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Contributing to Biopython

We welcome pull requests to fix bugs or add new features. Please read http://biopython.org/wiki/Contributing for a general overview about contributing - this file is primarily concerned with the practicalities.

Licensing

Biopython is moving towards dual licensing the code. In your git commit and/or pull request, please explicitly state that you agree to your contributions being dual licensed under both our original "Biopython License Agreement" and the more widely used "3-Clause BSD License" (see our LICENSE file for more details).

Git Usage

We have a git introduction online at http://biopython.org/wiki/GitUsage

If you are planning to make a pull request, start by creating a new branch with a short but descriptive name (rather than using your master branch).

Coding Conventions

Biopython tries to follow the coding conventions laid out in PEP8 and PEP257, with the notable exception of existing module names which are not lower case.

We have adopted the code formating tool black to which automates a lot of coding style choices like line breaks and spacing. This applies to all our code, except the Tests/ folder which we are still gradually updating.

We use the tool flake8 for automating our code style checks, together with various plugins which can be installed as follows:

$ pip install flake8 flake8-docstrings flake8-black flake8-blind-except flake8-rst-docstrings flake8-comprehensions flake8-quotes flake8-bugbear flake8-implicit-str-concat

We use the continuous integration service TravisCI to run these flake8 checks, but it is better to run them locally before making a pull request. We currently strongly suggest you then install the flake8 git pre-commit hook which will check our basic coding conventions as you work:

$ flake8 --install-hook git
$ git config --bool flake8.strict true

For testing, you can also run flake8 directly from the command line as follows:

$ flake8

For docstrings (Python's in-code documentation) in addition to PEP257 we are using reStructuredText (RST) markup language which allows basic formatting like italics and bold once rendered into HTML webpages for our online API documentation.

We also use reStructuredText for files like README.rst. You can run the reStructuredText checks with the restructuredtext-lint tool (also known as rst-lint):

$ pip install restructuredtext_lint
$ rst-lint --level warning *.rst

Testing

Any new feature or functionality will not be accepted without tests. Likewise for any bug fix, we encourage including an additional test. See the testing chapter in the Biopython Tutorial for more information on our test framework: http://biopython.org/DIST/docs/tutorial/Tutorial.html

Local Testing

Please always run the style checks (see above) and the full test suite on your local computer before submitting a pull request, e.g.:

$ git commit Bio/XXX.py Tests/test_XXX.py  -m "Fixed bug 123"
$ python setup.py build
$ python setup.py test

If you have multiple versions of Python installed, ideally test them all (the Python tool tox can be helpful here).

Continuous Integration

Once you submit your pull request on GitHub, several automated tests should be run, and their results reported on the pull request.

We use TravisCI to run most of the Biopython tests (although currently only under Linux, and not with all the optional dependencies included), plus also check Python coding style using the flake8 tool with lots of plugins, and reStructuredText files using rst-lint and doc8. https://travis-ci.org/biopython/biopython/branches

We use AppVeyor to run most of the tests under Windows (although currently without any optional dependencies). https://ci.appveyor.com/project/biopython/biopython/history

The TravisCI and AppVeyor checks must pass before your pull request will be merged.

Some of the TravisCI and AppVeyor runs collect test coverage information via CodeCov: https://codecov.io/github/biopython/biopython/

Ideally the CodeCov checks will also pass, but we currently do not insist on this when reviewing pull requests.

Contributing to the Biopython Tutorial

For instructions, see the Biopython Tutorial README