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CONTRIBUTING.md

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Contributing

Bug reports, feature suggestions and other contributions are greatly appreciated! pysatCDF is a community-driven project and welcomes both feedback and contributions.

Come join us on Slack! An invitation to the pysat workspace is available in the 'About' section of the pysat GitHub Repository. Development meetings are generally held fortnightly.

Short version

  • Submit bug reports and feature requests at GitHub
  • Make pull requests to the develop branch

Bug reports

When reporting a bug please include:

  • Your operating system name and version
  • Any details about your local setup that might be helpful in troubleshooting
  • Detailed steps to reproduce the bug

Feature requests and feedback

The best way to send feedback is to file an issue at GitHub.

If you are proposing a feature:

  • Explain in detail how it would work.
  • Keep the scope as narrow as possible, to make it easier to implement.
  • Remember that this is a volunteer-driven project, and that code contributions are welcome :)

Development

To set up pysatCDF for local development:

  1. Fork pysat on GitHub.

  2. Clone your fork locally:

    git clone [email protected]:your_name_here/pysatCDF.git

  3. Create a branch for local development:

    git checkout -b name-of-your-bugfix-or-feature

    Now you can make your changes locally. Tests for new instruments are performed automatically. Tests for custom functions should be added to the appropriately named file in pysatCDF/tests. If no test file exists, then you should create one. This testing uses pytest, which will run tests on any python file in the test directory that starts with test_.

  4. When you're done making changes, run all the checks to ensure that nothing is broken on your local system:

    pytest -vs

  5. Update/add documentation (in docs), if relevant

  6. Add your name to the .zenodo.json file as an author

  7. Commit your changes:

    git add .
git commit -m "AAA: Brief description of your changes"

    Where AAA is a standard shorthand for the type of change (eg, BUG or DOC). pysat follows the numpy development workflow, see the discussion there for a full list of this shorthand notation.

  8. Once you are happy with the local changes, push to Github:

    git push origin name-of-your-bugfix-or-feature

    Note that each push will trigger the Continuous Integration workflow.

  9. Submit a pull request through the GitHub website. Pull requests should be made to the develop branch.

Pull Request Guidelines

If you need some code review or feedback while you're developing the code, just make a pull request. Pull requests should be made to the develop branch.

For merging, you should:

  1. Include an example for use
  2. Add a note to CHANGELOG.md about the changes
  3. Ensure that all checks passed (current checks include GitHub Actions and Coveralls)

If you don't have all the necessary Python versions available locally or have trouble building all the testing environments, you can rely on the project's Continuous Integration (CI) service to run the tests for each change you add in the pull request. Because testing here will delay tests by other developers, please ensure that the code passes all tests on your local system first.

Project Style Guidelines ^^^^^^^^^^^^^^^^^^^^^^^^

In general, pysat follows PEP8 and numpydoc guidelines. Pytest runs the unit and integration tests, flake8 checks for style, and sphinx-build performs documentation tests. However, there are certain additional style elements that have been settled on to ensure the project maintains a consistent coding style. These include:

  • Line breaks should occur before a binary operator (ignoring flake8 W503)
  • Combine long strings using join
  • Preferably break long lines on open parentheses rather than using \
  • Use no more than 80 characters per line
  • Avoid using Instrument class key attribute names as unrelated variable names: platform, name, tag, and inst_id
  • The pysat logger is imported into each sub-module and provides status updates at the info and warning levels (as appropriate)
  • Several dependent packages have common nicknames, including:
    • import datetime as dt
    • import numpy as np
    • import pandas as pds
    • import xarray as xr
  • All classes should have __repr__ and __str__ functions
  • Docstrings use Note instead of Notes
  • Try to avoid creating a try/except statement where except passes
  • Use setup and teardown in test classes
  • Use pytest parametrize in test classes when appropriate
  • Provide testing class methods with informative failure statements and descriptive, one-line docstrings
  • Block and inline comments should use proper English grammar and punctuation with the exception of single sentences in a block, which may then omit the final period
  • When casting is necessary, use np.int64 and np.float64 to ensure operating system agnosticism