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.
If you expericence issues with pyGIMLi or miss a certain feature, please open a new issue on GitHub. To do so, you need to create a GitHub account.
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 chapt:examples, please send your script to [email protected]. Make sure that the individual steps in your Python script are documented according to the sphinx-gallery syntax.
note
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 sec:install).
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
adaptive_meshes
.
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 sec: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.
While you work on your forked repository, sometimes changes are commited to the
main repository (usually called upstream).
You do NOT need to delete your forked repository and refork to apply these
changes to your own fork.
Follow the procedure described here <https://help.github.com/en/articles/syncing-a-fork>
__
Required only once, add the main repository as a remote to your local (cloned) git repository:
git remote add upstream https://github.com/gimli-org/gimli.git
Development work is usually based on the dev branch, and before creating a new feature branch, make sure to update this branch on your forked repository:
.. code:: bash
git checkout -b dev
git merge upstream/dev
# the following will push updates to your personal fork
git push
Only then create your feature branch
.. code:: bash
git checkout -b new_feature