Stockket

Checking availabilities in stores for the products you want.

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Inspiration

We realized that panic buying and social distancing due to the novel coronavirus made it harder for a community to find their needs, whether that be medical supplies or groceries. We wanted to build an app that would support a community together during this pandemic.

What it does

Stockket is a user friendly app that is on Android, iOS, and web, that takes in a user’s Facebook profile to authenticate and log in, and share alerts between people around them. Alerts include alerting if a certain grocery item is in stock at a certain store or requesting items from people willing to donate.

How we built it

We built it primarily with a React Native frontend and a Python backend. We also used Google Cloud Platform and Firebase to handle our authentication/account services, as well as Google Maps API.

Challenges we ran into

Challenges we ran into ran to were how to design a user friendly app and using real world packages. We wanted to make an app that would be useful. With very little experiences in mobile development and little exposure to how services worked, a lot of time was spent towards learning and debugging.

Accomplishments that we're proud of

We’re proud of making something functional in the end, given the short amount of time and experience we were given. In the end, we’re proud that we found each other through random encounters before the hackathon started and we each had a unique experience. Some of them being, a teammate’s first hackathon, a first virtual hackathon, and hackathon members collaborating from different parts of the world.

What we learned

Learned that it’s not easy to implement an integrated frontend and backend. Considering that all members are university students, we were never really formally taught how to build a full stack app. But it was fun learning and collaborating with our individual skill sets.

What's next for Stockket

Improve the user experience with a stronger backend. We could implement a stronger backend with our university knowledge in machine learning, artificial intelligence, or data science. This would create a more predictable and optimized experience for an individual user using this app. Also, since this is a web application, the use case could even be expanded to people in need and in situations of a developing country.

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