Inspiration

We were initially inspired by Wayfair's prompt to help low-income students find affordable housing. We had many social issues that we wanted to address, but this one particularly grabbed our attention because all of our teammates personally experienced newfound struggles with our housing situations when the COVID-19 pandemic arose.

What it does

It stores data from both subletters (sellers of listings) and tenants (potential buyers of listings) by allowing them to sign up and input a wide variety of relevant data (including logistical data like name and age, as well as housing-related data like preferred location, preferred price range, etc.). There's also a map that helps users navigate current listings.

How I built it

We used Github and Virtual Studio Code as the coding environments. We used HTML, CSS and Javascript for the front-end. We used Python, Javascript, and SQL for the back-end.

Challenges I ran into

It was the first time that we used most of these languages and environments, so there was a huge learning curve in understanding how to install these programs and in implementing the syntax. This was mostly apparent in our inability to integrate SQL effectively for database management. Consequentially, we struggled in planning accordingly for how to create a fully functioning website in the limited time we had.

Accomplishments that I'm proud of

We learned so much code! We also managed to make a website that works where users can navigate without using forward and back arrows. We also were proud of our ability to connect front-end and back-end, without any members having prior experience.

What I learned

We learned all the programs and languages listed above, as well as how to better manage our time during these hackathon sprints.

What's next for room.

Our website will publicly display our data for anyone, regardless of having signed up or not, to view in order to create a platform whereby buyers can easily find available listings, and sellers can easily find potential buyers. This data would be filterable by the users. Our website will also display a heat-map that helps visually present the data regarding listings, especially price and location.

Share this project:

Updates