Context-aware music rating system with temporal preference tracking
💡Business Impact: Personal tool showcasing rapid CLI development while solving actual music workflow needs
Built music player CLI in one day specifically to get hands-on experience with command-line interfaces before applying to Anthropic Claude Code. Ended up solving real problems with my music workflow - goes beyond simple ratings to track listening context and mood patterns. Designed database schema for future AI analysis of music taste evolution over time.
Python 3.12 with MPV integration for cross-platform audio playback. SQLite database stores contextual listening data beyond traditional 5-star ratings. TOML configuration files keep settings simple and readable.
Records when/where/why I'm listening to specific songs - data structure designed for future machine learning on music preferences.
Separate modules for player control, library management, and database operations. Built for extensibility even though it was a rapid prototype.
Built complete CLI system with modern Python patterns
Context-aware music preference tracking database
Advanced prompt engineering techniques for music preference tracking
Built first CLI project with AI assistance for Claude Code experience
MPV integration for music playback and metadata extraction
TODO: Add key code examples and implementation snippets
Sole developer
September 2025 - 1 day
CLI development, audio integration, contextual data modeling
TODO: Document key technical challenges overcome and solutions implemented for this project
Cross-platform MPV audio backend
SQLite for reliable data persistence
Modular Python architecture for maintainability
Personal use scope with room for experimentation