Enduro Stats V2
A full-stack fitness analytics platform built to replicate and extend premium Strava insights without requiring a subscription. Originally started as a simple API wrapper, the project was later refactored from the ground up to improve data modeling, scalability, and performance.
Technologies Used:
Project Links:
Overview:
After completing the initial version of Enduro Stats, I realized the limitations of my original architecture. The app needed to evolve from a simple API wrapper into a robust analytics platform with proper data persistence, advanced caching, and professional development practices. This V2 represents a complete architectural overhaul.
Challenges:
- Complete architectural refactoring from scratch while maintaining user data and functionality
- Implementing proper data persistence and synchronization with conflict resolution
- Building advanced analytics and trend analysis features
- Creating a scalable, maintainable codebase with proper testing and CI/CD
- Optimizing performance with intelligent caching and data management
Implementation:
I completely rebuilt the application from the ground up using modern React patterns and best practices. The new architecture includes proper data modeling with Supabase, intelligent caching strategies, and a robust data synchronization system. I implemented React Query for efficient data fetching, proper error boundaries, and comprehensive testing.
Key Decisions:
- Redesign the entire application architecture with proper separation of concerns
- Implement persistent data storage and synchronization with Strava API
- Add advanced analytics, trend analysis, and performance insights
- Establish professional development practices including testing and CI/CD
- Create a more intuitive and feature-rich user experience
Learnings:
- Deep understanding of React Query and modern data fetching patterns
- Experience with database design and data synchronization strategies
- Advanced TypeScript patterns and type safety best practices
- Professional development workflow with testing, CI/CD, and code quality tools
- Performance optimization and caching strategies for real-time data applications
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