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Python library used by Home Assistant to interact with the WeatherFlow REST API

Project description

WeatherFlow4Py

A Python library for interacting with the WeatherFlow REST API and WebSocket services. This library provides both synchronous and asynchronous interfaces to access weather data from WeatherFlow weather stations.

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Features

  • REST API Client: Access station data, forecasts, and observations
  • WebSocket Client: Real-time weather data updates
  • Type Annotations: Full type support for better development experience
  • Asynchronous Support: Built with asyncio for efficient I/O operations
  • Pydantic Models: Strongly-typed data models for all API responses

Installation

pip install weatherflow4py

Or with uv:

uv pip install weatherflow4py

Prerequisites

Quick Start

REST API Example

import asyncio
from weatherflow4py.api import WeatherFlowRestAPI

async def main():
    # Initialize the API with your token
    async with WeatherFlowRestAPI("YOUR_API_TOKEN") as api:
        # Get all available stations
        stations = await api.async_get_stations()
        
        for station in stations.stations:
            print(f"Station: {station.name}")
            print(f"Location: {station.latitude}, {station.longitude}")
            
            # Get current observations
            obs = await api.async_get_observation(station.station_id)
            print(f"Current temperature: {obs.obs[0].air_temperature}°C")
            
            # Get forecast
            forecast = await api.async_get_forecast(station.station_id)
            print(f"Forecast high: {forecast.forecast.daily[0].air_temp_high}°C")

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

WebSocket Example

import asyncio
import logging
from weatherflow4py.ws import WeatherFlowWebsocketAPI

# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

async def main():
    # Initialize the WebSocket client
    ws = WeatherFlowWebsocketAPI("YOUR_API_TOKEN")
    
    # Define callback functions for different message types
    def handle_observation(data):
        print(f"Observation received - Temp: {data.air_temperature}°C")
    
    def handle_rapid_wind(data):
        print(f"Wind speed: {data.wind_speed} m/s at {data.wind_direction}°")
    
    # Register callbacks
    ws.register_callback("obs_st", handle_observation)
    ws.register_callback("rapid_wind", handle_rapid_wind)
    
    try:
        # Start listening for messages
        await ws.connect()
        
        # Start listening to all available devices
        await ws.start_listening()
        
        # Keep the connection alive
        while True:
            await asyncio.sleep(1)
            
    except KeyboardInterrupt:
        print("Disconnecting...")
    finally:
        await ws.disconnect()

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

API Documentation

REST API

The WeatherFlowRestAPI class provides the following methods:

  • async_get_stations(): Get all stations associated with the account
  • async_get_observation(station_id): Get current observations for a station
  • async_get_forecast(station_id): Get forecast data for a station
  • async_get_device_observations(device_id): Get observations from a specific device
  • get_all_data(): Get all available data for all stations

WebSocket API

The WeatherFlowWebsocketAPI class provides real-time updates:

  • connect(): Establish WebSocket connection
  • disconnect(): Close the connection
  • start_listening(device_ids=None): Start listening for updates
  • stop_listening(device_ids=None): Stop listening for updates
  • register_callback(message_type, callback): Register a callback for specific message types

Error Handling

The library raises specific exceptions for different error conditions:

  • TokenError: When no API token is provided
  • APIError: For general API errors
  • WebSocketError: For WebSocket connection issues

Rate Limiting

  • REST API: Limited to 100 requests per minute
  • WebSocket: Follows WeatherFlow's rate limiting policies

Resources

Development

This project uses uv for dependency management and virtual environment creation.

Setup with Nix

If you have Nix installed with flakes enabled:

# Enter the development environment
nix develop

# This will automatically:
# 1. Create a virtual environment with uv
# 2. Install dependencies from requirements.txt and requirements-dev.txt
# 3. Install the project in development mode

Manual Setup with uv

# Create a virtual environment
uv venv

# Activate the virtual environment
source .venv/bin/activate

# Install dependencies
uv pip install -r requirements.txt
uv pip install -r requirements-dev.txt

# Install the project in development mode
uv pip install -e .

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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

Acknowledgments

  • WeatherFlow for their excellent weather station hardware and API
  • All contributors who have helped improve this library

Support

For support, please open an issue on the GitHub repository.

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