This FastAPI-based service provides access to student results, academic records, and backlog details. It integrates with PostgreSQL, Redis, and RabbitMQ for efficient data handling and messaging.

✅ Fetch all results for a student
✅ Retrieve academic records based on student ID
✅ Check backlogs (pending subjects)
✅ Uses Redis caching for optimized performance
✅ RabbitMQ integration for event-driven messaging
✅ Docker support for easy deployment

• Backend: FastAPI (Python)
• Database: PostgreSQL
• Caching: Redis
• Messaging Queue: RabbitMQ
• Containerization: Docker
• Monitoring: Prometheus, Grafana

The following diagrams illustrate the components and overall architecture of the FastAPI-based results service.

This diagram shows how different services interact in the system.

This diagram outlines the flow of requests and data within the system.

1. Prerequisites:

   Ensure you have Docker and Docker Compose installed.

2. Clone the repository:

   git clone https://github.com/thilakreddyy/jntuh-backend.git

3. Navigate to the project directory:

   cd jntuh-backend

4. Build and start the Docker containers:

   docker-compose up --build

   This command will build the Docker images and start the services defined in the docker-compose.yml file.

Once the application is running, access the API documentation at http://localhost:8000/docs. This interactive documentation provides details about each endpoint and allows you to test them directly.

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature/YourFeature).
3. Commit your changes (git commit -m 'Add YourFeature').
4. Push to the branch (git push origin feature/YourFeature).
5. Open a Pull Request.

This project is licensed under the GPL-3.0 .

Special thanks to all contributors and the open-source community for their invaluable support.