paint-tracker 0.1.0

Paint and stain shelf tracker – self-updating, one-command deploy for Raspberry Pi

paint-tracker

Paint and stain shelf tracker with:

• FastAPI API
• SQLite auto-configured database (no setup required)
• React + Vite frontend bundled into the Python package
• Self-updating – checks PyPI for new versions on every start

---

🚀 One-click install on Raspberry Pi Zero 2 W

Run this single command on the Pi (requires Python 3.11+ and internet access):

bash <(curl -fsSL https://raw.githubusercontent.com/FlaccidFacade/paint-tracker/main/scripts/install_pi.sh)

The script will:

1. Install paint-tracker from PyPI.
2. Create and enable a systemd service that starts automatically on every boot.
3. Open port 8000 in the firewall (if ufw is active).
4. Print the local URL where the UI is reachable (e.g. http://raspberrypi.local:8000).

After installation, the tracker is accessible from any device on your network.

---

📦 Install from PyPI (any machine)

pip install paint-tracker
paint-tracker

On first launch Paint Tracker will:

• Check PyPI for a newer version and prompt you to upgrade.
• Auto-create the SQLite database at ~/.local/share/paint-tracker/paint_tracker.db.
• Start the web server on http://0.0.0.0:8000.

CLI options

paint-tracker --help

  --host HOST            Bind host (default: 0.0.0.0)
  --port PORT            Bind port (default: 8000)
  --no-update-check      Skip the PyPI update check on startup

---

🔧 Development setup

Backend

cd backend
pip install -r requirements.txt
pip install -e ..          # install paint_tracker package in editable mode
uvicorn paint_tracker.main:app --reload

DATABASE_URL defaults to ~/.local/share/paint-tracker/paint_tracker.db. Override for PostgreSQL:

export DATABASE_URL='postgresql+psycopg://user:password@localhost:5432/paint_tracker'

Run tests:

cd backend
pytest

Frontend (standalone dev server)

cd frontend
npm install
npm run dev

Optional API override:

export VITE_API_BASE_URL='http://localhost:8000/api'

---

📤 Publishing to PyPI

Build the frontend, bundle it into the Python package, and publish in one step:

pip install build twine
bash scripts/build_and_publish.sh          # publish to PyPI
bash scripts/build_and_publish.sh --test   # publish to TestPyPI

---

Included behavior

• Create paints with required room, shelf_level, shelf_depth
• Room suggestions while typing; new room names are saved automatically
• Search paints by room, color, and coordinates
• Edit existing paints from the list (✏️ button)
• Confirmation/decline controls use green check and red X buttons