed, user load testing tool. Intended for load testing web sites (or other systems) and figuring out how many concurrent users a system can handle.
The idea is that during a test, a swarm of locusts will attack your website. The behavior of each locust (or test user if you will) is defined by you and the swarming process is monitored from a web UI in real-time. This will help you battle test and identify bottlenecks in your code before letting real users in.
Locust is completely event based, and therefore it’s possible to support thousands of concurrent users on a single machine. In contrast to many other event-based apps it doesn’t use callbacks. Instead it uses light-weight processes, through gevent. Each locust swarming your site is actually running inside it’s own process (or greenlet, to be correct). This allows you to write very expressive scenarios in Python without complicating your code with callbacks.
No need for clunky UIs or bloated XML, just code as you normally would. Based on coroutines instead of callbacks (aka boomerang code) allows code to look and behave like normal, blocking Python code.
Locust supports running load tests distributed over multiple machines. Being event based, even one Locust node can handle thousands of users in a single process. Part of the reason behind this is that even if you simulate that many users, not all are actively hitting your system. Often, users are idle figuring out what to do next. Request per second != number of users online.
Locust has a neat HTML+JS user interface that shows relevent test details in real-time. And since the UI is web-based, it’s cross-platform and easily extendable.
Even though Locust is web-oriented, it can be used to test almost any system. Just write a client for what ever you wish to test and swarm it with locusts! It’s super easy!
Locust is small and very hackable and we intend to keep it that way. All heavy-lifting of evented I/O and coroutines are delegated to gevent. The brittleness of alternative testing tools was the reason we created Locust.
Locust was created because we were fed up with existing solutions. None of them are solving the right problem and to me, they are missing the point. We’ve tried both Apache JMeter and Tsung. Both tools are quite ok to use, we’ve used the former many times benchmarking stuff at work. JMeter comes with UI which you might think for second is a good thing. But you soon realize it’s a PITA to “code” your testing scenarios through some point-and-click interface. Secondly, JMeter is thread-bound. This means for every user you want to simulate, you need a separate thread. Needless to say, benchmarking thousands of users on a single machine just isn’t feasible.
Tsung, on the other hand, does not have these thread issues as it’s written in Erlang. It can make use of the light-weight processes offered by BEAM itself and happily scale up. But when it comes to defining the test scenarios, Tsung is as limited as JMeter. It offers an XML-based DSL to define how a user should behave when testing. I guess you can imagine the horror of “coding” this. Displaying any sorts of graphs or reports when completed requires you post-process the log files generated from the test. Only then can you get an understanding of how the test went.
Anyway, we’ve tried to address these issues when creating Locust. Hopefully none of the above painpoints should exist.
I guess you could say we’re really just trying to scratch our own itch here. We hope others will find it as useful as we do.
Open source licensed under the MIT license (see LICENSE file for details).