sugarplot 0.1.19

Plotting functionality for common experimental datasets

sugarplot - Making pretty data analysis easier

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 name test. 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

• Sphinx
• pytest
• Github Actions
• Codecov
• Github Pages

Acknowledgements

Thanks to all the great people on stack overflow and github, for their seemingly boundless tolerance to my and others' questions.