Weather information is one of the most frequently accessed categories of data in everyday life. Despite the widespread availability of weather applications on smartphones and the web, there remains a notable gap in the availability of dedicated, desktop-grade, Python-based weather monitoring tools that integrate real-time data with local analytical capabilities, air quality reporting, and persistent data management. This paper presents the design, architecture, and implementation of a GUI-Based Weather Dashboard developed using the Python programming language, the Tkinter graphical user interface framework, and the OpenWeatherMap API for real-time meteorological and air quality data retrieval. The proposed system provides users with a comprehensive view of current atmospheric conditions, including temperature, humidity, wind speed, atmospheric pressure, and a textual weather description. Additionally, the dashboard incorporates an Air Quality Index (AQI) monitoring module, a dynamic temperature trend visualization graph rendered using the Matplotlib library, a live digital clock, and an automated data refresh mechanism. The system further supports Excel-based data import and export functionality using the OpenPyXL library, enabling users to maintain historical weather logs for analysis and reporting. Evaluation of the system across multiple test scenarios demonstrates low API response latency, high data accuracy when compared against official meteorological benchmarks, and an intuitive user experience validated through structured usability assessment. The paper also discusses the three-tier architectural model, security considerations including API key management and data privacy, and potential avenues for future enhancement, including machine learning-based weather forecasting integration.
Maurya et al. (2026) studied this question.