The nessie interface and Google now gave us the idea that we could use the rich source of location information to help suggest places to eat.

What it does

Based on your transaction location history, we map your transactions, create a heatmap of those transactions, and then use the Yelp API to ultimately recommend areas to eat in commonly visited places.

How I built it

We used Python for most of the backend. This includes querying the Capital One API to get the transaction history, and then querying the Yelp API to get the restaurants. We use Javascript to interact with the ESRI ArcGIS API to map the restaurants and to visualize the transaction heatmap. Finally, we use Python, PHP and SQLite to create a user account system that saves your bank information.

Challenges I ran into

We had a lot of issues with Cross-Origin-Requests because Flask didn't play well with those requests. We also had some issues figuring out how to do geospatial processing.

Accomplishments that I'm proud of

We finished everything we set out to do in less than we anticipated. We managed to figure out 3 APIs in the short time we were given.

What I learned

How to create a Flask server, how to map geospatial data using the ESRI ArcGIS API.

What's next for Pique

Recommending locations based on time of day, and upcoming events, too. Essentially, predicting into the future rather than just giving recommendations for now.

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