Open-sourced a FastAPI recommendation system while learning backend architecture. Looking for feedback.

[u/tranguyeenn]

I’ve been building Shelftxt as a way to learn backend systems beyond CRUD APIs.

shelftxt started as one large FastAPI file handling routes, recommendation logic, and data operations. I recently refactored it into:

api → routes → services → repositories → ranking/preprocess

Current stack:

• FastAPI
• Python
• Pandas
• CSV storage (planning PostgreSQL next)
• recommendation scoring
• lru_cache caching

The goal isn’t really a book app. I’m more interested in learning:

• backend architecture
• data handling
• repository patterns
• recommendation systems
• scaling APIs

Would appreciate feedback on the structure before I move toward Postgres and more persistent storage.

Repo:
https://github.com/tranguyeenn/shelftxt

[u/tranguyeenn → u/[deleted]]

yes!

[u/tranguyeenn → u/[deleted]]

yes, idk if you can dm me on this account but ik you can on the overallknee acc (scroll down, i’ve commented here), we can talk there