This project provides the backend for afetharita.com, a platform for disaster relief coordination and information sharing. It serves as a central API for managing aid requests, volunteer coordination, and resource allocation during emergencies, targeting developers and organizations involved in disaster response.

How It Works

The backend is built using Python with the Django framework, leveraging PostgreSQL for data persistence and Redis for asynchronous task management via Celery. It utilizes AWS services like Elastic Load Balancer, ECS, and Fargate for deployment and scalability. OpenAI is integrated for image-to-text conversion, likely to process visual information related to disaster sites or needs.

Quick Start & Requirements

• Installation: Docker is recommended for development and is used in production.
• Prerequisites: Docker, PostgreSQL, Redis, Python with Poetry.
• Setup: Run docker-compose up --build -d for full setup. For development, docker-compose up -d postgres redis starts the database and cache. Install Python dependencies with poetry install.
• Configuration: Copy .env.template to .env and set environment variables including database credentials, Django secret key, and OpenAI API keys.
• Running: Use django-admin runserver for the Django development server and celery -A trquake.celery.app worker -B -l DEBUG for Celery tasks.

Highlighted Details

• Backend for afetharita.com, accessible at https://api.afetharita.com.
• Utilizes Django, PostgreSQL, Redis, AWS (ELB, ECS, Fargate), and OpenAI.
• Poetry is used for Python dependency management.
• Includes commands for database migrations, superuser creation, static file collection, and running the development server.

Maintenance & Community

The project is part of the acikyazilimagi organization, which appears to be involved in open-source disaster relief initiatives. Further community and maintenance details are not explicitly provided in the README.

Licensing & Compatibility

The README does not specify a license. Compatibility for commercial use or closed-source linking is not detailed.

Limitations & Caveats

The README mentions that running the latest Redis version directly on Windows may not work, recommending WSL with Docker as the best option. Specific details on API rate limits, data privacy, or security measures are not included.