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1-click Generator of Python Project, from Template with streamlined "DevOps" using a powerful CI/CD Pipeline.

Project description

GitHub Workflow Status (with event) Codecov Read the Docs (version) Maintainability Codacy Code Climate technical debt
Production Version PyPI - Wheel Supported Python versions GitHub commits since tagged version (branch) GitHub commits since latest release (by SemVer)
PyPI - Downloads OpenSSF Ruff Black GitHub

Generate Python Project and enjoy streamlined DevOps using a powerful CI/CD Pipeline.

What’s included?

  • Generator of Python Project (see Quickstart), with CLI for Linux, MacOS, and Windows

  • Option to Generate Python Package designed as module, module+cli, or pytest-plugin!

  • Scaffold over 24 files, from Template, to have a ready-to-develop Project equipped with:

    • Fully-featured CI/CD Pipeline, running on Github Actions, defined in .github/

    • Continuous Delivery to PyPI (i.e., and Dockerhub

    • Continuous Integration, with Test Suite running pytest, located in the tests dir

    • Continuous Documentation, building with mkdocs or sphinx, and hosting on readthedocs, located in the docs dir

    • Static Type Checking, using mypy

    • Lint Check and Apply commands, using the fast Ruff linter, along with standard isort, and black

    • Build Command, using the build python package

What to expect?

You can to be up and running with a new Python Package, and run workflows on Github Actions, such as:

CI Pipeline, running on Github Actions, for a Biskotaki Python Package


  1. CI Pipeline, running on Github Actions, defined in .github/

    1. Job Matrix, spanning different platform’s and python version’s

      1. Platforms: ubuntu-latest, macos-latest

      2. Python Interpreters: 3.6, 3.7, 3.8, 3.9, 3.10

    2. Parallel Job execution, generated from the matrix, that runs the Test Suite

    3. Artifact store of Source and Wheel Distributions, factoring Platform and Python Version

Auto Generated Sample Package Biskotaki

Check the Biskotaki Python Package Project, for a taste of the project structure and capabilities this Template can generate!

It it entirely generated using this Python Package Template:

Source Code hosted on Github at
Python Package hosted on at
CI Pipeline hosted on Github Actions at


To install the latest Generator in your environment, run:

pip install cookiecutter-python

The generate-python (executable) CLI should now be available in your environment.

Next, create a file, let’s call it gen-config.yml, with the following content:

    project_name: Demo Generated Project
    project_type: module+cli
    full_name: John Doe
    github_username: john-doe
    project_short_description: 'Demo Generated Project Description'
    initialize_git_repo: no
    interpreters: {"supported-interpreters": ["3.8", "3.9", "3.10", "3.11"]}

To generate a Python Package Project, run:

mkdir gen-demo-dir
cd gen-demo-dir

generate-python --config-file ../gen-config.yml --no-input

Now, you should have generated a new Project for a Python Package, based on the Template!

The Project should be located in the newly created demo-generated-project directory.

To leverage all out-of-the-box development operations (ie scripts), install tox:

python3 -m pip install --user 'tox<4'

To verify tox available in your environment, run: tox --version

Please, do a cd into the newly created directory, ie cd <my-great-python-package>.

To run the Test Suite, cd into the newly created Project folder, and run:

tox -e dev

All Tests should pass, and you should see a coverage report!

To run Type Checking against the Source Code, run:

tox -e type

All Type Checks should pass!

To setup a Git Repository, run:

git init
git add .
git checkout -b main
git commit -m "Initial commit"

To setup a Remote Repository, run for example:

git remote add origin <remote-repository-url>
git push -u origin main

To trigger the CI/CD Pipeline, run:

git push

Navigate to your page, to see the CI Pipeline running!

Develop your package’s Source Code (business logic) inside src/my_great_python_package dir :)
Develop your package’s Test Suite (ie unit-tests, integration tests) inside tests dir :-)

Read the Documentation’s Use Cases section for more on how to leverage your generated Python Package features.

Next Steps

To prepare for an Open Source Project Development Lifecycle, you should visit the following websites:

  • PyPI,, Dockerhub, and Read the Docs, for setting up Release and Documentation Pipelines

  • to configure Actions, through the web UI

  • Codecov, Codacy, and Codeclimate, for setting up Automated Code Quality, with CI Pipelines

  • for registering your Project for OpenSSF Best Practices Badge

Happy Developing!



Free/Libre and Open Source Software (FLOSS)


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