added notebook investigating boiler power usage

README.md

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+# Home Assistant Data Analysis
+
+Data analysis notebooks for investigating power consumption and other smart home metrics collected by Home Assistant.
+
+## Project Structure
+
+```bash
+.
+├── .gitea/
+│   └── workflows/
+│       └── setup_database.yml    # CI workflow to setup PostgreSQL database
+├── notebooks/
+│   └── boiler_warning.ipynb      # Power consumption analysis notebook
+├── utils/
+│   ├── __init__.py
+│   └── db_connection.py          # Shared database connection utilities
+├── .env.example                   # Example environment variables
+├── .gitignore
+├── pyproject.toml                # Project dependencies and configuration
+└── README.md
+```
+
+## Setup
+
+### 1. Install UV (Python Package Manager)
+
+```bash
+# macOS/Linux
+curl -LsSf https://astral.sh/uv/install.sh | sh
+
+# Or via Homebrew
+brew install uv
+```
+
+### 2. Create Virtual Environment and Install Dependencies
+
+```bash
+# Create and activate virtual environment with UV
+uv venv
+source .venv/bin/activate  # On macOS/Linux
+
+# Install dependencies
+uv pip install -e .
+```
+
+### 3. Configure Database Connection
+
+```bash
+# Copy example environment file
+cp .env.example .env
+
+# Edit .env with your PostgreSQL credentials
+nano .env  # or use your preferred editor
+```
+
+### 4. Run Jupyter Notebooks
+
+```bash
+# Start Jupyter Lab
+jupyter lab
+
+# Or Jupyter Notebook
+jupyter notebook
+```
+
+## Database Setup
+
+The repository includes a CI workflow (`.gitea/workflows/setup_database.yml`) that can be manually triggered to initialize the PostgreSQL database. Ensure the following secrets are configured in your Gitea repository:
+
+- `POSTGRES_HOST`
+- `POSTGRES_PORT`
+- `POSTGRES_ROOT_PASSWORD`
+- `DB_NAME`
+- `DB_USER`
+- `DB_PASSWORD`
+
+## Notebooks
+
+### Current Notebooks
+
+- **boiler_warning.ipynb**: Analysis of power consumption data from Home Assistant
+
+### Adding New Notebooks
+
+1. Create new notebook in the `notebooks/` directory
+2. Use descriptive names (e.g., `temperature_trends.ipynb`, `energy_efficiency.ipynb`)
+3. Import shared utilities: `from utils import get_db_connection, get_db_engine`
+
+## Shared Utilities
+
+The `utils/` module provides common functions for database connections:
+
+```python
+from utils import get_db_connection, get_db_engine
+
+# Using psycopg2 (for raw SQL)
+conn = get_db_connection()
+cursor = conn.cursor()
+cursor.execute("SELECT * FROM states LIMIT 10")
+
+# Using SQLAlchemy (for pandas integration)
+engine = get_db_engine()
+import pandas as pd
+df = pd.read_sql("SELECT * FROM states LIMIT 10", engine)
+```
+
+## Development
+
+### Optional Development Tools
+
+Install development dependencies for code formatting and linting:
+
+```bash
+uv pip install -e ".[dev]"
+```
+
+Format code with Black:
+
+```bash
+black utils/
+```
+
+Lint code with Ruff:
+
+```bash
+ruff check utils/
+```
+
+## Contributing
+
+When adding new analysis notebooks:
+
+1. Document the purpose and findings in the notebook
+2. Add any new dependencies to `pyproject.toml`
+3. Update this README if adding significant new functionality