This project demonstrates a FastAPI application using Beanie ODM (Object Document Mapper) for MongoDB. The project is containerized using Docker and Docker Compose for easy setup and deployment.

• app/server/models/product_review.py: Defines the ProductReview and UpdateProductReview models using Beanie and Pydantic.
• app/server/routes/product_review.py: Contains the API routes for handling product reviews.
• app/server/app.py: The main FastAPI application setup, including route inclusion and database initialization.
• app/server/database.py: Contains the database initialization logic.
• main.py: The entry point for running the Uvicorn server.
• Dockerfile: The Dockerfile for building the FastAPI application image.
• docker-compose.yml: Docker Compose file for setting up the FastAPI and MongoDB services.
• requirements.txt: Python dependencies required for the project.

• Docker Desktop installed and up and running on your machine.

1. Clone the repository:

   git clone https://github.com/SaadARazzaq/Product-Reviews-API
   cd fastapi-beanie

2. Build and start the Docker containers:

   docker-compose up --build

3. The FastAPI application will be available at http://localhost:8000.

{
    "name": "Saad Abdur Razzaq",
    "title": "MacBook Air M2",
    "rating": 5.0,
    "review": "Best Laptop in the world",
    "date": "2023-06-30T12:34:56.789Z"
}

{
    "name": "Taha Abdur Razzaq",
    "title": "HP Victus 16",
    "rating": 5.0,
    "review": "Worst Laptop in the world",
    "date": "2023-06-30T12:34:56.789Z"
}

• Ensure MongoDB is running and accessible for the FastAPI application to function correctly.
• The mongo_url in app/server/database.py is set to connect to a MongoDB instance at host.docker.internal.

This project was made with 💖 by Saad Abdur Razzaq