A high-performance, local-first analytical dashboard designed for competitive Square-1 speedcubers. Built with Clean Architecture principles, this engine processes session data, provides real-time WCA-compliant statistics, and tracks daily biométric performance to optimize training efficiency.
- WCA-Compliant Analytics: Real-time calculation of Mo3, Ao5, Ao12, and global averages using standard trimming rules (WCA 9f2).
- Daily Performance Tracker: A specialized module to log biometric data (sleep quality, mental energy, physical fatigue) and correlate it with cubing performance.
- OBL/CSP Audit Engine: Dynamic case tracking system to identify bottleneck patterns in OBL and CSP execution.
- Local-First Architecture: Powered by
Dexie.jsandIndexedDBfor zero-latency data persistence without the need for external cloud backends. - Data Visualization: Interactive performance charts using
Rechartsfor Gaussian distribution and time-series progress tracking.
- Frontend: React, TypeScript, Vite
- Styling: Tailwind CSS (v4)
- Database: IndexedDB via Dexie.js
- Data Processing: PapaParse (CSV integration)
- Mathematical Engine: Custom TypeScript implementation of WCA standard deviations and sliding window averages.
- Clone the repository:
git clone <your-repository-url>
- Install dependencies: npm install
- Run the development server: npm run dev
📐 Architecture The project follows the Clean Architecture pattern to ensure strict separation of concerns:
domain/: Business entities and interfaces. application/: Pure logic and use cases (statistical engine). infrastructure/: Data persistence (Dexie) and external parsers. presentation/: React components and custom hooks.
📝 License This project is licensed under the MIT License.