Weather Web Scraping

A desktop weather monitoring app that collects current observations from IMGW, stores them in PostgreSQL, and visualizes trends with interactive Plotly charts.

Features

• Fetches weather data from IMGW Synop endpoint.
• Stores records in PostgreSQL.
• Displays interactive charts for temperature, precipitation, wind, humidity, and pressure.
• Supports multiple time ranges (12h, 24h, 3 days, 7 days, 30 days, full history).
• Exports filtered data to downloaded.csv.

Tech Stack

• Python (Tkinter desktop UI)
• pandas
• requests + BeautifulSoup
• PostgreSQL (psycopg2)
• Plotly

Requirements

• Python 3.10+
• PostgreSQL
• uv

Setup (uv)

1. Install uv and sync environment from pyproject.toml:

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
uv sync

1. Create .env from the template:

Copy-Item .env.example .env

1. Edit .env and set your PostgreSQL credentials.
2. Create a PostgreSQL database (default from template: html).

Database Configuration (.env)

Use these variables in .env:

DB_HOST=localhost
DB_PORT=5432
DB_NAME=html
DB_USER=postgres
DB_PASSWORD=your_password
FETCH_INTERVAL_MINUTES=5

Run

uv run python app.py

Project Files

• app.py - Tkinter user interface.
• functions.py - scraping, database operations, filtering, plotting, CSV export.
• data.csv - latest downloaded source snapshot.
• downloaded.csv - user-exported filtered data.
• .env.example - environment variables template for local setup.

Data Source

IMGW public data: https://danepubliczne.imgw.pl/api/data/synop/format/html

License

This project is intended for educational use only. Licensed under the MIT License. See LICENSE for details.