Flight Data Enrichment System

A system for managing, enriching, and visualizing flight data. It features both Django and FastAPI backends, background task processing with Celery, and a dashboard for monitoring. The project is containerized with Docker and uses SQLite for development.

Technologies Used

• Python 3.10+
• Django (web framework, dashboard, admin)
• Django REST Framework (API for Django)
• FastAPI (async API)
• Celery (background task processing)
• SQLite (development database)
• Redis (Celery broker and result backend)
• Poetry (Python dependency management)
• Docker & Docker Compose (containerization)

Prerequisites

• Docker and Docker Compose installed (Install Docker)
• Git installed (Install Git)
• (Optional) Poetry for Python dependency management (Install Poetry)

Local Setup

1. Clone the repository:

   git clone https://github.com/vgarcia13/ff-flight-data-enrichment-system.git
   cd ff-flight-data-enrichment-system
   

2. Copy and configure environment variables:

   cp .env.example .env

   Edit .env to set your environment variables.

3. Build and start the containers:

   docker compose up --build

4. Access the applications:

   • Flight API Browser: http://localhost:8000/api/
   • FastAPI: http://localhost:8080/docs
   • Dashboard (Flights): http://localhost:8000/dashboard/flights/
   • Dashboard (Completed Tasks): http://localhost:8000/dashboard/tasks/

Testing the API

Using Postman

• Import the API endpoints (Django: /api/, FastAPI: /docs) into Postman.
• For Django endpoints, use http://localhost:8000/api/.
• For FastAPI endpoints, use http://localhost:8080/.
• Send requests (e.g., POST /enrich-flight, GET /task-status/{task_id}) and inspect responses.

Using Django REST Framework API Browser

• Open http://localhost:8000/api/ in your browser.
• Browse available endpoints, submit requests, and view responses interactively.

Author

Victor Garcia <https://github.com/vgarcia13>