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Merge pull request #243 from adaptive-intelligent-robotics/develop
Add Dominated Novelty Search
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.github/CONTRIBUTING.md

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# Contributing
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We'd love to accept your patches and contributions to this project. When contributing to the repository, please make sure to first discuss the changes you wish to make via a [github issue](https://github.com/adaptive-intelligent-robotics/QDax/issues).
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After the issue is discussed and the solution is determined, you will be invited to fork the repository and create a branch to implement the solution. Once ready to be merged, you can create a [Pull Request](https://github.com/adaptive-intelligent-robotics/QDax/pulls) on github and request to merge into the branch **develop**.
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When implementing your contribution, there are just a few guidelines you need to follow.
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## Installing Pre-commit hooks
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Pre-commits hooks have been configured for this project using the [pre-commit](https://pre-commit.com/) library:
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- [black](https://github.com/psf/black) python formatter
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- [flake8](https://flake8.pycqa.org/en/latest/) python linter
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- [isort](https://pypi.org/project/isort/) sorts imports
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- [nbstripout](https://github.com/kynan/nbstripout) strips outputs from notebooks
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- [mypy](https://github.com/pre-commit/mirrors-mypy) checks type hints
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To get them going on your side, make sure to have python installed, and run the following
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commands from the root directory of this repository:
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```bash
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pip install pre-commit
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pre-commit install
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```
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You can then run the pre-commit hooks on all files as follows:
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```bash
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pre-commit run --all-files
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```
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## Coding conventions
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Please respect the following conventions to contribute to the code:
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- Use hard wrap at 88
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- Respect black, isort and flake8 conventions
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- Classes' names are Caml case (example: MyClass)
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- Functions and variables are in lower case with _ as separator (example: my_function, my_var)
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- Names are explicit: avoid mathematical notations, functions' names start with a verb
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- Use python typing library: each class and method should be typed (both for inputs and outputs)
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- Create custom types if needed
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- All classes and functions should have a docstring
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- Avoid repeating arguments and returns in docstring (should be explicit with the types) except when it is truly necessary
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- A function (or a class) does not take more than 5 arguments, if you need more create a data class
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- Avoid dictionaries to pass arguments when possible and prefer dataclasses instead
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- Repeat inputs names when calling a function: ex: compute_custom(arg1=arg1, arg2=my_arg2)
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- Use list comprehension when it is possible
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- Use f strings to add variables in strings: ex: print(f'my var value is {my_var}')
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## Commit messages
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Please try to follow the conventional [commit standard](https://www.conventionalcommits.org/en/v1.0.0/).
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## Merge request and code reviews
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All submissions, including submissions by project members, require review. We
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use GitHub pull requests for this purpose. Consult
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[GitHub Help](https://help.github.com/articles/about-pull-requests/) for more
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information on using pull requests.
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## Community Guidelines
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This project follows
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[Google's Open Source Community Guidelines](https://opensource.google.com/conduct/).

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