VeggieBuddy

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  VeggieBuddy

Inspiration

The inspiration behind our project, VeggieBuddy, came from our own experiences with food choices. As vegetarians, we often struggle to find good restaurants that cater to our needs when eating out. Many restaurants either don’t clearly state that they offer vegetarian options or list them in places that are hard to find. We realized this was a common problem and decided to do something about it.

What it does

VeggieBuddy is an application designed to help users easily find vegetarian restaurants. You input your dietary preference and cuisine, and it shows you restaurants that match it. No more guessing or endless scrolling through reviews and menus.

How we built it

We used Python with Selenium to scrape the websites, and Flask to build the REST APIs. For the frontend, we chose ReactJS with TypeScript.

Challenges we ran into

One of the main challenges we faced was budget-related, rather than technical. We originally planned to support dynamic location detection so that users could open the app from anywhere and see nearby matching restaurants. However, due to the high cost of the Google API, we had to limit our scope to the Manhattan area and work with a sample of 100 restaurants.

Accomplishments that we're proud of

Some things we are proud of include making this project possible in such a short time despite many constraints. We both had events running through the weekend, yet we managed to put it together.

What we learned

We learned how to work together effectively, despite not having known each other for long, and in the process, we built a new friendship. We also learned how to integrate multiple APIs and platforms to create a functional product. Finally, we gained valuable experience in frontend development and explored techniques for creating a clean and modern UI.

What's next for VeggieBuddy

For VeggieBuddy, the next steps include creating user profiles to save dietary preferences and favorite spots. We will also use dynamic location mapping using Google Places API. In the long term, we hope to integrate machine learning to personalize suggestions based on user behavior and feedback about restaurants.

Built With

• css
• flask
• google-directions
• html
• python
• typescript