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CONTRIBUTING.md

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Contributing code

Note: This document is based on the contribution guidelines for scikit-learn.

How to contribute

The preferred way to contribute to SKLL is to fork the main repository on GitHub:

(NOTE: Contributors internal to ETS can skip step 1 and clone the SKLL repository directly.)

  1. Read the part of the documentation that provides an overview of the SKLL codebase, run the tutorial and examples, and get familiar with the SKLL outputs.

  2. Fork the project repository: click on the 'Fork' button near the top of the page. This creates a copy of the code under your account on the GitHub server.

  3. Clone this copy to your local disk:

       $ git clone git@github.com:YourLogin/skll.git
   $ cd skll

  4. Create a feature branch to hold your changes:

       $ git checkout -b feature/my-new-addition

    and start making changes. Never work in the master branch!

  5. Work on this copy on your computer using Git to do the version control. When you're done editing, do:

       $ git add modified_files
   $ git commit

    to record your changes in Git, then push them to GitHub with:

       $ git push feature/my-new-addition

Finally, go to the web page of the your fork of the SKLL repo, and click 'Pull request' to send your changes to the maintainers for review.

(If any of the above seems like magic to you, then look up the Git documentation on the web.)

It is recommended to check that your contribution complies with the following rules before submitting a pull request:

  • All public methods should have informative docstrings.

  • All existing tests pass when everything is rebuilt from scratch. You should be able to see this by running nosetests locally, or looking at the Travis build status after you create your pull request.

  • All new functionality must be covered by unit tests.

  • Every pull request description should contain a link to the issue that it is trying to address. This is easily done by just typing # and then picking the issue from the dropdown. If the issue is not visible, then you type a few characters from the issue title and the dropdown should update.

You can also check for common programming errors with the following tools:

  • Code with good unittest coverage (at least 80%), check with:

       $ pip install nose coverage
   $ nosetests --with-coverage path/to/tests_for_package

  • No pyflakes warnings, check with:

        $ pip install pyflakes
    $ pyflakes path/to/module.py

  • No PEP8 warnings, check with:

        $ pip install pep8
    $ pep8 path/to/module.py

  • AutoPEP8 can help you fix some of the easy redundant errors:

        $ pip install autopep8
    $ autopep8 path/to/pep8.py

After submitting a pull request, it is recommended to add at least 2-3 reviewers to review it. See Requesting a pull request review for more details.

Easy Issues

A great way to start contributing to SKLL is to pick an item from the list of issues labelled with the good first issue tag. Resolving these issues allow you to start contributing to the project without much prior knowledge. Your assistance in this area will be greatly appreciated by the more experienced developers as it helps free up their time to concentrate on other issues.

Large Issues

If you are willing, there are often issues that are not incredibly complex, but still take more time than the main developers have had time to address them. Any help with these issues would be greatly appreciated. They are labelled with the help wanted tag on the issue list.

Documentation

We are glad to accept any sort of documentation: function docstrings, reStructuredText documents (like this one), tutorials, etc. reStructuredText documents live in the source code repository under the doc/ directory.

You can edit the documentation using any text editor and then generate the HTML output by typing make html from the doc/ directory. Alternatively, make can be used to quickly generate the documentation without the example gallery. The resulting HTML files will be placed in _build/html/ and are viewable in a web browser. See the README file in the doc/ directory for more information.

For building the documentation, you will need sphinx as well as the readthedocs sphinx theme. To install both, just run:

  conda install sphinx sphinx_rtd_theme

in your existing conda environment.