The preferred way to contribute to scikit-video is to fork the main repository on GitHub:
Fork the project repository: click on the 'Fork' button near the top of the page. This creates a copy of the code under your account on the GitHub server.
Clone this copy to your local disk:
$ git clone git@github.com:YourLogin/scikit-video.git $ cd scikit-video
Create a branch to hold your changes:
$ git checkout -b my-feature
and start making changes. Never work in the
masterbranch!Work on this copy on your computer using Git to do the version control. When you're done editing, do:
$ git add modified_files $ git commit
to record your changes in Git, then push them to GitHub with:
$ git push -u origin my-feature
Finally, go to the web page of your fork of the scikit-video repo, and click 'Pull request' to send your changes to the maintainers for review.
(If any of the above seems like magic to you, then look up the Git documentation on the web.)
It is recommended to check that your contribution complies with the following rules before submitting a pull request:
All public methods should have informative docstrings with sample usage presented as doctests when appropriate.
The test suite passes. Install in editable mode with the test extra and run pytest (FFmpeg must be on the PATH for the io tests):
$ pip install -e ".[test]" $ pytest -v skvideo/tests
New functionality should come with tests; bug fixes should come with a regression test that fails before the fix.
When adding additional functionality, consider adding an example to the documentation (
doc/examples/). Examples should demonstrate why the new functionality is useful in practice and, if possible, compare it to other methods available in scikit-video.
Review cadence: the project is maintained on a part-time basis, with a focus on bug fixes and compatibility. Expect responses on the scale of weeks, not days.
We are glad to accept any sort of documentation: function docstrings,
reStructuredText documents (like this one), tutorials, etc.
reStructuredText documents live in the source code repository under the
doc/ directory.
You can edit the documentation using any text editor and then generate
the HTML output by typing make html from the doc/ directory
(requires pip install -e ".[docs]"). The resulting HTML files will
be placed in doc/_build/html/ and are viewable in a web browser.
When you are writing documentation, it is important to keep a good compromise between mathematical and algorithmic details, and give intuition to the reader on what the algorithm does. It is best to always start with a small paragraph with a hand-waving explanation of what the method does to the data and a figure (coming from an example) illustrating it.