Moo-ney Meals

Plan Less. Save More. Moo-ney Meals gives you the specific ingredients and total cost for a given recipe at your store of choice.

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Inspiration

College students face lots of barriers to cooking. From working on a tight budget to fighting a tight schedule, making home meals is often out of reach. Moo-ney Meals is here to help, finding in-budget meals and recipes with groceries available in nearby stores. Moo-ney meals empowers people from all walks of life to take control of their time, health, and budget.

What it does

  • Lets users enter their weekly budget to ensure they cannot go over budget while choosing meals for the week
  • Generates recipes from different cuisines that the user can choose from
  • Makes a grocery list based on the meals chosen, so the user does not have to spend time looking for what ingredients they need and how much it would cost
  • Calculates the total cost of buying all the ingredients for the meal(s) picked
  • Saves the recipe(s) chosen to refer back to for instructions

Moo-ney Meals is essentially a one-stop website for cooking, especially for people on a budget.

How we built it

After agreeing on the idea, our group decided that building a website would be our best medium to launch Moo-ney Meals based on our experience and background. We assigned each individual responsibility for different parts of the project. Princess designed the overall layout of the website on Figma after the team discussed the most important functionality features, which include the cuisine filter, recipes, and the grocery list. After finishing the basic layout, she continued to expand on the features of the website, which helped other team members visualize while they worked on implementing the actual website using HTML, CSS, and Javascript. Carolyn then turned the prototype into a working website using HTML and CSS. Some functionalities she implemented include the navigation bar, the tutorial page, and other design aesthetics. Ruston used Javascript to make API calls to Spoonacular and Kroger APIs, which enabled the functionality to search for recipes based on cuisine or natural language search terms. He then developed the logic to track ingredients and prices across recipes, and format them for on-page display. Hanran wrote code to make API calls to Kroger to pull grocery data which allows price calculation for dishes and grocery lists. He developed a prototype to calculate the amount of ingredients needed to satisfy customers’ needs to make selected dishes and to build the overall grocery list.

Challenges we ran into

  • Learning the ins and outs and procedures for participating in a hackathon
  • Feeling confident about the progress in our project
  • Translating design layout into a functional website using HTML, CSS, and Javascript
  • Integrating the front-end with back-end development for the website

Accomplishments that we're proud of

  • Became proficient in using Figma and applying design principles
  • Understood and integrated API into our code
  • Collaborated well with each other and had fun in the process
  • Produced aesthetic UI
  • Attended multiple workshops and applied the knowledge gained to our project

What we learned

  • 3 kinds of short-term storage: data stored until cleared by user, data stored until browser is closed, database in the browser
  • Machine learning input can be supervised, unsupervised, or reinforcement learning
  • While developing an understanding OOP concepts is important, being able to program in a scripting environment can be equally valuable
  • How hackathons work
  • Project development cycle
  • Figma tools to make prototypes

What's next for Moo-ney Meals

  • Allow users to create an account to access their recipe history and/or favorited history
  • Make a mobile version of the website, so users can access it more easily and anywhere
  • Add more stores for users to refer to when shopping for ingredients
  • Make a Submit A Recipe section for users to add their own favorite recipes complete with the ingredients list to the recipe inventory.
  • Front-end features to accept natural language search terms
  • Expand cuisine options

*Figma "Try it out" Link Note: prototype only works with (Italian) Chicken Pesto Pasta Recipe

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