JenOce888/living-memory-cameroon

INF232 EC2 — Data collection and descriptive analysis application. An application to archive oral testimonies, myths/legends/proverbs, and medicinal plant knowledge collected from Cameroonian elders. # Living Memory of Cameroon **INF232 EC2 — Data collection and descriptive analysis application** An application to archive oral testimonies, myths/legends/proverbs, and medicinal plant knowledge collected from Cameroonian elders. ## Features - Collect historical testimonies (text + audio recording) - Collect oral histories: myths, legends, proverbs, folktales, traditions - Collect medicinal plants (description + photo + usage context) - Store elder profiles with explicit consent tracking - Descriptive statistics dashboard (charts by region, ethnic group, period, language) - Search across all records ## Tech stack - **Backend**: Python + Flask + SQLAlchemy - **Database**: SQLite (local) / PostgreSQL (production on Render) - **Media storage**: Cloudinary (audio, photos) - **Analysis**: Pandas - **Deployment**: Render.com (free tier) ## Run locally ```bash # 1. Install dependencies pip install -r requirements.txt # 2. Create your environment file cp .env.example .env # Edit .env with your Cloudinary credentials # 3. Start the app python app.py # Open localhost ``` ## Deploy on Render 1. Push this project to a GitHub repository 2. Go to render.com → "New Web Service" → connect your repo 3. Render will detect render.yaml automatically 4. Add your CLOUDINARY_* variables in the Render dashboard (Environment tab) 5. Deploy — Render gives you a public URL to send to your professor