Dandy Hacks 2018: Whip
Overview
Hosted at the University of Rochester, Dandy Hacks is an annual hackathon lasting for 36 hours. Students are allowed to create anything that they want. However, the companies sponsoring the event incentivize students to explore and utilize their technologies by offering awards and prizes aside from the main prizes.
The idea
The vision was to provide uber and lyft drivers with some sort of way to plan their schedules out ahead of time by assisting them in predicting surge pricing before it even happens.
Data scraping
I created a python script which takes in an airport code such as ROC for Rochester International Airport and scrapes an online database for information on all incoming future flights(Typically 2-3 days in advance). We were mostly focused on the date and time of arrival. This data was presented very neatly into a graph.
Marrying Lyft's and Google Place's API
Originally we wanted to target both Lyft and Uber, however due to Uber's API limitation and restrictions we only focused on Lyft. Another useful aspect of Whip was assessing a driver's competition in a particular area. This was accomplished utilizing Google places and Lyft's API. Using Google places we were able to find nearby airports and their geo-coordinates. Using Lyft's API, we requested the location of nearby drivers and mapped them on a Google Map. These locations were updated around every minute.
Final thoughts
Our goal was not to provide a magical surge pricing predictor, that what completely out of the time scope. Instead we focused on collecting data, and presenting that data in the best way that we possibly could. The conclusions that each driver would draw would be their own. Allowing driver to plan out their schedule ahead of time in a way to be at surge pricing locations as they became public.