A Python-Based Real Estate Rental Application for Students: Leveraging Open Data and Visualization to Enhance Housing Decisions

The growing demand for accessible and affordable housing for students has highlighted the need for innovative solutions in real estate applications tailored to the academic community. This paper presents a student-led approach in the development of a real-estate renting app specifically designed for current or future students who plan to study at universities in Timisoara. The app prototype utilizes Python and open-source technologies to create a user-friendly platform that simplifies the process of finding suitable rental options. By addressing key challenges faced by students-such as affordability, location proximity to campuses, and ease of use-the prototype offers a cost-effective solution for student housing. This work establishes a practical model for future innovations in student-focused real estate applications, showcasing how a collaborative, frugal approach can drive impactful technology development.