fastapi-mongo-setup 0.3.2

A CLI tool to auto-generate MongoDB connection boilerplates for FastAPI projects.

fastapi-mongo-setup 🚀

Stop writing MongoDB boilerplate for FastAPI! fastapi-mongo-setup is a fast, lightweight Python CLI tool that instantly scaffolds a professional, industry-standard FastAPI + MongoDB project structure. It generates async DB connections, Pydantic settings, and a fully functional CRUD router in one command.

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⚡ Installation

Install globally or within your virtual environment:

pip install fastapi-mongo-setup

🛠️ Usage

Navigate to the root of your empty (or existing) FastAPI project and run:

mongo-setup

What does this command do?

Instantly, it generates the following modular architecture:

fastapi-project/
├── .env                   # Auto-populated with MONGODB_URL and DATABASE_NAME
├── requirements.txt       # Dependencies (fastapi, motor, pydantic-settings, etc)
├── main.py                # FastAPI entry point with MongoDB Lifespan logic
└── src/
    ├── config.py          # Configuration loader using Pydantic Settings
    ├── utils/             # Database core
    │   ├── db.py          # Asynchronous Motor connection manager
    │   └── helpers.py     # MongoDB ObjectId Serialization helpers
    └── tasks/             # Complete pre-built API module
        ├── router.py      # GET/POST/DELETE endpoints
        ├── schemas.py     # Pydantic validation models
        └── service.py     # Database CRUD logic

🚀 Running Your Generated Project

Once the files are created, just install the dependencies and start the built-in demo server!

# 1. Install required packages
pip install -r requirements.txt

# 2. Run the server
python main.py

Go to http://localhost:8000/docs to see your automatically generated Swagger UI with a fully functional Tasks API connected to your MongoDB!

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🏗 Why this exists?

Setting up Motor (the async MongoDB driver) with FastAPI usually requires copy-pasting code to handle connections, lifespans, and fixing ObjectId serialization errors. This minimalist tool does all of that for you, providing a clean abstraction layer and a modular structure designed for scaling.

🤝 Contributing

Found a bug or want to request a feature? Feel free to open an issue or submit a pull request!