BeatSync

Flirtify: Match Through Music 🎵

Inspiration

Music has always been a powerful connector of people. We realized that someone’s music taste can tell you a lot about their personality, emotions, and potential compatibility. Flirtify was born from the idea that shared musical interests could be the foundation for meaningful connections.

What it does

Flirtify is a sophisticated music-based matching platform that:

How we built it

Tech Stack:

Frontend: (Planned)

Backend:

Key Components:

Authentication System (auth.py): Spotify OAuth integration Secure token management User session handling Matching Algorithm (match.py): Advanced similarity calculations Audio feature analysis Weighted scoring system Database Architecture (database.py): Firebase integration Real-time data updates Secure credential management

Challenges we ran into

Spotify API Integration: Complex OAuth flow Token refresh management Rate limiting considerations Firebase Setup: Credential management Environment variable configuration Real-time database synchronization Algorithm Development: Balancing different matching criteria Handling edge cases Optimizing performance

Accomplishments that we’re proud of

Sophisticated Matching System: Multi-factor analysis Detailed compatibility explanations Real-time processing Robust Backend Architecture: Clean code structure Efficient error handling Scalable design Security Implementation: Secure credential management Protected user data Safe API integration

What we learned

Technical Skills: FastAPI development Firebase integration Spotify API usage Algorithm design Development Practices: Environment management API documentation Code organization Error handling Project Management: Feature prioritization System architecture Documentation importance

What’s next for Flirtify

Feature Enhancements: Playlist generation for matches Real-time chat integration Music recommendation system Match history analytics Technical Improvements: Frontend development Mobile app version Performance optimization Enhanced matching algorithms User Experience: Interactive matching visualization Detailed music taste analysis Social features integration Premium features