Offline Algorithm Practice

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A standalone algorithm coding practice application that works 100% offline. No local development environment required — just download, install, and start practicing. Supports JavaScript, TypeScript, and Python with WASM-based browser-side code execution.

Quick Start

Desktop Application (Recommended)

The desktop application provides the best experience with zero environment setup required. Simply download and run.

Download Latest Release

Platform	Download
macOS (Apple Silicon)	Algorithm-Practice-*-macOS-arm64.dmg
macOS (Intel)	Algorithm-Practice-*-macOS-x64.dmg
Windows (Installer)	Algorithm-Practice-*-Windows-Setup.exe
Windows (Portable)	Algorithm-Practice-*-Windows-Portable.exe
Linux (AppImage)	Algorithm-Practice-*-Linux.AppImage
Linux (Debian/Ubuntu)	Algorithm-Practice-*-Linux.deb
Linux (Fedora/RHEL)	Algorithm-Practice-*-Linux.rpm

macOS Users: If you encounter "App is damaged and can't be opened", run in Terminal:

xattr -cr "/Applications/Algorithm Practice.app"

Web Version (Alternative)

For developers who prefer running from source, see Development Setup below.

Features

Core Functionality

• Standalone Application: No Node.js, Python, or any development environment required
• Complete Offline Support: Works without internet after installation
• Built-in Problem Library: 10+ classic algorithm problems included
• AI Problem Generator: Generate custom problems using various AI providers
• WASM Code Execution: Browser-side execution for JavaScript, TypeScript, and Python
• Monaco Code Editor: VS Code-like editing experience with syntax highlighting and autocomplete
• Instant Testing: Run tests immediately with detailed results and execution time tracking
• Cross-platform: Windows, macOS, and Linux supported

Supported Languages

Language	Status	Implementation
JavaScript	Supported	Native browser execution
TypeScript	Supported	TypeScript compiler transpilation
Python	Supported	Pyodide (CPython WASM)

All code execution happens in the browser using WebAssembly. No server-side execution required.

AI-Powered Problem Generation

• Custom Problem Creation: Describe what you want to practice in natural language
• Complete Solutions: Each problem includes working reference solutions
• Comprehensive Testing: Auto-generated test cases including edge cases
• Instant Integration: Problems automatically added to your local library

How to Use

Problem Solving

1. Browse Problems: View the problem list with difficulty and tags
2. Select a Problem: Click on any problem to open the detail page
3. Choose Language: Select JavaScript, TypeScript, or Python
4. Write Solution: Use the Monaco editor with full IDE features
5. Run Tests: Click "Submit & Run Tests" to execute your code
6. View Results: See detailed test results with execution time

AI Problem Generation

1. Access Generator: Click "AI Generator" on the homepage
2. Describe Requirements: Enter what type of problem you want
3. Generate: AI creates a complete problem with test cases and solutions
4. Practice: Generated problem is automatically available in your library

Settings Configuration

Access the settings page to configure AI providers:

• Desktop Mode: Via "Settings" button or application menu
• Web Mode: Navigate to /settings (e.g., http://localhost:3000/settings)

Supported AI providers:

• DeepSeek
• OpenAI
• Qwen (Alibaba Cloud)
• Claude (Anthropic)
• Ollama (Local)

Configuration is saved to ~/.offline-leet-practice/config.json in desktop mode. See AI_PROVIDER_GUIDE.md for detailed configuration.

Adding Custom Problems

1. Via UI: Use the "Add Problem" page in the application
2. JSON Import: Upload or paste problem data in JSON format
3. Direct Edit: Modify public/problems.json for immediate changes

See MODIFY-PROBLEMS-GUIDE.md for the complete guide.

Development Setup

For developers who want to run from source or contribute to the project.

Prerequisites

• Node.js 18+ (Download)
• npm 8+

Running Locally

Windows:

start-local.bat

macOS / Linux:

chmod +x start-local.sh
./start-local.sh

Manual Setup:

git clone https://github.com/zxypro1/OfflineLeetPractice.git
cd OfflineLeetPractice
npm install
npm run build
npm start

Then open http://localhost:3000 in your browser.

Building Desktop Application

# macOS
npm run dist:mac

# Windows
npm run dist:win

# Linux
npm run dist:linux

# All platforms
npm run dist:all

See DESKTOP-APP-GUIDE.md for detailed build instructions.

Technology Stack

• Frontend: React 18, Next.js 13, TypeScript
• UI Framework: Mantine v7
• Code Editor: Monaco Editor
• Code Execution: WebAssembly
  • JavaScript: Native browser Function constructor
  • TypeScript: TypeScript compiler (CDN)
  • Python: Pyodide (CPython compiled to WASM)
• Desktop: Electron

Project Structure

OfflineLeetPractice/
├── pages/                  # Next.js pages and API routes
│   ├── api/
│   │   ├── problems.ts     # Problem data API
│   │   ├── generate-problem.ts
│   │   └── add-problem.ts
│   ├── problems/[id].tsx   # Problem detail page
│   ├── generator.tsx       # AI Generator page
│   └── index.tsx           # Homepage
├── src/
│   ├── components/         # React components
│   └── hooks/
│       └── useWasmExecutor.ts
├── public/
│   └── problems.json       # Problem database
├── electron-main.js        # Electron main process
└── electron-builder.config.js

Contributing

Contributions are welcome. Areas for improvement:

• Additional algorithm problems
• Performance analytics features
• User experience enhancements
• Documentation improvements

License

MIT License

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Practice algorithms anywhere — on flights, cruises, or any offline environment.