Omari Wallace attended Fullstack Academy in 2014, and he told us about what convinced him to join the Fullstack program, how he pushed through tough times, and what he created for his final project (hint: think Tinder for Cheap Eats).
What were you up to before deciding to go to Fullstack?
I worked as a project consultant for a private equity firm.
Did you apply to other schools? Why did you ultimately choose Fullstack?
Can you talk about a time when you got stuck in the class and how you pushed through?
Getting stuck was a daily occurrence, and I considered it a hallmark of the learning process taking effect. But one that sticks out in my mind was for my final individual project where I was implementing functionality with the Google Calendar API. I was attempting to chain a sequence of functions that would add an event to a user's calendar; but I kept on receiving an error response. I ended up refactoring almost every line of code in the module, added a ton of console.log's to debug every line of code, and added a linter to make help catch any syntactical issues. After taking some time to step away from the code and re-read the documentation, I discovered that it was a simple capitalization issue for the query I was making of the API.
All in all it was a valuable exercise in debugging and I ended up with cleaner code than when I had initially started -- but it was a lesson in the importance of attention to detail that won't soon be forgotten.
Tell us about your final project!
The project that I was most excited building was done with a fellow student during the final 2 weeks of Fullstack and we call it The Hunger Game -- which can be succinctly described as the "Tinder" for cheap food.
The technologies we used to build the project included the MEAN stack (MongoDB, Express, AngularJS, Node.js), the Foursquare API, the GoogleMaps API, Firebase and the HTML5 Geolocation API.
Here's how it works: Users are presented with an interactive slideshow of restaurants from foursquare filtered by proximity, lowest price (only one "$" out of four), and being open at the time of gameplay. Users can vote up or down on restaurants by swiping on the images during a 30 second round. Upon conclusion of a round, users are presented with a winning restaurant that is chosen at random from their selections (or provided a random choice from the entire pool if no selections were made). For multiplayer mode, users are aggregated in "rooms" based on their geolocated proximity and the voting system tallies votes amongst all users in the room. After all participants end their round, they are presented with the choice that received the most votes.