Contributions are really valuable to AgileRL, and we are grateful to the community for your support. We are happy to have you here!
In this guide you will get an overview of the contribution workflow from opening an issue, creating a PR, reviewing, and merging the PR.
If you have any questions, please raise them on our Discord.
When contributing to AgileRL, we ask that you:
-
Let us know what you plan in the GitHub Issue tracker so we can provide feedback.
-
Provide tests and documentation whenever possible. When fixing a bug, provide a failing test case that your patch solves.
-
Open a GitHub Pull Request with your patches and we will review your contribution and respond as quickly as possible. Keep in mind that this is an open source project, and it may take us some time to get back to you. Your patience is very much appreciated.
There are many ways to contribute, from writing tutorials or blog posts, improving the documentation, submitting bug reports and feature requests or writing code which can be incorporated into AgileRL itself.
All members of the AgileRL community are expected to follow the Code of Conduct.
AgileRL is nascent, and so there is a lot of scope to contribute on what you find interesting. You can have a big impact on the framework now and get involved in our exciting early development. Please feel free to suggest new, crazy ideas and have a go at the coolest RL implementations you can think of. We expect the GitHub Issue tracker to fill up with bugs, improvements and feature requests, so please take a look there too.
Some early suggestions for contributions we think would add value to AgileRL include adding more RL algorithms and evolvable network types, parallelising and benchmarking training, writing documentation, and general improvements to current implementations.
Contributing to an open source project for the first time? You can learn how from this great resource, https://www.firsttimersonly.com/.
If you've noticed a bug or have a feature request, make one! It's generally best if you get confirmation of your bug or approval for your feature request this way before starting to code.
For something that is bigger than a one or two line fix:
- Create your own fork of the code.
- Do the changes in your fork.
- Run the tests by running
pytest tests - Make the test pass.
- Commit your changes. Please use an appropriate commit prefix. If your pull request fixes an issue specify it in the commit message.
- Push to your fork and submit a pull request. Please provide us with some explanation of why you made the changes you made. For new features make sure to explain a standard use case to us.
Checks will be run automatically by the CI on code pushed to the AgileRL repository. These checks can also be run locally with the following steps:
- Install
pre-commit. - Install the Git hooks by running
pre-commit install.
Once these steps are done, the hooks will be run automatically at every new commit.
If you find a security vulnerability, do NOT open an issue. Email dev@agilerl.com instead.
When filing an issue, make sure to answer these five questions:
- What version of AgileRL are you using?
- What operating system and processor architecture are you using?
- What did you do?
- What did you expect to see?
- What did you see instead? General questions should go to the AgileRL Discord instead of the issue tracker.
The AgileRL philosophy is to provide streamlined tooling for reinforcement learning development, to make it easier and faster to create incredible models.
If you find yourself wishing for a feature that doesn't exist in AgileRL, you are probably not alone. There are bound to be others out there with similar needs. Many of the features that AgileRL has today have been added because our users saw the need. Open an issue on our issues list on GitHub which describes the feature you would like to see, why you need it, and how it should work.
You can chat with the core team on the AgileRL Discord. We try to respond as quickly as possible.