Pastafist

In a society where financially challenged students and adults increasingly struggle to acquire affordable nutriment. Pastafist brings a golden era of pacifism, generating user-oriented grocery lists.

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Inspiration

Pastafist was inspired by the rapid contrast between student budgets and rapidly increasing grocery prices. As low-income students ourselves, we wanted to build something genuinely useful in our everyday lives, something that helps people stretch limited budgets without sacrificing nutrition or convenience.

What it does

  • Helps budget-constrained users plan affordable meals by leveraging nearby grocery data.

  • Displays nearby grocery stores on an interactive map

  • Generates a personalized grocery list and shopping path based on: Budget constraints, Dietary restrictions, Nutrition preferences

  • Caches store locations and product data to enable fast, repeat queries

  • Designed to support meal planning rather than impulse buying

How we built it

  • Frontend: React

  • Maps: Leaflet + OpenStreetMap (free and open-source)

Backend / Data:

  • MongoDB for persistent storage of stores and products

  • Python-based web scraping pipeline (manually triggered)

  • OpenStreetMap data for store discovery

Challenges we ran into

  • Legal and ethical concerns around scraping centralized grocery websites

  • Most accurate mapping APIs require paid tiers, which we avoided

  • Grocery sites heavily obfuscate or dynamically load product data

  • Many major retailers price-match competitors, reducing visible price variance

  • Public data sources vary significantly in accuracy by region

Accomplishments that we’re proud of

  • Built a fully functional web app with original, real-world utility

  • Implemented a working store-discovery and caching pipeline

  • Successfully integrated open-source mapping and geospatial data

  • Learned and experimented with numerous tools despite repeated dead ends

  • Persisted through technical setbacks while working with very limited time and rest

What we learned

  • Planning for data access and legal constraints is as important as feature design

  • Free and open data ecosystems require creative engineering tradeoffs

  • “Simple” ideas become complex when scaled to real-world constraints

What’s next for Pastafist

  • Expand retailer coverage beyond major chains

  • Improve data accuracy with hybrid APIs + community data

  • Automate and harden the scraping pipeline

  • Add smarter nutrition-aware meal planning and price trend tracking

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