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Showcase
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Rating display
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Home page
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House search page
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Landlord rate page
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Code Sneakpeak
💡 Inspiration 💡
With school returning to in-person classes for everyone. There are two things on every student's mind: Housing and Courses
Our team decided to combine two of the most important parts of university/college into one application. For many students, it is their first time dealing with properties and landlords. Some students end up taken advantage of by landlords or just end up with a very negative housing experience. A bad living situation could really affect student's performance during the school year and nobody wants that to happen to them. When finding a house for the school year, students often have to check multiple sites and sort through many different types of property listings. This can be really daunting for somebody living away from home for the first time. We took inspiration from the RateMyProf website which is a website for professor and course reviews that many students use yearly to plan out their courses for the school year. We also wanted to create a housing site created directly for students. Many students struggle to find housing each year and we believe our project can help alleviate some of the trouble.
❓ What it does ❓
RateMyLandlord (RML) is focused on created a similar experience to RateMyProf but for the student housing market. Instead of focusing on professors, it focuses on Landlords of properties around a school campus and the quality of their service and their listings. The site has a centralized database where students can search for landlords or rental housing. The criteria can be based on the landlord's name, the listing address, or even sorted by proximity to a specific school campus. Prior tenants are able to leave reviews of their experience with the landlords and their property, guaranteeing that students have a far easier time when searching for and signing a lease. We also hope that RML can aid students in making better financial decisions when it comes to renting houses.
🔨 How we built it 🔨
In terms of design, RateMyLandlord was created on Figma using the Iconify, Mapsicle and Clay Mockups 3D plugins. The logo was drawn in procreate.
On the frontend, RateMyLandlord is built with NextJS and Tailwind, using Axios and useSWR to interface with the backend (localhost)
On the backend, RateMyLandlord is built with Python, MongoDB, Flask, and various libraries that connect MongoDB and Python scripts.
💻 Challenges we ran into 💻
One of the first challenges we faced was creating responsive designs in Figma as well as working with auto-layout. As the design and front end team did not have much experience with this, it was quite challenging to learn on the spot.
We also struggled with establishing a connection to the MongoDB database
Setting up the REST API took some time but through trial and error we were able to figure out what was causing the HTTP errors
A huge issue was with the densely packed requirements of the frontend. David was the only frontend dev and so creating a dynamic fully flushed website was very difficult. Initially, we planned on faking much of the dynamic side, but David managed to squeeze it all out in the end! As a newer frontend dev, David didn't have much experience working with nextjs/tailwind, but with his previous react and css skills, learning it was a reasonable challenge!
🎉 Accomplishments that we're proud of 🎉
Creating a functioning Figma prototype and multiple mockups within the span of 2 days! Meeting and working with new teammates to develop a fullstack application in one short weekend! Learning new libraries and applications on the go! Creating a large scale, functional frontend in two days!
🏫 What we learned 🏫
Amy learnt how to work with responsive design and autolayout on figma as well as creating mockups of the website.
Matt learned how to work his way around a NoSQL database as well as become more comfortable working with REST APIs
David learnt/refined intermediate-high level nextjs and tailwind skills, as well as polishing up on some intricacies with dynamic scaling and AJAX requests.
❤️ How to Run Our Code ❤️
You may notice that the vercel hosted website is not connected to a back-end! You are correct, due to time constraints we were not able to host the backend live, therefore you'll have to run it locally to demo our project. (sorry about that!) To run it locally, sign into MongoDB Atlas using these creds: ratemylandlord12@gmail.com ratemylandlord12 access the database and connect to your local machine. Then, download the backend and: pip install -r requirements.txt. flask --app NewMethod/app.py run You should be good to go!
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