VdE is a Django-based web interface designed for local community energy users (e.g., residents of an apartment building or housing cooperative). It enables residents to monitor real-time and historical energy consumption and solar production, view shared/common loads for the building, and manage access via authentication.

• Real-time dashboard: per-user consumption and production
• Shared/common facilities view: communal consumption and production
• Historical data visualization (daily/weekly/monthly) and export
• User authentication and profile management
• Pages: dashboard, graphs, calendar, groups, profile
• Cassandra-backed time-series storage (configurable)

Energy data can be sensitive. This project follows these principles:

• Restrict access with authentication
• Store minimal personal data and allow anonymization/aggregation for communal views
• Encourage secure production settings (HTTPS, secret management)

• Python 3.10
• pip
• Access to a Cassandra instance (or a local/test mode)

1. Create and activate a virtual environment:

python3.10 -m venv .venv
source .venv/bin/activate

1. Install dependencies:

pip install -r requirements.txt

1. Configure Cassandra credentials:

• Edit or create cassandra_serv_credentials.json with host/port/username/password, or adapt vde_interface/cassandra_db.py to your environment.

Apply migrations (if any) and start the development server:

python manage.py migrate
python manage.py runserver 0.0.0.0:8000

Open http://localhost:8000 in your browser.

• manage.py — Django management script
• requirements.txt — project dependencies
• vde_interface/ — main Django app
  • cassandra_db.py — Cassandra helper
  • views.py, urls.py, settings.py — application code and configuration
• templates/ — HTML templates (dashboard, graphs, login, profile)
• static/ — CSS and image assets
• cassandra_serv_credentials.json — example credentials (DO NOT commit secrets)

• Disable DEBUG and manage secrets via environment variables or a secret manager
• Use HTTPS and standard security headers (HSTS, CSP)
• Serve behind a reverse proxy (nginx) and an application server (gunicorn/uvicorn)
• Consider Docker for reproducible deployments and provide a docker-compose example

Contributions are welcome. Suggested workflow:

1. Fork the repository
2. Create a feature branch
3. Add tests and documentation for your changes
4. Open a pull request with a clear description

• Add unit and integration tests for critical views and data handling
• Provide a sample dataset and a local Cassandra/Docker configuration for testing
• Add a deployment guide (Docker + nginx)

This project is licensed under the MIT License — see ../LICENSE.md.

Open an issue for bugs, feature requests, or questions.