In this thesis, we present the development of a prototype web application for analyzing the real estate market in Ljubljana. The application collects and stores real estate data daily by scraping information from a real estate listing website. It allows users to search for properties, view price history, compare listings, and perform statistical analysis of the market. The thesis includes a review of existing solutions, identifying core functionalities, descriptions of the used technologies, system architecture, and implementation. The frontend was built using the Angular framework, the backend with Node.js, and MySQL was used as the database. Data scraping was implemented in Python using the Selenium library. Finally, the application was evaluated through a potential user survey.
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