locust

Write scalable load tests in plain Python 🚗💨

Description

Locust is an easy-to-use, distributed, user load testing tool. It is 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 its own process (or greenlet, to be correct). This allows you to write very expressive scenarios in Python without complicating your code with callbacks.

Code Quality Rank: L3

Programming language: Python

License: MIT License

Tags: Testing     GUI / Web Testing     Traffic Generation    

Latest version: v2.13.0

README

Locust

Locust is an easy to use, scriptable and scalable performance testing tool. You define the behaviour of your users in regular Python code, instead of being constrained by a UI or domain specific language that only pretends to be real code. This makes Locust infinitely expandable and very developer friendly.

To get started right away, head over to the documentation.

Features

Write user test scenarios in plain old Python

If you want your users to loop, perform some conditional behaviour or do some calculations, you just use the regular programming constructs provided by Python. Locust runs every user inside its own greenlet (a lightweight process/coroutine). This enables you to write your tests like normal (blocking) Python code instead of having to use callbacks or some other mechanism. Because your scenarios are “just python” you can use your regular IDE, and version control your tests as regular code (as opposed to some other tools that use XML or binary formats)

from locust import HttpUser, task, between

class QuickstartUser(HttpUser):
    wait_time = between(1, 2)

    def on_start(self):
        self.client.post("/login", json={"username":"foo", "password":"bar"})

    @task
    def hello_world(self):
        self.client.get("/hello")
        self.client.get("/world")

    @task(3)
    def view_item(self):
        for item_id in range(10):
            self.client.get(f"/item?id={item_id}", name="/item")

Distributed & Scalable - supports hundreds of thousands of users

Locust makes it easy to run load tests distributed over multiple machines. It is event-based (using gevent), which makes it possible for a single process to handle many thousands concurrent users. While there may be other tools that are capable of doing more requests per second on a given hardware, the low overhead of each Locust user makes it very suitable for testing highly concurrent workloads.

Web-based UI

Locust has a user friendly web interface that shows the progress of your test in real-time. You can even change the load while the test is running. It can also be run without the UI, making it easy to use for CI/CD testing.

Can test any system

Even though Locust primarily works with web sites/services, it can be used to test almost any system or protocol. Just write a client for what you want to test, or explore some created by the community.

Hackable

Locust's code base is intentionally kept small and doesn't solve everything out of the box. Instead, we try to make it easy to adapt to any situation you may come across, using regular Python code. If you want to send reporting data to that database & graphing system you like, wrap calls to a REST API to handle the particulars of your system or run a totally custom load pattern, there is nothing stopping you!

Links

• Website: locust.io
• Documentation: docs.locust.io
• Support/Questions: StackOverflow
• Code/issues: GitHub
• Chat/discussion: Slack signup

Authors

• Carl Bystr (@cgbystrom on Twitter)
• Jonatan Heyman (@jonatanheyman on Twitter)
• Joakim Hamrén (@Jahaaja on Twitter)
• Hugo Heyman (@hugoheyman on Twitter)
• Lars Holmberg

License

Open source licensed under the MIT license (see LICENSE file for details).