Inspiration

Being a student I wanted to buy the best products at the least price available among the nearest grocery stores and SAVE MONEY!

What it does

This web application compares and categorizes my list of groceries to be bought into sublists and suggests the stores wherever each item is cheapest.

How I built it

We used Bootstrap, AJAX, JQuery for front end. We used Python, Flask, REST APIs & Machine Learning algorithms to identify buying patterns or Market-Basket analysis and suggest missing items to be bought.

Challenges I ran into

Using APIs to get grocery stores datasets. Connecting Google Cloud SQL to my external application.

Accomplishments that I'm proud of

-> We learnt to use Flask on top of Python and build GUIs. -> Brainstorming several ideas and implementing the best one in 24-hr crunch time under complete stress.

What I learned

-> Learnt to overcome all hurdles and complete the project on time. -> Learnt using Google Cloud SQL and Google cloud platform.

What's next for SmartGrocList-PearlHacks2020

-> Building mobile app for SmartGrocList similar to this web application. -> Using Image Classification to suggest items based on image scan. -> Using Image to Text Detection on scanned images of sticky notes/white board checklist. -> Adding additional cool features to the app.

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