Contribution Guide#

Contributions are highly welcomed and appreciated. Every little help counts, so do not hesitate! You can make a high impact on xbitinfo just by using it and reporting issues.

The following sections cover some general guidelines regarding development in xbitinfo for maintainers and contributors.

Nothing here is set in stone and can’t be changed. Feel free to suggest improvements or changes in the workflow.

Feature requests and feedback#

We are eager to hear about your requests for new features and any suggestions about the API, infrastructure, and so on. Feel free to submit these as issues with the label "enhancement".

Please make sure to explain in detail how the feature should work and keep the scope as narrow as possible. This will make it easier to implement in small PRs.

Report bugs#

Report bugs for xbitinfo in the issue tracker with the label “bug”.

If you are reporting a bug, please include:

  • Any details about your local setup that might be helpful in troubleshooting, specifically the Python interpreter version, installed libraries, and xbitinfo version.

  • Detailed steps how to reproduce the bug <>__

If you can write a demonstration test that currently fails but should pass, that is a very useful commit to make as well, even if you cannot fix the bug itself.

Bug Fix#

Look through the GitHub issues for bugs.

Talk to developers to find out how you can fix specific bugs.

Preparing Pull Requests#

  1. Fork the xbitinfo GitHub repository. It’s fine to use xbitinfo as your fork repository name because it will live under your user.

  2. Clone your fork locally using git, connect your repository to the upstream (main project), and create a branch:

    $ git clone
    $ cd xbitinfo
    $ git remote add upstream
    # now, to fix a bug or add feature create your own branch off "main":
    $ git checkout -b your-bugfix-feature-branch-name main

    If you need some help with Git, follow this quick start guide.

  3. Install dependencies into a new conda environment:

    $ conda env create -f environment.yml
    $ conda activate bitinfo
  4. Make an editable install of xbitinfo by running:

    $ pip install -e .
  5. Install pre-commit and its hook on the xbitinfo repo:

    $ pip install --user pre-commit
    $ pre-commit install

    pre-commit automatically beautifies the code, makes it more maintainable and catches syntax errors. Afterwards pre-commit will run whenever you commit.

    Now you have an environment called bitinfo that you can work in. You’ll need to make sure to activate that environment next time you want to use it after closing the terminal or your system.

    You can now edit your local working copy and run/add tests as necessary. Please try to follow PEP-8 for naming. When committing, pre-commit will modify the files as needed, or will generally be quite clear about what you need to do to pass the commit test.

    pre-commit also runs:

    * `mypy <>`_ for static type checking on
      `type hints <>`_.
    * `isort <>`_ sorting imports
    * `black <>`_ code formatting
    * `flake8 <>`_ code linting
        * `blackdoc <>`_ docstring code formatter
  6. Break your edits up into reasonably sized commits:

    $ git commit -m "<commit message>"
    $ git push -u
  7. Run all tests

    Once commits are pushed to origin, GitHub Actions runs continuous integration of all tests with pytest on all new commits. However, you can already run tests locally:

    $ pytest  # all
    $ pytest tests/  # specific tests

    Check that doctests are passing:

    $ pytest --doctest-modules xbitinfo

    Please stick to xarray’s testing recommendations.

  8. Running the performance test suite

    If you considerably changed to core of code of xbitinfo, it is worth considering whether your code has introduced performance regressions. xbitinfo has a suite of benchmarking tests using asv to enable easy monitoring of the performance of critical xbitinfo operations. These benchmarks are all found in the asv_bench directory.

    If you need to run a benchmark, change your directory to asv_bench/ and run:

    $ asv continuous -f 1.1 upstream/main HEAD

    You can replace HEAD with the name of the branch you are working on, and report benchmarks that changed by more than 10%. The command uses conda by default for creating the benchmark environments.

    Running the full benchmark suite can take some time and use up a few GBs of RAM. Usually it is sufficient to paste only a subset of the results into the pull request to show that the committed changes do not cause unexpected performance regressions. If you want to only run a specific group of tests from a file, you can do it using . as a separator. For example:

    $ asv continuous -f 1.1 upstream/main HEAD -b benchmarks_bitround.rasm.time_xr_bitround

    will only run the time_xr_bitround benchmark of class rasm loading the xr.tutorial.load_dataset("rasm") defined in

  9. Create a new changelog entry in CHANGELOG.rst:

    The entry should be entered as:

    <description> (:pr:`#<pull request number>`) `<author's names>`_

    where <description> is the description of the PR related to the change and <pull request number> is the pull request number and <author's names> are your first and last names.

    Add yourself to list of authors at the end of CHANGELOG.rst file if not there yet, in alphabetical order.

  10. Add yourself to the authors.

  11. Finally, submit a Pull Request through the GitHub website using this data:

    head-fork: YOUR_GITHUB_USERNAME/xbitinfo
    compare: your-branch-name
    base-fork: observingClouds/xbitinfo
    base: main

Note that you can create the Pull Request while you’re working on this. The PR will update as you add more commits. xbitinfo developers and contributors can then review your code and offer suggestions.