Tigo Python API Wrapper

A modern, open-source Python library for interacting with the Tigo Energy API.

Features

• 🔑 Automatic authentication with credentials from environment
• 📊 Raw API access and convenient DataFrame helpers
• ⚡ Built-in rate limiting and error handling
• 🧪 Well-tested with comprehensive test suite
• 📈 Advanced analytics including system efficiency and panel performance
• 🛡️ Type hints for better development experience

Installation

From PyPI (when published)

pip install tigo_python

From GitHub

pip install git+https://github.com/matt-dreyer/tigo_python.git

Development Installation

git clone https://github.com/matt-dreyer/tigo_python.git
cd tigo-python
pip install -e ".[dev]"

Quick Start

1. Set up credentials

Create a .env file in your project root:

TIGO_USERNAME=your_username
TIGO_PASSWORD=your_password

Or set environment variables:

export TIGO_USERNAME=your_username
export TIGO_PASSWORD=your_password

2. Basic usage

from tigo_python import TigoClient

# Credentials loaded automatically from environment
with TigoClient() as client:
    # Get your systems
    systems = client.list_systems()
    system_id = systems["systems"][0]["system_id"]
    
    # Get current performance
    summary = client.get_summary(system_id)
    print(f"Current power: {summary['summary']['last_power_dc']} W")
    
    # Get historical data as DataFrame
    df = client.get_today_data(system_id)
    print(df.head())

3. Advanced analytics

# System efficiency analysis
efficiency = client.calculate_system_efficiency(system_id, days_back=30)
print(f"System efficiency: {efficiency['average_efficiency_percent']:.1f}%")

# Panel performance comparison
panel_perf = client.get_panel_performance(system_id)
print(panel_perf.head())

# Find underperforming panels
problems = client.find_underperforming_panels(system_id, threshold_percent=85)
for panel in problems:
    print(f"Panel {panel['panel_id']}: {panel['efficiency_percent']:.1f}% efficiency")

API Coverage

Core Endpoints

• ✅ Authentication - Login/logout with token management
• ✅ Users - User information and preferences
• ✅ Systems - List systems, get details and layouts
• ✅ Sources - Hardware sources and configurations
• ✅ Objects - System components and hierarchy
• ✅ Data - Combined and aggregate data endpoints
• ✅ Alerts - System alerts and notifications

Data Formats

• Raw API responses - Direct JSON from Tigo API
• CSV strings - For integration with other tools
• Pandas DataFrames - For data analysis and visualization

Error Handling

The library provides specific exceptions for different error scenarios:

from tigo_python.exceptions import TigoAPIError, TigoAuthenticationError

try:
    client = TigoClient("wrong_user", "wrong_pass")
except TigoAuthenticationError as e:
    print(f"Login failed: {e}")
except TigoAPIError as e:
    print(f"API error: {e}")

Rate Limiting

The library automatically handles API rate limits by:

• Limiting data requests to safe time ranges (≤20,150 minutes)
• Using appropriate data resolution (minute/hour/day) based on time span
• Providing helpful warnings when requests are adjusted

Development

Setup

git clone https://github.com/matt-dreyer/tigo_python.git
cd tigo-python
pip install -e ".[dev]"

Running Tests

pytest tests/ -v

Code Quality

# Linting
ruff check tigo_python/

# Type checking  
mypy tigo_python/

# Formatting
ruff format tigo_python/

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes with tests
4. Ensure code quality checks pass
5. Submit a pull request

Requirements

• Python ≥ 3.8
• httpx ≥ 0.27.0
• pandas ≥ 2.0.0
• numpy ≥ 1.24.0

Acknowledgments

This project is inspired by the Rust tigo client by @mrustl.

License

MIT License - see LICENSE for details.

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This library is not affiliated with or endorsed by Tigo Energy.