Project Info

Basket

This project did not submit a demo video on Devpost.

Inspiration

Supermarkets are filled from floor to ceiling with unhealthy foods, made cheap by unsafe pesticides, unsustainable agricultural practices, and unsanitary factory production, all while the grocery stores pushing these products take a massive cut of the profits. In America, people feel that organic foods and a healthy lifestyle are out of reach. Farmer's markets typically happen once a week for only half the day, consumers don't know what food will be there, and they charge farmers upwards of $200 to have a booth. Farm-to-table services are convenient for consumers, but logistical problems like order tracking and last mile distribution can be too much responsibility for farmers to tackle, often causing them to outsource logistics and introduce yet another middle-man, with more fees.

What it does

Basket provides a solution, with the consumer convenience of farm-to-table services, and the simplicity that farmer's markets provide for farmers. Basket does this through the power of shared deliveries, a business model that has taken over Chinese e-commerce, but has yet to make its way to the west. When you open the app, you can scroll through food sold by farms near you and buy what you want. Then, the app combines your order with the orders of people near you, and sends one bulk order to be fulfilled by the farm. The farm then ships the order to one of the customers who volunteers as a pickup point. This address is then sent to the other customers who can pick up their order. This provides consumers with the convenience of online shopping, knowing exactly what food they're getting and how much they're paying, while providing farmer's the simplicity of farmer's markets, with only one delivery to make. The high costs of delivery services and farmer's markets fees are eliminated, and the delivery fees needed by the farmer are split among customers for the bulk order.

How we built it

The backend consists of a PostgreSQL database holding products, orders, and all other data. A Python server powered by FastAPI provides the algorithms to combine orders and determine prices. The frontend is written using React + Vite, using Tailwind for styling and Auth0 for authentication.

Challenges we ran into

Managing deployment for both backend and frontend were difficult, as well as the SQL queries to manage interactions between orders.

Accomplishments we're proud of

We're proud of coming up with a sound business model, and using our different specializations to build an e-commerce store in a limited time.

What we learned

We learned about the costs incurred by farmers in the agricultural process from top to bottom, and how money gets distributed through the grocery store system.

What's next

In the future, Basket could partner with local grocers to provide delivery points. This will help with privacy concerns for the pickup point volunteers, and build a positive relationship between Basket and grocers, who will receive traffic from Basket customers.

Analysis

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Technology

Found in codeClaimed only

CSSIn code
FastAPIIn code
HTMLIn code
JavaScriptIn code
PostgreSQLIn code
PythonIn code
ReactIn code
Tailwind CSSIn code

8 of 8 appear in the indexed code.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

33 KB

Source files

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.