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Contributing

Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.

You can contribute in many ways:

Report Bugs

Report bugs at https://github.com/opencobra/cobrapy/issues.

If you are reporting a bug, please follow the template guide lines. The more detailed your report, the easier and thus faster we can help you.

Fix Bugs

Look through the GitHub issues for bugs. Anything tagged with "bug" and "help wanted" is open to whoever wants to implement it.

Implement Features

Look through the GitHub issues for features. Anything tagged with "enhancement" and "help wanted" is open to whoever wants to implement it.

Write Documentation

cobrapy could always use more documentation, whether as part of the official documentation, in docstrings, or even on the web in blog posts, articles, and such.

Submit Feedback

The best way to send feedback is to file an issue at https://github.com/opencobra/cobrapy/issues.

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 contributions are welcome :)

Get Started!

Ready to contribute? Here's how to set up cobrapy for local development.

  1. Fork the https://github.com/opencobra/cobrapy repository on GitHub. If you have never done this before, follow the official guide

  2. Clone your fork locally as described in the same guide.

  3. Install your local copy into a a Python virtual environment. You can read this guide to learn more about them and how to create one. Alternatively, particularly if you are a Windows or Mac user, you can also use Anaconda. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development

    mkvirtualenv my-env
cd cobrapy/
pip install -e ".[development]"

  4. Create a branch for local development using the devel branch as a starting point. Use fix, refactor, or feat as a prefix

    git checkout devel
git checkout -b fix-name-of-your-bugfix

    Now you can make your changes locally.

  5. When making changes locally, it is helpful to git commit your work regularly. On one hand to save your work and on the other hand, the smaller the steps, the easier it is to review your work later. Please use semantic commit messages.

    git add .
git commit -m "fix: Your summary of changes"

  6. When you're done making changes, check that your changes pass our test suite. This is all included with tox

    tox

    You can also run all tox tests in parallel. As of tox 3.7, you can run

    tox --parallel

  7. Push your branch to GitHub.

    git push origin fix-name-of-your-bugfix

  8. Open the link displayed in the message when pushing your new branch in order to submit a pull request. Please follow the template presented to you in the web interface to complete your pull request.

For larger features that you want to work on collaboratively with other cobrapy team members, you may consider to first request to join the cobrapy developers team to get write access to the repository so that you can create a branch in the main repository (or simply ask the maintainer to create a branch for you). Once you have a new branch you can push your changes directly to the main repository and when finished, submit a pull request from that branch to devel.

Pull Request Guidelines

Before you submit a pull request, check that it meets these guidelines:

  1. The pull request should include tests in the cobra/test directory. Except in rare circumstances, code coverage must not decrease (as reported by codecov which runs automatically when you submit your pull request)
  2. If the pull request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring and consider creating a notebook that demonstrates the usage in documentation_builder (documentation is written as jupyter notebooks in the documentation_builder directory, which are then converted to rst by the autodoc.sh script.)
  3. The pull request will be tested for several different Python versions.
  4. Someone from the @opencobra/cobrapy-core team will review your work and guide you to a successful contribution.

Unit tests and benchmarks

cobrapy uses pytest for its unit-tests and new features should in general always come with new tests that make sure that the code runs as intended. Since COBRA rapidly can become quite resource intensive fundamental methods such as model manipulation, adding and removing reactions, metabolites etc also must work efficiently. We use pytest-benchmark to compare different implementations to make sure that new code do not come with unacceptable increased computation time. If you add benchmarked tests, make sure to also include a test with and without the benchmark as we do not want to slow down continuous integration by running benchmarks, for examples, see e.g. test_add_metabolite in test_model.py. test_add_metabolite is the main test, test_add_metabolite_benchmark takes the special benchmark fixture that enables profiling the important code snippet but is skipped when running:

(cobrapy)$ pytest --benchmark-skip

When the test function itself is small and can safely be assumed to not take many resources, we can directly profile the test as in test_subtract_metabolite_benchmark which calls benchmark(self.test_subtract_metabolite, model).

To run all tests and benchmarks do:

(cobrapy)$ pytest

and to compare two implementations you may keep them in two branches e.g. old and new and then do:

(cobrapy)$ git checkout old
(cobrapy)$ pytest --benchmark-save
(cobrapy)$ git checkout new
(cobrapy)$ pytest --benchmark-compare

Branching model

devel
Is the branch all pull-requests should be based on.
stable
Is only touched by maintainers and is the branch with only tested, reviewed code that is released or ready for the next release.
{fix, bugfix, doc, feature}/descriptive-name
Is the recommended naming scheme for smaller improvements, bugfixes, documentation improvement and new features respectively.

Please use concise descriptive commit messages and consider using git pull --rebase when you update your own fork to avoid merge commits.

Thank you very much for contributing to cobrapy!

FAQs

Q1. Why do all of the tests that involve loading a pickled model fail on my branch?
A: Pickling is the standard method for serializing objects in python, which is commonly done during operations like multiprocessing. Because of this, we need to maintain tests that run on pickled models, otherwise contributors may inadvertantly break multiprocessing features. If changes you made to cobrapy modify attributes of the cobra.Model class, the pickled models stored in the repository won't contain those changes and may fail tests that you add or modify. To resolve these errors, just run cobra/test/data/update_pickles.py on your branch, which will repickle the models.