gecko-iot-client-community 0.4.0

Community fork of the Gecko IoT client with fixes & extensions for the Home Assistant integration

🦎 Gecko IoT Client (Community Fork)

A modern, asynchronous Python client library for Gecko IoT devices with AWS IoT integration. Control and monitor your Gecko-powered spas, hot tubs, and pool equipment with ease.

Community fork. Published to PyPI as gecko-iot-client-community to track community-driven fixes (e.g. Gecko's June 2026 cloud migration, Waterlab support) without colliding with the upstream gecko-iot-client package. The import name remains gecko_iot_client, so application code is unchanged. Upstream: geckoal/gecko-iot-client.

✨ Features

• 🌐 AWS IoT Integration: Secure MQTT communication via AWS IoT Core
• 🏊 Multi-Zone Control: Temperature, lighting, and flow zone management
• 📡 Real-time Updates: Event-driven state synchronization
• 🔄 Async/Await Support: Modern Python async programming patterns
• 🛡️ Type Safety: Full type hints and mypy compatibility
• 📊 Comprehensive Logging: Detailed debug and monitoring capabilities
• 🧪 Well Tested: Extensive test suite with code coverage
• 📖 Rich Documentation: Auto-generated API docs and examples

🚀 Quick Start

Installation

pip install gecko-iot-client-community

Basic Usage

import asyncio
from gecko_iot_client import GeckoIotClient
from gecko_iot_client.transporters.mqtt import MqttTransporter

async def main():
    # Create MQTT transporter with your AWS IoT endpoint
    transporter = MqttTransporter(
        endpoint="wss://your-endpoint.iot.region.amazonaws.com/mqtt",
        device_id="your-device-id"
    )

    # Initialize client
    client = GeckoIotClient(idd="your-device-id", transporter=transporter)

    async with client:
        # Get all temperature control zones
        temp_zones = client.get_zones_by_type(ZoneType.TEMPERATURE_CONTROL_ZONE)

        for zone in temp_zones:
            print(f"Zone {zone.name}: {zone.temperature}°C (target: {zone.target_temperature}°C)")

        # Control lighting
        lighting_zones = client.get_zones_by_type(ZoneType.LIGHTING_ZONE)
        if lighting_zones:
            light = lighting_zones[0]
            await light.activate()  # Turn on
            await light.set_color(255, 0, 0)  # Set to red

if __name__ == "__main__":
    asyncio.run(main())

🏗️ Architecture

Zone Types

The client supports three main zone types:

• 🌡️ Temperature Control Zones: Heater and temperature management
• 💡 Lighting Zones: LED lighting control with color support
• 🌊 Flow Zones: Pump and circulation control

Event System

def on_temperature_change(zone, old_temp, new_temp):
    print(f"Temperature changed from {old_temp}°C to {new_temp}°C")

client.register_zone_callbacks(lambda zone_name: on_temperature_change)

📁 Project Structure

gecko-iot-client/
├── .github/workflows/     # CI/CD pipelines
├── gecko_iot_client/      # Main package
│   ├── src/              # Source code
│   │   └── gecko_iot_client/
│   │       ├── models/   # Data models and zone types
│   │       └── transporters/  # Communication layers
│   ├── tests/            # Test suite
│   ├── docs/             # Sphinx documentation
│   └── examples/         # Usage examples
└── README.md             # This file

🛠️ Development

Prerequisites

• Python 3.13+
• Poetry (recommended) or pip

Setup

# Clone the repository
git clone https://github.com/geckoal/gecko-iot-client.git
cd gecko-iot-client

# Install dependencies
cd gecko_iot_client
pip install -e ".[dev,docs]"

# Run tests
pytest tests/ --cov=gecko_iot_client

# Format code
black src/ tests/
isort src/ tests/

# Build documentation
sphinx-build docs/source docs/build/html

# Generate changelog from git history
./scripts/generate-changelog.sh
# or using the Python entry point
gecko-build-changelog

Running Examples

# Run the demo script
python gecko_iot_client/examples/demo.py

📚 Documentation

• 📖 Full Documentation - Complete API reference and guides
• 🎯 Quick Start Guide - Get up and running fast
• 🔧 Configuration - Setup and configuration options
• 💡 Examples - Code examples and use cases

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

Development Workflow

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Add tests for new functionality
5. Ensure all tests pass (pytest)
6. Commit your changes (git commit -m 'Add amazing feature')
7. Push to the branch (git push origin feature/amazing-feature)
8. Open a Pull Request

📊 Testing & Quality

• ✅ Automated Testing: GitHub Actions run tests on every push and PR
• 📈 Code Coverage: Monitored via SonarCloud with detailed quality reports
• 🔍 Code Quality: SonarCloud analysis with Black, isort, and flake8 for consistent style
• 📝 Documentation: Auto-generated and deployed on every release

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

• 🐛 Issues: GitHub Issues
• 💬 Discussions: GitHub Discussions

🏷️ Versioning Strategy

This project follows Semantic Versioning (SemVer) combined with PEP 440 for Python compatibility.

Version Format

MAJOR.MINOR.PATCH[-PRERELEASE]

• MAJOR: Breaking changes (incompatible API changes)
• MINOR: New features (backward-compatible functionality)
• PATCH: Bug fixes (backward-compatible fixes)

Git Tag Format

All releases use the v prefix in git tags:

# Release versions
v1.0.0          # Major release
v1.1.0          # Minor release
v1.1.1          # Patch release

# Pre-release versions
v1.0.0-alpha.1  # Alpha release
v1.0.0-beta.1   # Beta release
v1.0.0-rc.1     # Release candidate

Release Lifecycle

Stage	Git Tag Example	PyPI Version	Purpose
Alpha	v0.1.0-alpha.1	0.1.0a1	Early development, internal testing
Beta	v0.1.0-beta.1	0.1.0b1	Feature complete, external testing
Release Candidate	v0.1.0-rc.1	0.1.0rc1	Final validation before release
Stable Release	v0.1.0	0.1.0	Production ready
Patch Release	v0.1.1	0.1.1	Bug fixes only
Minor Release	v0.2.0	0.2.0	New features, backward compatible
Major Release	v1.0.0	1.0.0	Breaking changes

Version Detection

Versions are automatically determined from git tags using setuptools-scm:

import gecko_iot_client
print(gecko_iot_client.__version__)  # e.g., "0.1.0a2.post1"

Version Components:

• 0.1.0a2 - Alpha version 2 of release 0.1.0
• .post1 - 1 commit after the tagged release
• +dirty - Local uncommitted changes (development builds)

Release Process

1. Development happens on the develop branch
2. Tagging creates releases: git tag v0.1.0-alpha.3 && git push origin v0.1.0-alpha.3
3. GitHub Actions automatically builds and publishes to PyPI
4. Documentation is automatically updated and deployed

🏷️ Version History

See CHANGELOG.md for a detailed version history.

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