ezEATS

Make a meat plan while saving money

Comment

Inspiration

As students, we wanted to generate a solution for efficient and convenient meal planning based on the weekly deals at the grocery store. The plan is to save people money and encourage people to try out new recipes at the same time.

What it does

In summary, the app combines web scraping, API integration, frontend and backend development, and database management to deliver a user-friendly platform for personalized meal recommendations, leveraging both user preferences and current grocery deals. Users can benefit from a streamlined approach to meal planning and grocery shopping, making the process more convenient and enjoyable.

How we built it

The app was built using React for the frontend, Django for the backend, Firebase for the database, and Python for web scraping. It integrates the Edamam API to offer personalized meal recommendations based on scraped data from weekly grocery flyers. The development process included setting up environments, creating an intuitive UI with React, implementing backend logic with Django, and deploying on suitable platforms. The app enhances meal planning by combining modern web technologies, real-time data, and user-friendly interfaces.

Challenges we ran into

Web scraping complications - As it turns out, websites don't usually love it when Python scrypts are run to read and extract the content of its source code. This led us to having several grocery websites block us from gathering the data we were after (Walmart, Loblaws, ...)

API call limitations - As non paying users, we were informed personnally by a rep from Edamam API that we had exceeded the limit of API calls for a free user by 300%. This was not shocking considering the large dataset we were trying to produce for the backend of our application.

Firebase datase Read limits - Limits to daily read limits from Firebase database slowed down our progress tremendously as we were unable to see anything from our Database for the rest of the day.

Accomplishments that we're proud of

-Learning web app development with React and Django -Modelling a solution that is meaningful to us and we believe can help people. -Rendering a successful pre release product.

What we learned

-Web app development with React front end and Django back end -Web scrapping scrypt with Python -Integrating API into web applications for research and data production -Javascript coding in general -Planning and executing a tech project from start to finish.

What's next for ezEATS

-Expand the operation to store the data from many grocery stores to go worldwide. -Implement more functionalities to our web app. Accounts for users to save liked recipies, self updating database for the new flyers every week.

Share this project:

Updates