Global MLH Hackathon Winner

Written by Usman Khan

My team and I learned that 45% of college students report experiencing some form of food insecurity at school. As a college student, finding foods and keeping healthy meal plans that provide significant amounts of nutrition can be sometimes difficult, especially with the mental bandwidth of college coursework and other commitments. My team and I decided that LunchMoney would be an initiative in the right direction. The premise of this app is to find the most nutritional foods that fit under a given budget by the user. To customize further, the user decides which nutritional categories they want to maximize and minimize in their search results.

This project was submitted and won a Global MLH Hackathon in June of 2022 for 2 categories.

Features:

• The user inputs their budget, food query, and nutritional preferences which sends a request to the built-in web scraper to scrape Target.com.
• User is able to select the nutrition that they want to maximize (such as protein, fiber, carbohydrates, etc.) and those they want to minimize (sugar, sodium, fats, etc.)
• Returns the best food item that fits the user's preferences and budget.
• Displays a nutrition facts label to show the nutritional information for the food the program found to fit the user's preferences.
• Provides the amount of money saved if the item is below the user’s entered budget.
• Provides a link to the specific item’s Target.com page.

Technologies:

• Python (Programming Language) - the backend is developed entirely using Python
• Flask (Framework) - the application handles requests and web page management with Flask
• BeautifulSoup - library used to retrieve and scrape data from Target.com
• Selenium - package used to automate web browser interaction from Python
• RegEx - used to filter through web scrape to retrieve item name, price, link, and nutrition info
• HTML (Scripting Language) - frontend/webpage was built using HTML