Inspiration
Too often, our team has faced the issue of having our groceries go bad because there were simply no places for them in the meals us or our families were cooking. Two days before PrideHacks started, we brainstormed issues that have been affecting our daily lives, and stumbled upon the problem of rotten groceries. While it may be a minor issue to some, it could be a catastrophic event for others. The solution to groceries going bad? 🔥Let Them Cook.
What it does
🔥Let Them Cook is a web app designed to help people of different demographics reduce produce waste by suggesting meals to make out of them. The user enters the ingredients (vegetables, fruits, proteins, etc.) they currently have, and 🔥Let Them Cook recommends recipes that the user can recreate. This encourages exploring different cuisines and styles of cooking, and using the groceries you have at home.
How we built it
We built the project using a Next.js frontend with components built using ChakraUI. On the backend, we employed Python for web scrapers that would allow us to build our recipes database hosted on MongoDB. We then created endpoints using Flask to communicate with the frontend.
Challenges we ran into
On the frontend, handling state management in React was an initial hurdle that we had to learn on the fly. We also had to overcome a learning curve when it came to MongoDB, since none of us were familiar with it. Using a cloud-native database for the first time required a lot of patience, energy, and knowledge.
Accomplishments that we're proud of
We were able to design an intuitive UI that was successfully translated to a working frontend. We were also able to create effectively designed web scrapers that allowed us to build our database with MongoDB.
What we learned
We learned a lot about state management and using UI libraries such as ChakraUI on the frontend. On the backend, learning more about the use of MongoDB in addition to building web scrapers was a major focus for the team.
What's next for Let Them Cook
We're hoping to build a more robust endpoint system that can fully handle all of the application's needs. We also wanted to expand the frontend and backend to include more features that we weren't able to implement such as taking photos to identify what ingredients you have that would have been implemented using OpenCV.
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