Fapid Rest 🚀

A minimal, flexible and pragmatic FastAPI template to kickstart REST API development. Designed for prototyping, PoCs, internal tools, and dev utilities — with a strong foundation but without unnecessary complexity.

Note

⚠️ If you need something more robust for large-scale, production-ready services with full DDD, CQRS, or event-driven architectures — consider other templates.
fapid-rest is made for speed, clarity, and developer happiness 🚀

Overview

Service : A concrete service class defines the API of an external Service. Model : Defines the applications data model. Controllers : Where all the routes lives in API REST.

MCS stands for Model-Controller-Service. I don't want to bloater all with a lot of Clases, Wrappers or huge complexity, just simple and minimaslitic. Think of it like MVC — but:

• 🧠 Easier to reason about.
• 📁 Organized folder structure
• 🧪 Ideal for rapid PoC creation.
• ⚒️ Minimal setup. Easy to scale or swap in prod later.

Perfect when you want to start lean but keep your codebase clean.

🧰 Tech Stack

• FastAPI – Python’s async web framework for high-performance APIs.
• Pydantic - Data validation using Python type hints.
• SQLModel – Type-safe SQL layer, blending SQLAlchemy and Pydantic.

✨ Features

• 🧱 Clean and simple MCS architecture
• 🗂️ Predefined folder structure by Domain: fapid_rest/user, fapid_rest/item
• 🐳 Dockerized for local dev and deploy
• 🧪 Basic test setup with pytest
• 🧹 Linting and formatting via ruff
• 📦 Dependency management with pip-tools
• ⚡️ Powered by uv for fast Python execution
• 🐣 Project management with hatch

📦 Installation (Recommended with pipx)

pipx is a tool to install and run Python CLI apps in isolated environments — safely and globally.

Instead of polluting your global Python environment with packages like hatch, uv, or black, pipx creates a virtual environment per tool, then exposes the CLI to your $PATH.

Why Use pipx?

pipx is like nvm or rustup, but for Python CLI tools.

• 🔒 Isolated
• 🧼 Clean
• 🔁 Reproducible
• 💨 Fast when paired with uv

1. Zero conflicts across projects

   Installing CLI tools globally with pip can easily cause version conflicts. pipx keeps each tool isolated — no conflicts, no surprises.

2. Python version friendly

   Want to use Python 3.11 for uv, 3.10 for hatch? pipx supports that with:

3. Reproducibility + portability

   You can pin and install the same versions of tools across machines or CI pipelines, ensuring your dev environment is predictable.

4. Uninstalls cleanly pipx uninstall hatch deletes the tool and its virtualenv cleanly — no residuals in your system.

Here's a one-liner to install modern Python tooling that works across all your projects:

pipx install hatch uv pip-tools --python python3.11

Create virtual environment

# with hatch
hatch env create
# with uv
uv venv --python 3.11

Compile requirements

uv pip compile requirements/requirements.in -o requirements/requirements.txt
uv pip install -r requirements/requirements.txt

Setup database

docker compose up -d

Run the app

hatch run dev