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🚀 Quantpraxus

University Exam (YKS) Analysis and Performance Tracking System

📺 Demo Video

Quantpraxus Demo

This video demonstrates the core features and usage scenarios of the project.

Report every study session down to the finest detail.

Quantpraxus Dashboard Preview

Plan your studies in detail.

Quantpraxus Dashboard Preview

Discover when and how many questions appeared for each subject, and organize your studies accordingly.

Quantpraxus Dashboard Preview

Review the mistakes you made in practice exams and question solving, and avoid repeating them.

Quantpraxus Dashboard Preview

Version License Electron React TypeScript


🎯 About

Quantpraxus is a full-stack analysis platform developed to make student performance measurable and analyzable during the university exam (YKS) preparation process.

It has evolved from a simple score tracker into a modular system that analyzes performance trends, subject-based weaknesses, and study habits.

It runs smoothly on both web and desktop (Electron) environments.


✨ Core Features

  • 📊 Performance dashboard with trend analysis
  • 📚 Subject-based weakness detection (TYT / AYT)
  • ⏱ Integrated Pomodoro timer & task management
  • 🖥 Offline-first desktop support (Electron)
  • 💾 JSON data export / import
  • 📈 Detailed mock exam tracking & statistics
  • 🌙 Dark / Light theme support

🛠 Tech Stack

Layer Technology
Frontend React 18, TypeScript, Tailwind CSS, Radix UI
Backend Node.js, Express
Database PostgreSQL (Drizzle ORM - planned) + Local JSON Storage
Desktop Electron, Electron Builder
Testing Vitest, Playwright

🏗 System Architecture

User (React + Vite)
        ↓
API Client (Fetch)
        ↓
Express Server (Node.js)
        ↓
Storage Layer (Drizzle ORM)
        ↓
JSON Storage ↔ PostgreSQL (Planned)

⚙️ Engineering Challenges

1. ESM vs CJS Conflict

The module system conflict between Vite (ESM) and Electron (CJS) was resolved by implementing a separate build pipeline strategy.

2. Timezone Normalization

Data inconsistencies arising from UTC and Turkey time zone differences were normalized using centralized date helper functions.

3. Performance Optimization

Performance was improved in datasets containing 1000+ records by using:

  • Optimized queries
  • Memoization techniques
  • Lazy rendering

📁 Project Structure

.
├── client/        # React + Electron frontend
├── server/        # Express backend
├── electron/      # Electron main process
├── shared/        # Shared types & schemas
├── data/          # JSON storage
└── tests/         # Unit & E2E tests

🚀 Installation

Requirements

  • Node.js >= 20
  • npm or yarn

Setup

git clone https://github.com/beratcode03/quantpraxus.git
cd quantpraxus
npm install

Development

# Web
npm run dev

# Desktop
npm run electron:dev

Production Build

# Web
npm run build

# Electron
npm run electron:build

🧪 Testing

npm run test
npx playwright test
npm run test:coverage

🔮 Roadmap

  • Full PostgreSQL migration
  • Mobile app (React Native)
  • AI-based study recommendations
  • Cloud sync support
  • Social comparison system

👨‍💻 Author

Built by Berat Cankır.

Quantpraxus represents an end-to-end full-stack system — from database modeling to cross-platform desktop packaging.

Contributions, issues, and discussions are welcome.


📄 License

MIT License — see LICENSE file for details.


⭐ If you find this project useful, consider giving it a star.

About

🎯 Quantpraxus: Veri odaklı YKS analiz ve takip sistemi. Electron & React ile geliştirilmiş yüksek performanslı masaüstü uygulaması.

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