2f15fbb752
``_target_to_response`` in ``api/routes/output_targets.py`` used to be
an isinstance ladder over the three OutputTarget subclasses with a
silent fallback that fabricated a ``LedOutputTargetResponse`` for
unknown types (audit finding H3). The fallback masked exactly the
kind of bug we hit on the CSS side in Phase 1.1: a new target subclass
slipped past the ladder and got mis-shaped on the wire.
Replace the ladder with a ``_TARGET_RESPONSE_BUILDERS`` dict keyed by
the concrete subclass plus an import-time
``_assert_target_response_coverage()`` that requires the registry to
exactly match ``{WledOutputTarget, HALightOutputTarget,
Z2MLightOutputTarget}``. ``_target_to_response`` now raises
``RuntimeError`` instead of silently fabricating a LED response for an
unknown subclass — coverage is asserted at import so this branch is
unreachable in normal operation.
Tests: 5 new regression tests cover bijection between expected classes
and registered builders, callable shape, the rogue-target-raises
contract, and missing/extra entry rejection in the assertion. 24
existing output-target tests stay green; ruff clean.
LedGrab - Server
High-performance FastAPI server that captures screen content and controls WLED devices for ambient lighting.
Overview
The server component provides:
- 🎯 Real-time Screen Capture - Multi-monitor support with configurable FPS
- 🎨 Advanced Processing - Border pixel extraction with color correction
- 🔧 Flexible Calibration - Map screen edges to any LED layout
- 🌐 REST API - Complete control via 25+ REST endpoints
- 💾 Persistent Storage - JSON-based device and configuration management
- 📊 Metrics & Monitoring - Real-time FPS, status, and performance data
Quick Start
Option 1: Docker (Recommended)
# Start server
docker-compose up -d
# View logs
docker-compose logs -f
# Stop server
docker-compose down
Server runs on: http://localhost:8080
Option 2: Python
# Create virtual environment
python -m venv venv
# Activate
source venv/bin/activate # Linux/Mac
venv\Scripts\activate # Windows
# Install dependencies
pip install .
# Set PYTHONPATH
export PYTHONPATH=$(pwd)/src # Linux/Mac
set PYTHONPATH=%CD%\src # Windows
# Run server
uvicorn ledgrab.main:app --host 0.0.0.0 --port 8080
Installation
Requirements
- Python 3.11+ (for Python installation)
- Docker & Docker Compose (for Docker installation)
- WLED device on your network
See ../INSTALLATION.md for comprehensive installation guide.
Configuration
Configuration File
Edit config/default_config.yaml:
server:
host: "0.0.0.0"
port: 8080
log_level: "INFO"
processing:
default_fps: 30 # Target frames per second
max_fps: 60 # Maximum allowed FPS
border_width: 10 # Pixels to sample from edge
wled:
timeout: 5 # Connection timeout (seconds)
retry_attempts: 3 # Number of retries
storage:
devices_file: "data/devices.json"
logging:
format: "json"
file: "logs/ledgrab.log"
Environment Variables
# Server configuration
export LEDGRAB_SERVER__HOST="0.0.0.0"
export LEDGRAB_SERVER__PORT=8080
export LEDGRAB_SERVER__LOG_LEVEL="INFO"
# Processing configuration
export LEDGRAB_PROCESSING__DEFAULT_FPS=30
export LEDGRAB_PROCESSING__BORDER_WIDTH=10
# WLED configuration
export WLED_WLED__TIMEOUT=5
Usage
WLED Device Setup
Important: Configure your WLED device using the official WLED web interface before connecting it to this controller:
- Access WLED Interface: Open
http://[wled-ip]in your browser - Configure Device Settings:
- Set LED count and type
- Configure brightness, color order, and power limits
- Set up segments if needed
- Configure effects and presets
This controller only sends pixel color data - it does not manage WLED settings like brightness, effects, or segments. All WLED device configuration should be done through the official WLED interface.
API Documentation
- Web UI: http://localhost:8080 (recommended for device management)
- Swagger UI: http://localhost:8080/docs
- ReDoc: http://localhost:8080/redoc
Quick Example
# 1. Add device
curl -X POST http://localhost:8080/api/v1/devices \
-H "Content-Type: application/json" \
-d '{"name":"Living Room","url":"http://192.168.1.100","led_count":150}'
# 2. Start processing
curl -X POST http://localhost:8080/api/v1/devices/{device_id}/start
# 3. Check status
curl http://localhost:8080/api/v1/devices/{device_id}/state
Testing
# Run all tests
pytest
# Run with coverage
pytest --cov=ledgrab --cov-report=html
# Run specific test
pytest tests/test_screen_capture.py -v
Development
Project Structure
src/ledgrab/
├── main.py # FastAPI application
├── config.py # Configuration
├── api/ # API routes
├── core/ # Core functionality
│ ├── screen_capture.py
│ ├── wled_client.py
│ ├── calibration.py
│ └── processor_manager.py
├── storage/ # Data persistence
└── utils/ # Utilities
Code Quality
# Format code
black src/ tests/
# Lint code
ruff check src/ tests/
License
MIT - see ../LICENSE