Phill Good

Inspiration

Initially, we were interested by the promise of the crime database in helping people stay safe. However, as we progressed through the development of the application, we realized that there were so many other databases that could be equally helpful for different people. Thus, we thought we could provide the city of Philadelphia with a one stop solution to everything from healthy eating, to public safety, to recreation.

What it does

With the simple entry of a street address, Phill Good will instantaneously provide you with a map of the city showing you the nearest city resources and facilities.

How we built it

Phill Good was built with several data files provided by OpenDataPhilly. We gathered data in the form of .csv files, which were them placed into databases using SQLite3. Our website was built using JavaScript, HTML, CSS, Flask, Python and Jinja2. The user's search data initiates a python script that analyzes relevant data and alters the website with needed information. The Google Map uses the Google Map API to illustrate the data.

Challenges we ran into

Less than 5 hours before the deadline, there was an issue with the github cache, and it resulted in our database being deleted accidentally. This significantly hindered our progress in the final hours and hurt our ability to polish the final product. We did pull together and clean up the front end, but it is still not quite where we want it to be.

Accomplishments that we're proud of

We are particularly proud of our ability to implement the Google Map API so effectively. We did not expect to be using the API early on in our development, and we only looked into it in the final hours. However, it's functionality and aesthetic still pleased us greatly.

What we learned

This was the first time using Python, Flask, SQLite and Jinja for some of our team members. Furthermore, it is the first time our team has worked with such large sets of data, and processing and analyzing it proved to be an interesting and challenging experience.