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A Python project generator using cookiecutter templates

Project description

License: MIT PyPI version Python 3.10+ Documentation Status

Generate Project

A Python project folder generator with support for Poetry and UV package managers. The generated folder provides everything you need to get started with a well-structured Python project, including development tasks for formatting, linting, documentation, testing, and CI/CD.

Features

๐Ÿ“ฆ Poetry or UV for dependency management and packaging
๐Ÿงน Code quality tools including black, isort, flake8, mypy and pylint
๐Ÿ“š Sphinx based documentation with auto-generated API docs and live preview
โœ… Testing framework with pytest and test coverage reports
๐Ÿ”„ GitHub actions with CI/CD workflows for tests, documentation and release management
๐Ÿ PyPl package publishing automation with version control
๐Ÿ“ ReadTheDocs integration for hosting documentation
๐Ÿš€ Automated release process for versioning and publishing
๐Ÿ“‹ Project structure following best practices

Requirements

Python 3.10+
Cookiecutter 2.6.0+
PyYAML 6.0.0+
python-dotenv 1.1.0+

Installation

pip install generate-project

Or, if you use Poetry:

poetry add generate-project

Or, if you use UV:

uv add generate-project

Quick Start

Basic Usage

You can provide the project configuration values in the terminal command line:

generate-project generate "project-name" \
--author_name="Your Name" \
--email="your.email@example.com" \
--github_username="yourusername" \
--python_min_version="3.11"
...

Project Configuration Options

These are the most important project configuration options:

Option Description
package_name Python package name (defaults to project_name)
author_name Author's name
email Author's email
github_username GitHub username
version Initial version number
description Short project description
python_min_version Minimum Python version

Advanced Usage

You can also save your own configuration values to be used as default values:

generate-project config \
--author_name="Your Name" \
--email="your.email@example.com" \
--github_username="yourusername" \
--python_min_version="3.11"

You can also set the default package manager:

generate-project config --manager uv

and then you can omit the saved configuration options:

generate-project generate "project-name"
...

Package Manager

By default, generate-project creates projects using Poetry. Use the --manager flag to select UV instead:

Manager Build Backend Dependency Format Command
Poetry (default) poetry-core [tool.poetry.dependencies] --manager poetry
UV hatchling [dependency-groups] (PEP 735) --manager uv
# Poetry project (default)
generate-project generate my-project

# UV project
generate-project generate my-project --manager uv

Project Structure

The generated project will have the following structure:

project-name/
โ”œโ”€โ”€ .github/workflows/         # GitHub actions for CI/CD
โ”‚   โ”œโ”€โ”€ docs.yml               # Documentation building and testing
โ”‚   โ”œโ”€โ”€ tests.yml              # Code quality and testing
โ”‚   โ”œโ”€โ”€ release.yml            # Automated releases and publishing
โ”‚   โ””โ”€โ”€ update_rtd.yml         # Manual ReadTheDocs updates
โ”œโ”€โ”€ .vscode/                   # VS Code configuration
โ”‚   โ”œโ”€โ”€ settings.json          # Editor settings, linting, formatting
โ”‚   โ”œโ”€โ”€ launch.json            # Debug configurations
โ”‚   โ””โ”€โ”€ tasks.json             # Task definitions
โ”œโ”€โ”€ docs/                      # Sphinx documentation
โ”‚   โ”œโ”€โ”€ api/                   # Auto-generated API docs
โ”‚   โ”œโ”€โ”€ guides/                # User guides
โ”‚   โ”œโ”€โ”€ conf.py                # Sphinx configuration
โ”‚   โ””โ”€โ”€ index.md               # Documentation home
โ”œโ”€โ”€ src/package_name/          # Source code
โ”‚   โ””โ”€โ”€ __init__.py            # Package initialization
โ”œโ”€โ”€ tests/                     # Test directory
โ”œโ”€โ”€ scripts/                   # Release management scripts
โ”œโ”€โ”€ .env                       # Environment variables (if --local-env used)
โ”œโ”€โ”€ .gitignore                 # Git ignore rules
โ”œโ”€โ”€ .readthedocs.yaml          # ReadTheDocs configuration
โ”œโ”€โ”€ CLAUDE.md                  # Claude Code integration guide
โ”œโ”€โ”€ CredentialManagement.md    # Token management documentation
โ”œโ”€โ”€ LICENSE                    # MIT License
โ”œโ”€โ”€ Makefile                   # Development commands
โ”œโ”€โ”€ pyproject.toml             # Project configuration
โ”œโ”€โ”€ run.sh                     # Development task runner
โ””โ”€โ”€ README.md                  # Project documentation

Project Types

By default, generate-project creates an application project with a CLI entry point. Use the --library flag to create a library project instead:

# Create an application (default)
generate-project generate my-app

# Create a library
generate-project generate my-lib --library
Project Type CLI Entry Point main.py Use Case
Application Yes Yes CLI tools, scripts
Library No No Reusable packages, APIs

GitHub Repository Setup

The following options are available to setup a github repository for the project:

Option Description
--github Create a private github repository for the project
--public Create a public github repository for the project
--secrets Create repository secrets for the release management workflows

The following repository secrets can be automatically setup:

TEST_PYPI_TOKEN
PYPI_TOKEN
RTD_TOKEN

The tokens must be available in a .env file located in the directory where generate-project is executed or in any parent directory up the folder hierarchy. If no .env file is found, the application falls back to reading the tokens from environment variables.

Development Workflow

The generated project includes a Makefile with common development tasks:

# Environment Setup
make venv                 # Create and activate a local virtual environment
make install              # Install core dependencies
make install-dev          # Install all development dependencies

# Code quality
make format               # Run code formatters
make lint                 # Run linters
make check                # Run format + lint + tests on all files
make pre-commit           # Run format and lint only on changed files, then tests

# Testing
make test                 # Run tests
make test-cov             # Run tests with coverage
make coverage             # Generate coverage report

# Documentation
make docs-api             # Generate API documentation
make docs                 # Build documentation
make docs-live            # Start live preview server


# Release tasks will bump the version, create a new release and publish it
make release-major        # Create major release
make release-minor        # Create minor release
make release-micro        # Create micro (patch) release
make release-rc           # Create release candidate
make release-beta         # Create beta pre-release
make release-alpha        # Create alpha pre-release

Run make help for a complete list of the development tasks available.

Acknowledgments

This project was inspired by the GitHub workflows and automation ideas from phitoduck/python-course-cookiecutter-v2.

While this project is an independent implementation and a full Python application, the original repository provided valuable inspiration for the CI/CD and automation approach.

We thank the original authors for their contributions and ideas.

License

This project is released under the MIT License. See the LICENSE file for details.

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