Contributing to Skoot

Note: This document is a ‘getting started’ summary for contributing code, documentation, testing, and filing issues. Please read it carefully to help make the code review process go as smoothly as possible and maximize the likelihood of your contribution being merged.

How to contribute

The preferred workflow for contributing to skoot is to fork the main repository on Github, clone, and develop on a branch. Steps:

  1. Fork the project repository by clicking on the ‘Fork’ button near the top right of the page. This creates a copy of the code under your Github user account.

  2. Clone your fork of the skoot repo from your Github account to your local disk:

    $ git clone https://github.com/tgsmith61591/skoot.git
$ cd skoot

  3. Create a feature branch to hold your development changes:

    $ git checkout -b my-feature

    Always use a feature branch. It’s good practice to never work on the master branch!

  4. Develop the feature on your feature branch. Add changed files using git add and then git commit files:

    $ git add modified_files
$ git commit

    to record your changes in Git, then push the changes to your Github account with:

    $ git push -u origin my-feature

5. Follow these instructions to create a pull request from your fork. This will send an email to the committers.

Pull Request Checklist

We recommended (and prefer that) that your contribution complies with the following rules before you submit a pull request. Failure to adhere to the rules may hinder the speed with which your contribution is merged:

  • Skoot uses the gitflow branching model. That means all of your feature branches should be merged back to the develop branch, and not master!

  • Write detailed docstrings for all of public your functions. The preferred format for docstrings is the numpy standard. Also include usage examples where appropriate. See also the Numpy guidelines for documenting your code

  • Use, when applicable, the validation tools and scripts in the skoot.utils submodule.

  • Give your merge request a helpful title that summarizes what your contribution does. In some cases Fix <ISSUE TITLE> is enough. Fix #<ISSUE NUMBER> is not enough.

  • If your pull request references an issue, reference it in the body of your descriptive text using #<ISSUE NUMBER>

  • Please prefix the title of your pull request with [MRG] (Ready for Merge), if the contribution is complete and ready for a detailed review. The core developers will then review your code and merge when approved. An incomplete contribution – where you expect to do more work before receiving a full review – should be prefixed [WIP] (to indicate a work in progress) and changed to [MRG] when it matures. WIPs may be useful to: indicate you are working on something to avoid duplicated work, request broad review of functionality or API, or seek collaborators.

  • All other tests pass when everything is rebuilt from scratch. Note that this will actually require a Spark distribution to work locally. On Unix-like systems, check with (from the toplevel source folder):

    $ python setup.py develop
$ pytest

    You may need to see the Setup section for instructions on how to build the package. For instructions on how to test (using nose or pytest) see Numpy’s testing instructions and the Testing section.

Filing bugs

We use Github issues to track all bugs and feature requests; feel free to open an issue if you have found a bug or wish to see a feature implemented.

It is recommended to check that your issue complies with the following rules before submitting:

  • Verify that your issue is not being currently addressed by other issues or pull requests.
  • If your issue references and pull request, reference it in the body of your descriptive text using !<PULL REQUEST NUMBER>
  • Please include your operating system type and version number, as well as your Python, scikit-learn, numpy, scipy, pandas and skoot versions. This information can be found by running the following code snippet:
import platform; print(platform.platform())
import sys; print("Python", sys.version)
import numpy; print("NumPy", numpy.__version__)
import scipy; print("SciPy", scipy.__version__)
import sklearn; print("Scikit-Learn", sklearn.__version__)
import pandas; print("Pandas", pandas.__version__)
import skoot; print("Skoot", skoot.__version__)