As an open-source project, pyGIMLi always welcomes contributions from the community. Here, we offer guidance for 3 different ways of contributing with increasing levels of required coding proficiency.
We are constantly looking for interesting usage examples of pyGIMLi. If you have used the package and would like to contribute your work to the Examples, please send your script to firstname.lastname@example.org. Make sure that the individual steps in your Python script are documented according to the sphinx-gallery syntax.
To avoid redundant work, please contact us before you start working on a non-trivial feature.
The preferred way to contribute to the pygimli code base is via a pull request (PR) on GitHub. The general concept is explained here and involves the following steps:
If you are a first-time contributor, you need a GitHub account and your own copy (“fork”) of the code. To do so, go to https://github.com/gimli-org/gimli and click the “Fork button” in the upper right corner. This will create an identical copy of the complete code base under your username on the GitHub server. Clone this repository to your local disk:
git clone https://github.com/YOUR_USERNAME/gimli
After that you can install the software as usual (see Installation).
Go to the source folder and create a feature branch to hold your changes. It is
advisable to give it a sensible name such as
cd gimli git checkout -b adaptive_meshes
Go nuts! Add and modify files and regularly commit your changes with meaningful commit messages. Remember that you are working in your own personal copy and in case you break something, you can always go back. While coding, we encourage you to follow a few sec:coding_guidelines.
git add new_file1 new_file2 modified_file1 git commit -m "Implemented adaptive meshes."
Make sure that everything works as expected. New functions should always contain a docstring with a test:
def sum(a, b): """Return the sum of `a` and `b`. Examples -------- >>> a = 1 >>> b = 2 >>> sum(a,b) 3 """ return a + b
When you run
pg.test() the docstring test will be evaluated. See also the
section on Testing.
Once you implemented a functioning new feature, make sure your GitHub repository contains all your commits:
git push origin adaptive_meshes
After pushing, you can go to GitHub and you will see a green PR button. Describe your changes in more detail. Once reviewed by the core developers, your PR will be merged to the main repository.