DSAlytics 🚀

A modern platform to practice, track, and master Data Structures & Algorithms (DSA). Built with the MERN stack, DSAlytics offers an interactive experience for students and professionals to improve their coding skills.

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📚 What is DSAlytics?

DSAlytics is a web application designed to help users:

• Practice DSA problems from a curated question bank
• Track their progress and analytics
• Collaborate in study plans and discussion forums
• Prepare for coding interviews and competitive programming

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🌟 Key Features (Implemented)

• User Authentication (Email & Google OAuth)
• Comprehensive DSA Question Bank (with filters & tags)
• Online Coding Playground (Monaco Editor, code execution placeholder)
• Progress Tracking & Analytics (basic charts, leaderboards)
• Discussion Forum (Q&A, peer support, basic implementation)
• Study Plans (join, create, and track study groups)
• AI Chatbot (FAQ and learning support)

🚧 Features in Progress / Planned

• AI Interviewer (mock interviews, feedback) — Prototype exists, not fully functional
• Custom Test Generator (topic/difficulty-wise) — Planned
• Advanced Analytics (detailed insights, recommendations) — Planned

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Demo Screenshots

🛠️ Tech Stack

Frontend

• React.js (with React Router)
• TailwindCSS
• Monaco Editor
• Chart.js, Recharts
• Axios

Backend

• Node.js, Express.js
• MongoDB (Mongoose ODM)
• JWT Authentication, Passport (Google OAuth)

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📁 Project Structure

DSAlytics/
├── client/                # React frontend
│   ├── public/            # Static assets
│   ├── src/
│   │   ├── assets/        # Images, SVGs, etc.
│   │   ├── components/    # Shared React components
│   │   ├── contexts/      # React context providers
│   │   ├── context/       # (legacy or additional context)
│   │   ├── data/          # Static data (e.g., problems.json)
│   │   ├── features/      # Feature modules (AI, Auth, Dashboard, etc.)
│   │   ├── pages/         # Page-level React components
│   │   ├── services/      # API and utility services
│   │   ├── utils/         # Utility functions
│   │   └── main.jsx       # App entry point
│   ├── index.html         # Main HTML file
│   ├── tailwind.config.js # TailwindCSS config
│   └── ...                # Other config files
│
├── server/                # Node.js + Express backend
│   ├── config/            # DB and other config files
│   ├── controllers/       # Route controllers
│   ├── data/              # Seed or static data
│   ├── middleware/        # Express middleware
│   ├── models/            # Mongoose models
│   ├── routes/            # API route definitions
│   ├── scripts/           # Data import/utility scripts
│   ├── services/          # Backend services (e.g., AI)
│   ├── utils/             # Utility functions
│   └── server.js          # Main server entry point
│
├── ai-services/           # (Optional) AI microservices (currently empty)
├── data/                  # Datasets, PDFs, CSVs
├── scripts/               # Root-level utility scripts
├── docker/                # Docker configs (currently empty)
├── requirements.txt       # Python requirements placeholder (not used)
├── README.md              # Project documentation
├── package.json           # Root package config
└── ...                    # Other root files (e.g., setup.js, .gitignore)

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🚀 Getting Started

Prerequisites

• Node.js (v16 or higher)
• MongoDB
• npm or yarn

Installation

1. Clone the repository

   git clone https://github.com/varshitha127/DSAlytics.git
   cd DSAlytics

2. Install dependencies

   npm install           # Root dependencies
   cd client && npm install   # Frontend
   cd ../server && npm install # Backend

3. Environment Setup
   • Copy .env.example to .env in both client/ and server/ directories
   • Update the environment variables as needed
4. Start the development servers

   # Backend (from server directory)
   npm run dev
   # Frontend (from client directory)
   npm run dev

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🔧 Environment Variables

Server (server/.env)

PORT=5000
MONGODB_URI=your_mongodb_uri
JWT_SECRET=your_jwt_secret
JUDGE0_API_URL=your_judge0_url
OPENAI_API_KEY=your_openai_key
GOOGLE_CLIENT_ID=your_google_client_id

Client (client/.env)

VITE_API_URL=http://localhost:5000
VITE_GOOGLE_CLIENT_ID=your_google_client_id

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📊 Usage

• Register or log in (Google OAuth supported)
• Browse and solve DSA problems
• Track your progress and analytics
• Use the AI Chatbot for help and learning support
• Join discussions and forums
• Create or join study plans

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🧑‍💻 Contributing

We welcome contributions from the community! To get started:

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Contribution Guidelines:

• Write clear, concise commit messages
• Add tests for new features
• Follow code style and linting rules
• Document your code where necessary
• Be respectful and constructive in discussions

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📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

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📧 Contact

Project Maintainer: Varshitha (GitHub Profile)
Email: lakkireddyvarshithareddy@gmail.com LinkedIn: in/varshithareddy-lakkireddy-1b1326290

Project Link: https://github.com/varshitha127/DSAlytics

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⚠️ Note on requirements.txt

This project is a JavaScript/Node.js (MERN) stack and does not use Python. All dependencies are managed via package.json in the root, client/, and server/ directories. A requirements.txt is not required unless you add Python-based services.