-
Interactive ESG Leaderboard
Real-time ranking of top performers with drill-down capabilities and year-over-year tracking -
Advanced Analytics
Industry benchmarking, regional comparison, and trend forecasting -
Environmental Metrics
Carbon emissions, resource efficiency, and energy consumption monitoring -
Financial Integration
ESG-financial correlation analysis with market performance indicators -
Smart Filtering
Multi-dimensional data filtering with custom thresholds and industry-specific views
📦 Python 3.11+
📦 Node.js 18+
📦 MongoDB (Atlas or local)
📦 Git
# Create virtual environment
python -m venv .venv
.venv\Scripts\activate # Windows
source .venv/bin/activate # Mac/Linux
# Install dependencies
pip install -r backend/requirements.txt
# Configure environment
cd backend
cp .env.example .env
# Edit .env with your MongoDB URI and secret key
# Run server
python app.py
# Backend runs on http://localhost:5000cd frontend
npm install
# Configure environment
cp .env.example .env
# Set VITE_API_URL=http://localhost:5000
# Run dev server
npm run dev
# Frontend runs on http://localhost:5173Frontend
React 18 • Vite • Tailwind CSS • Framer Motion • Recharts
Backend
Flask • Flask-CORS • JWT Auth • Flask-Mail • Flask-PyMongo
Database
MongoDB Atlas
Analytics
Pandas • NumPy
DevOps
Docker • GitHub Actions
esg_score_predictor/
├── backend/
│ ├── app/ # Flask blueprints & extensions
│ ├── app.py # Development entry point
│ ├── wsgi.py # Production entry point
│ ├── Dockerfile # Container configuration
│ └── requirements.txt
├── frontend/
│ ├── src/ # React components
│ ├── public/ # Static assets
│ └── package.json
├── data/ # Sample CSV datasets
├── notebook/ # Analysis notebooks
└── LICENSE
- High-level ESG metrics, sustainability leaderboard, KPIs, and financial impact analysis
- Sector-wise comparisons, resource efficiency metrics, and competitive benchmarking
- Geographic distribution, compliance tracking, and regional trends
- Historical data visualization, predictive insights, and performance forecasting
cd backend
docker build -t esg-backend .
docker run -e PORT=5000 -e MONGO_URI="your-mongo-uri" -p 5000:5000 esg-backendMONGO_URI=your_mongodb_connection_string
SECRET_KEY=your_secret_key_here
PORT=5000
SMTP_HOST=your_smtp_host
SMTP_PORT=587
SMTP_USER=your_email
SMTP_PASSWORD=your_passwordVITE_API_URL=http://localhost:5000python app.py # Development server
gunicorn -b 0.0.0.0:5000 wsgi:app # Production servernpm run dev # Development server
npm run build # Production build
npm run preview # Preview production build
npm run lint # Run ESLintContributions are welcome! Please follow these steps:
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
This project is licensed under the MIT License. See the LICENSE file for details.
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