Brooklyn's coffee shops have a variety of artisanal coffee shops, some charging $5 for a 16 oz cup of coffee and some for $2. Often times the price of the coffee is not an indicator of the quality, freshness, and taste.
What it does
Users can select their coffee preferences such as price range (avg price per cup) and more, gathering an overall measurement of how users like their coffee. Once the user goes through their preferences and signs up they get greeted by the dashboard.
How We built it
We used the MERN(MongoDB Express React Node) stack to get CRUD operations on our users' and roasters. Passwords are encrypted via bcrypt, an industry-standard hashing technique, and never revealed. We used JSON Web Tokens to allow logging and logout sessions and protect routes so that only authenticated users can view privileged data (dashboard).
Challenges We ran into
The development came with a few challenges including CORS, filtering criteria and react state management. Every hurdle came with its valuable lessons. Thankfully we were able to get through most roadblocks by the end of our hour sprint and talk it through in our standup.
Accomplishments that We're proud of
We are proud to have followed a modified agile development methodology and got though 11 one hour sprints, each with a 5-minute standup between. As sprints went on, we honed our focus and kept on iterating on the user's perspective, implementing user-centered design.
What's next for Local Roasters
Local roasters will be continually updated and developed into a react-native app. Many other features include:
- Checking in, and updating Roasters' info (ie coffee price)
- Setting dynamic prices for specific drinks
- Allow users to set how they take their coffee and calculate the price with milk
- In-app map visualization, Roaster gallery, and distance estimation.