A Cookiecutter template for generating production-ready FastAPI projects with machine learning, uv, GitHub Actions, and Pytest.
cookiecutter-fastapi is a Cookiecutter template that generates a complete, production-ready FastAPI project boilerplate. It automates the initial setup by providing a structured foundation with integrated tools for machine learning, dependency management, CI/CD, and testing. This solves the problem of repetitive project configuration, allowing developers to start building features immediately.
Python developers, especially those working with FastAPI, who need a quick, standardized way to bootstrap new projects with modern tooling. It's ideal for teams or individuals focusing on machine learning APIs or production web services.
Developers choose this template because it offers an opinionated, best-practice setup that includes essential tools like uv, GitHub Actions, and Pytest out of the box. It saves time, ensures consistency, and reduces configuration errors compared to manually setting up a FastAPI project from scratch.
Cookiecutter template for FastAPI projects using: Machine Learning, uv, Github Actions and Pytests
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Generates a complete FastAPI project with a standard directory structure and essential configurations, saving hours of manual setup.
Includes pre-configured dependencies and setup for machine learning workflows, making it ideal for data science teams building APIs.
Uses uv for fast package management and comes with GitHub Actions for CI/CD, ensuring efficient development and deployment out of the box.
Provides a configured Pytest suite, promoting reliable test execution and adherence to best practices from the start.
Lacks built-in authentication, database ORM integration, or frontend components, requiring additional manual setup for common web app needs.
Assumes familiarity with Cookiecutter, uv, and GitHub Actions, which can be a barrier for developers new to these modern Python ecosystems.
The opinionated structure and ML focus may introduce bloat for basic REST APIs, as not all projects need the full boilerplate.