project-setup

To bootstrap a Python project, this tool automates creating directory structures, configuration files like pyproject.toml, and CI/CD pipelines. It integrates Ruff, MyPy, and Pytest to enforce best practices from the start.

Yes, you can generate boilerplate for specific types including data pipelines, ML projects, web APIs, and Python libraries. The scaffolding adapts directory layouts and configurations to fit your chosen project type.

Setting up a Python project includes generating pyproject.toml, .env.example, Dockerfile, and a Makefile. These files provide standardized configuration for dependencies, environment variables, and common development tasks.

Python project scaffolding supports FastAPI web APIs by generating necessary folders, pyproject.toml with FastAPI dependencies, a basic main.py, config.py, Dockerfile, and a Makefile for streamlined development.

The best way to integrate Ruff and MyPy is through automated project initialization, which configures these linters and type checkers alongside Pytest within your pyproject.toml during the scaffolding process.

Automated scaffolding saves significant development time by instantly creating a standardized, production-ready Python project structure with best practice CI/CD pipelines, ensuring robust configurations from the outset.