Plotting functionality for common experimental datasets
Project description
Template Github Repository
This is a template repository for python projects which use sphinx for documentation, github actions for building, pytest and codecov for test coverage.
Getting Started
Installation via pip
pip install sugarplot
Features
- Github actions unit test integration via pytest
- Github actions package management with conda
- Github actions documentation build using sphinx and reST/markdown, with auto self-push to repository after successful build
- Github pages documentation hosting/integration
- Local commits hooks run full test suite
- Coverage uploaded automatically to codecov after successful build
- [FUTURE] Auto-deploy to pyPi/testpyPi after successful build
Common Issues
- Re-running builds on github actions will cause them to fail, as the build number deployed to PyPi depends on the github run number, which does not change if you restart a build.
- Pypi deploy is a little slower than test pypi, so it may not always be downloading the latest version.
How to Use
Adding Additional Unit Tests
- Any time you want to add additional unit tests just add them to those in the
tests/
directory and prepend with the nametest
. These will be automatically found by pytest and run during local commits and remote builds.
Writing the Documentation
- The documentation source is located in
docs/source
and is written in restructured text (markdown is also available).
Building the Documentation
Simply run make html
from the docs/
directory. This will compile the
files in the docs/source/
directory, and place them in the main docs/
directory where github pages can find them.
Dependencies / Technologies Used
Acknowledgements
Thanks to all the great people on stack overflow and github, for their seemingly boundless tolerance to my and others' questions.
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