sarabablal/Weather-Scraper-for-Solar-Wind-Forecasting

Weather Scraper for Solar/Wind Forecasting retrieves live weather data from Open-Meteo API for Ouarzazate, Morocco. It captures temperature, wind speed, and direction, and appends them to a Pandas DataFrame and CSV file for machine learning and clean energy modeling. ## Weather Scraper for Solar/Wind Forecasting An automated Python script designed to harvest real-time meteorological data for renewable energy forecasting. This tool queries the Open-Meteo API to extract critical weather parameters for Ouarzazate, Morocco, and continuously appends the structured data into a local CSV file for machine learning and energy yield modeling. ### Features * Live API Data Extraction: Pulls real-time temperature, wind speed, wind direction, and WMO weather codes. * Geotargeted Tracking: Hardcoded to monitor coordinates (30.93, -6.91)—highly relevant for solar/wind energy analysis in Ouarzazate. * Persistent Storage: Automatically structures the JSON payload and appends new logs to a weather_data.csv database without overwriting historical data. * Data-Science Ready: Outputs data directly into a Pandas DataFrame, making it immediately ready for feature engineering and predictive analysis. ### Captured Parameters * timestamp: Precise ISO 8601 measurement time. * temperature: Ambient temperature in °C (critical for solar PV efficiency tracking). * wind_speed: Local wind velocity in km/h. * wind_degree: Wind direction vector in degrees (0-360°). * weather_code: WMO Weather interpretation code for cloud cover and precipitation status. ### Tech Stack * Language: Python 3.x * Data Handling: Pandas * Networking: Requests API ### Getting Started Install the required libraries using pip: pip install pandas requests ### Data Output Preview Your data will compile inside weather_data.csv in the following format: | timestamp | temperature | wind_speed | wind_degree | weather_code | |---|---|---|---|---| | 2026-08-30T20:00 | 28.5 | 12.4 | 190 | 0 |