🌦️ WeatherFlow: Multi-Platform Weather Data Forwarding

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🌟 Overview

WeatherFlow is a modern, Dockerized Python solution that effortlessly transfers your Personal Weather Station (PWS) data from Weather Underground to multiple platforms including Windy and idokep.hu. Leverage the power of APIs and cloud computing to ensure your weather station's data is accurately reflected on multiple platforms, where it can contribute to global and regional weather monitoring.

This project is built with scalability and flexibility in mind, allowing you to configure update intervals and station-specific details with ease. Whether you're a tech enthusiast, a data geek, or a professional meteorologist, WeatherFlow is your go-to solution for seamless weather data integration.

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🚀 Features

• Dockerized for Simplicity: Run in a containerized environment for consistent performance across platforms
• Multi-Platform Support: Send data to both Windy and idokep.hu simultaneously
• Modular Architecture: Clean, maintainable codebase with separate modules for each provider
• Configurable Update Intervals: Set your own data update frequency (Windy minimum: 5 minutes)
• Robust Error Handling: Comprehensive logging and error handling for reliability
• Scalable: Easily deploy multiple instances for managing multiple PWS stations

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📁 Project Structure

weatherflow/
├── src/
│   ├── __init__.py
│   ├── config.py              # Configuration management
│   ├── main.py                # Application entry point
│   └── providers/
│       ├── __init__.py
│       ├── weather_underground.py  # WU data fetcher
│       ├── windy.py               # Windy publisher
│       └── idokep.py              # Idokep.hu publisher
├── docker-compose.yml
├── Dockerfile
├── requirements.txt
└── readme.md

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🛠️ Setup

Prerequisites

• Docker
• Docker Compose

Installation

1. Clone the Repository:

   git clone https://github.com/LavX/weatherflow.git
   cd weatherflow

2. Configure Environment Variables: Update the docker-compose.yml with your own values:

   environment:
     # Required - Weather Underground
     - WU_PWS_ID=your_pws_id_here
     - WU_API_KEY=your_weather_underground_api_key_here
     
     # Required - Windy
     - WINDY_API_KEY=your_windy_api_key_here
     - WINDY_STATION_ID=0
     
     # General settings
     - UPDATE_INTERVAL=300
     
     # Optional - Idokep.hu
     - IDOKEP_ENABLED=false
     - IDOKEP_USER=your_idokep_username
     - IDOKEP_PASS=your_idokep_password
     - IDOKEP_STATION_TYPE=PWS
     - IDOKEP_PRO=false
     - IDOKEP_UTC=1

3. Build and Run:

   docker-compose up -d --build

4. Check Logs:

   docker-compose logs -f

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⚙️ Configuration Reference

Required Variables

Variable	Description
WU_PWS_ID	Your Weather Underground PWS station ID
WU_API_KEY	Your Weather Underground API key
WINDY_API_KEY	Your Windy API key
WINDY_STATION_ID	Your Windy station ID (default: 0)

General Settings

Variable	Description	Default
UPDATE_INTERVAL	Update interval in seconds	300 (5 minutes)

Idokep.hu Settings (Optional)

Variable	Description	Default
IDOKEP_ENABLED	Enable idokep.hu integration	false
IDOKEP_USER	Your idokep.hu username	-
IDOKEP_PASS	Your idokep.hu password	-
IDOKEP_STATION_TYPE	Station type (e.g., PWS, WS2305, Netatmo)	PWS
IDOKEP_PRO	Use pro.idokep.hu for data archiving	false
IDOKEP_UTC	Time format: 1 = UTC, 0 = Central European	1

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🇭🇺 Idokep.hu Integration

WeatherFlow supports sending weather data to idokep.hu, a popular Hungarian weather service.

Prerequisites

1. Register at idokep.hu (basic registration is sufficient)
2. For data archiving, register at pro.idokep.hu

Data Mapping

Parameter	Description	Unit
hom	Temperature	°C
rh	Relative humidity	%
harmatpont	Dewpoint	°C
szelirany	Wind direction	degrees
szelero	Wind speed	m/s
szellokes	Wind gust	m/s
p	Sea-level pressure	hPa
uv	UV index	-
csap1h	1-hour precipitation	mm

Notes

• Temperature/Dewpoint 0°C: Automatically reported as 0.1°C (idokep.hu API limitation)
• Time Format: Default is UTC (IDOKEP_UTC=1). Set to 0 for Central European local time
• Pro vs Regular: Use IDOKEP_PRO=true for pro.idokep.hu with data archiving

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🌍 Example Usage

VEVOR 7-in-1 Wi-Fi Weather Station

• Weather Underground: PWS Dashboard
• Windy: PWS on Windy

Docker Commands

# Build and start
docker-compose up -d --build

# View logs
docker-compose logs -f

# Stop service
docker-compose down

# Restart service
docker-compose restart

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🔧 Development

Running Locally (without Docker)

# Install dependencies
pip install -r requirements.txt

# Set environment variables
export WU_PWS_ID=your_pws_id
export WU_API_KEY=your_api_key
export WINDY_API_KEY=your_windy_key
# ... other variables

# Run
python -m src.main

Requirements

• Python 3.14+
• requests >= 2.32.5

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📄 License

Licensed under the MIT License - see LICENSE file for details.

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📫 Contact

Questions? Open an issue or reach out via GitHub.

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WeatherFlow - Delivering precise and reliable weather data across platforms ☁️🌧️🌤️

Crafted with ❤️ by LavX