# Contribution Guidelines

Thank you for your interest in contributing to the ML-Agents toolkit! We are incredibly
excited to see how members of our community will use and extend the ML-Agents toolkit.
To facilitate your contributions, we've outlined a brief set of guidelines
to ensure that your extensions can be easily integrated.

### Communication

First, please read through our [code of conduct](CODE_OF_CONDUCT.md), 
as we expect all our contributors to follow it.

Second, before starting on a project that you intend to contribute
to the ML-Agents toolkit (whether environments or modifications to the codebase), 
we **strongly** recommend posting on our 
[Issues page](https://github.com/Unity-Technologies/ml-agents/issues) and
briefly outlining the changes you plan to make. This will enable us to provide
some context that may be helpful for you. This could range from advice and 
feedback on how to optimally perform your changes or reasons for not doing it.

Lastly, if you're looking for input on what to contribute, feel free to
reach out to us directly at ml-agents@unity3d.com and/or browse the GitHub
issues with the `contributions welcome` label.

### Git Branches

Starting with v0.3, we adopted the 
[Gitflow Workflow](http://nvie.com/posts/a-successful-git-branching-model/).
Consequently, the `master` branch corresponds to the latest release of 
the project, while the `develop` branch corresponds to the most recent, stable,
version of the project.

Thus, when adding to the project, **please branch off `develop`**
and make sure that your Pull Request (PR) contains the following:
* Detailed description of the changes performed
* Corresponding changes to documentation, unit tests and sample environments 
(if applicable)
* Summary of the tests performed to validate your changes
* Issue numbers that the PR resolves (if any)

### Environments

We are also actively open to adding community contributed environments as 
examples, as long as they are small, simple, demonstrate a unique feature of 
the platform, and provide a unique non-trivial challenge to modern 
machine learning algorithms. Feel free to submit these environments with a
PR explaining the nature of the environment and task. 

### Style Guide

When performing changes to the codebase, ensure that you follow the style
guide of the file you're modifying. For Python, we follow 
[PEP 8](https://www.python.org/dev/peps/pep-0008/). For C#, we will soon be
adding a formal style guide for our repository.