Contributions are highly welcomed and appreciated. Every little help counts, so do not hesitate! You can make a high impact on ProPlot just by using it and reporting issues.
The following sections cover some general guidelines regarding development in ProPlot for maintainers and contributors. Nothing here is set in stone and can’t be changed. Feel free to suggest improvements or changes in the workflow.
Feature requests and feedback¶
We are eager to hear about your requests for new features and any suggestions about the API, infrastructure, and so on. Feel free to submit these as issues with the label “feature.”
Please make sure to explain in detail how the feature should work and keep the scope as narrow as possible. This will make it easier to implement in small PRs.
Report bugs for ProPlot in the issue tracker with the label “bug”.
If you are reporting a bug, please include:
Your operating system name and version.
Any details about your local setup that might be helpful in troubleshooting, specifically the Python interpreter version, installed libraries, and ProPlot version.
Detailed steps to reproduce the bug.
If you can write a demonstration test that currently fails but should pass, that is a very useful commit to make as well, even if you cannot fix the bug itself.
Look through the GitHub issues for bugs.
Talk to developers to find out how you can fix specific bugs.
ProPlot could always use better documentation. For small changes, you can edit documentation files directly in the GitHub web interface, without using a local copy.
The documentation is written in reStructuredText with numpydoc style headers.
The default ReST role is
'py:obj'. This is meant to encourage populating docstrings with links to the API reference. ProPlot uses intersphinx, so you can also link to sphinx documentation from other projects, e.g. matplotlib. In general, you should compress your links with a tilde, e.g.
When editing the ipython notebooks found in
docs, make sure to put your example descriptions inside reStructedText cells, not markdown cells. This lets us populate the descriptions with sphinx links. See this guide for how to convert cells to ReST.
Some helpful ReST guides are located here and here.
To build the documentation locally, use the following commands:
cd docs pip install requirements.txt make html
The built documentation should be available in the
Preparing pull requests¶
Fork the proplot GitHub repository. It’s fine to use ProPlot as your fork repository name because it will live under your user.
Clone your fork locally using git, connect your repository to the upstream (main project), and create a branch:
git clone email@example.com:YOUR_GITHUB_USERNAME/proplot.git cd proplot git remote add upstream firstname.lastname@example.org:lukelbd/proplot.git git checkout -b your-bugfix-feature-branch-name master
If you need some help with git, follow the quick start guide.
Install pre-commit and its hook on the
pip install --user pre-commit pre-commit install
pre-commitwill run whenever you commit. https://pre-commit.com/ is a framework for managing and maintaining multi-language pre-commit hooks to ensure code-style and code formatting is consistent.
You can now edit your local working copy as necessary. Please follow PEP-8 naming conventions. When committing,
pre-commitwill modify the files as needed, or will generally be clear about what you need to do to pass the commit test.
If you intend to make changes / add examples to the ipython notebooks, you need to install and configure nbstripout with
pip install --user nbstripout git config --local include.path ../.gitconfig
This strips notebook cell output when files are staged, which reduces the repo storage size and lets us use nbsphinx to test each
git configcommand associates the filters declared in
proplot/.gitattributeswith the operations described in
proplot/.gitconfigby adding them to the recognized local configuration file
Make an editable install of ProPlot by running:
pip install -e .
This way when you
import proplot, your local copy is used. You can print
proplot.__file__to verify this. Make sure matplotlib is already installed.
Break your edits up into reasonably sized commits.
git commit -a -m "<commit message>" git push -u
The commit messages should be short, sweet, and use the imperative mood, e.g. “Fix bug” instead of “Fixed bug”.
Create a new changelog entry in
The entry should be entered as:
<description> (:pr:`<PR number>`) `<author name>`_
<description>is the description of the PR related to the change,
<PR number>is the pull request number, and
<author name>is your first and last name.
Add yourself to list of authors at the end of
CHANGELOG.rstfile if not there yet, in alphabetical order.
Finally, submit a pull request through the GitHub website using this data:
head-fork: YOUR_GITHUB_USERNAME/proplot compare: your-branch-name base-fork: lukelbd/proplot base: master
Note that you can create the Pull Request while you’re working on this. The PR will update as you add more commits. ProPlot developers and contributors can then review your code and offer suggestions.