AICS Cookiecutter template for a Python package.

Cookiecutter is a Python package to generate templated projects. This repository is a template for cookiecutter to generate a Python project which contains following:

• A directory structure for your project
• Prebuilt setup.py file to help you develop and install your package
• Includes examples of good Python practices, including tests
• Continuous integration
  • Preconfigured to generate project documentation
  • Preconfigured to automatically run tests every time you push to GitHub
  • Preconfigured to help you release your package publicly (PyPI)

We think that this template provides a good starting point for any Python project.

• Uses tox (an environment manager) and pytest for local testing, simply run tox or make build from a terminal in the project home directory
• Runs tests on Windows, Mac, and Ubuntu on every branch and pull request commit using GitHub Actions
• Releases your Python Package to PyPI when you push to stable using GitHub Actions
• Automatically builds documentation using Sphinx on every push to master and deploys to GitHub Pages
• Includes example code samples for objects, tests, and bin scripts

• For an example of the base project that is built from this template, go to the example-build branch.

To use this template use the following commands and then follow the prompts from the terminal.

1. pip install cookiecutter
2. cookiecutter gh:AllenCellModeling/cookiecutter-pypackage

1. pip install -e .[dev]

   This will install your package in editable mode with all the required development dependencies (i.e. tox).

2. make build

   This will run tox which will run all your tests in both Python 3.7 and Python 3.8 as well as linting your code.

3. make clean

   This will clean up various Python and build generated files so that you can ensure that you are working in a clean environment.

4. make docs

   This will generate and launch a web browser to view the most up-to-date documentation for your Python package.

• Turn your project into a GitHub repository:
  • Make sure you have git installed, if you don't, follow these instructions
  • Make an account on github.com
  • Go to make a new repository
  • Recommendations:
    • It is strongly recommended to make the repository name the same as the Python package name
    • A lot of the following optional steps are free if the repository is Public, plus open source is cool
  • After a GitHub repo has been created, run the following commands:
    • git remote add origin [email protected]:{your github username}/{your repository name}.git
    • git push -u origin master
• Register your project with Codecov:
  • Make an account on codecov.io (Recommended to sign in with GitHub)
  • Select the organization you want to link a repository to and click: Add new repository
  • Copy the token provided, go to your GitHub repository's settings and under the Secrets tab, add a secret called CODECOV_TOKEN with the token you just copied. Don't worry, no one will see this token because it will be encrypted.
• Generate and add an access token as a secret to the repository for auto documentation generation to work
  • Go to your GitHub account's Personal Access Tokens page
  • Click: Generate new token
  • Recommendations:
    • Name the token: "Auto-Documentation Generation" or similar so you know what it is being used for later
    • Select only: repo:status, repo_deployment, and public_repo to limit what this token has access to
  • Copy the newly generated token
  • Go to your GitHub repository's settings and under the Secrets tab, add a secret called ACCESS_TOKEN with the personal access token you just created. Don't worry, no one will see this password because it will be encrypted.
• Register your project with PyPI:
  • Make an account on pypi.org
  • Go to your GitHub repository's settings and under the Secrets tab, add a secret called PYPI_TOKEN with your password for your PyPI account. Don't worry, no one will see this password because it will be encrypted.
  • Next time you push to the branch: stable, GitHub actions will build and deploy your Python package to PyPI.
  • Recommendation: Prior to pushing to stable it is recommended to install and run bumpversion as this will, tag a git commit for release and update the setup.py version number.
• Add branch protections to master and stable
  • To protect from just anyone pushing to master or stable (the branches with more tests and deploy configurations)
  • Go to your GitHub repository's settings and under the Branches tab, click Add rule and select the settings you believe best.
  • Recommendations:
    • Require pull request reviews before merging
    • Require status checks to pass before merging (Recommended: lint and test)

1. master is for the most up-to-date development, very rarely should you directly commit to this branch. GitHub Actions will run on every push and on a CRON to this branch but still recommended to commit to your development branches and make pull requests to master.
2. stable is for releases only. When you want to release your project on PyPI, simply make a PR from master to stable, this template will handle the rest as long as you have added your PyPI information described in the above Optional Steps section.
3. Your day-to-day work should exist on branches separate from master. Even if it is just yourself working on the repository, make a PR from your working branch to master so that you can ensure your commits don't break the development head. GitHub Actions will run on every push to any branch or any pull request from any branch to any other branch.
4. It is recommended to use "Squash and Merge" commits when committing PR's. It makes each set of changes to master atomic and as a side effect naturally encourages small well defined PR's.
5. GitHub's UI is bad for rebasing master onto stable, as it simply adds the commits to the other branch instead of properly rebasing from what I can tell. You should always rebase locally on the CLI until they fix it.

Original repo: https://github.com/audreyr/cookiecutter-pypackage/