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Plotting functionality for common experimental datasets

Project description

Template Github Repository

Build docs codecov

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

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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