Inspiration
As car enthusiasts, we have watched our friends and family struggle to decide the car they want. Everyone knows what they want from a car, but as modern cars get increasingly complex, it takes hours of intensive research to find a perfect car. It's a process that can be streamlined, and save millions of combined hours for millions of customers. We wanted to offer our knowledge about cars in the form of a web application that asks simple questions, yet thanks to our multivariate algorithm, the app compares hundreds of cars and outputs 6 cars that fit your needs.
What it does
Our algorithm takes into account user's preferences for a car, such as: budget, make, body type, required capacity, mileage, fuel, etc. It assigns a weightage to each of those attributes and assigns a score to each car in our database. It outputs the cars that scored the highest based on user input.
How we built it
We used python and Flask for the backend server, and react plus javascript for the front end. We were originally going to create SQL lite database for storing all the cars. But due to time constraints we stored cars into a list of dictionaries, with each dictionary being a single car.
Challenges we ran into
It took some fine tuning to get the algorithm to behave correctly, we had to change the weightage for each attributes so we can penalise cars that don't fit user's needs. No one in our team knew how to use flask, and we had limited experience with javascript.
After getting import errors that seemed unsolvable we got frustrated gave up on our project, and decided we were gonna make a chrome extension that would be less complicated than a car recommendation app. But we hit few road blocks while scraping websites for chrome extension. So went back to drawing board for car recommendation app and coded all Saturday night, it was brutal but we made it to the other side.
Accomplishments that we're proud of
We are proud of our front end design, and how fast our app works. We added unique images to every car as well for our results page.
What we learned
We learned flask, got proficient in java script. Learned the challenges involved in creating a full stack web application. It was just as hard as everyone told us and some more.
What's next for Drivvu
We would like to add more cars, more attributes, better algorithm to deliver even better results.



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