Alexandria

Context

Most reading trackers are either too generic or overloaded with social mechanics. Alexandria was designed as a personal, private system focused on consistency: add books quickly, keep progress clean, and extract useful signals from reading history.

What I built

Alexandria includes:

• A dashboard split between currently reading and finished books
• Search and add flows connected to the Google Books API
• Detailed book records with enriched metadata (authors, categories, page count, rating, language)
• A dedicated stats view for reading velocity, volume trends, categories, and long-range habits
• A private librarian login for controlled access to search/edit/delete operations

Technical approach

I implemented Alexandria with Flask, Flask-Login, and SQLAlchemy on top of a SQLite data store, keeping the architecture lightweight and maintainable for solo usage. Book ingestion is API-driven (Google Books via request-based adapters), while template-driven UI views expose both operational flows (search/add/edit) and analytical outputs (stats and trend aggregates). The app is containerized for predictable local and deployment environments.

Outcome

Alexandria evolved into a full private reading companion rather than a simple list app. It balances elegant UX with practical depth: low-friction cataloging, clear reading progress, and meaningful analytics that make long-term reading habits easier to understand and sustain.