A Python Flask web application to track your progress through the 450 DSA problems. This is a complete conversion from the original React + LocalBase version to Flask + SQLAlchemy with a SQLite database.

• Topic-wise tracking: View progress for each Data Structures & Algorithms topic
• Question status: Mark questions as done/incomplete
• Bookmarking: Bookmark important questions for quick reference
• Notes: Add and save notes for each problem
• Progress dashboard: Visual progress bars showing completion percentage
• Persistent storage: All data stored in SQLite database

1. Install dependencies

pip install -r requirements.txt

2. Run the Flask app

python app.py

3. Open in browser

http://localhost:5000

450-DSA/
├── app.py                 # Flask application & SQLAlchemy models
├── data.json              # Question data (converted from JS)
├── requirements.txt       # Python dependencies
├── templates/             # Jinja2 HTML templates
│   ├── base.html         # Base template (Bootstrap 4)
│   ├── index.html        # Dashboard view
│   └── topic.html        # Questions table view
├── venv/                 # Python virtual environment
└── instance/
    └── dsa.db            # SQLite database (auto-created)

The project uses SQLAlchemy ORM with SQLite:

Topic Model

• id: Primary key
• name: Topic name (unique)
• position: Order in curriculum
• started: Whether user initiated this topic
• questions: Relationship to Question records

Question Model

• id: Primary key
• topic_id: Foreign key to Topic
• problem: Problem statement
• done: Completion status
• bookmark: Bookmark flag
• notes: User notes/solutions
• url: Main problem link
• url2: Alternative link (Coding Ninjas)

• ✅ Dashboard: Overview of all topics with progress bars
• ✅ Topic View: All questions for a specific topic
• ✅ Status Tracking: Mark questions as complete
• ✅ Bookmarks: Bookmark important questions
• ✅ Notes: Add personal notes for each question
• ✅ Progress: Track completion percentage
• ✅ Persistent Storage: All data saved to SQLite

• GET / - Dashboard with all topics
• GET /topic/<topic_id> - View questions for a topic

• POST /update_question/<question_id> - Update question (body: {done, bookmark, notes})

This represents a complete rewrite from React + LocalBase to Flask + SQLAlchemy:

The 450DSAFinal.js data was converted to valid JSON using pyjson5 and loaded into the database on first run.

• Backend: Flask 2.3.2
• ORM: Flask-SQLAlchemy 3.0.5
• Database: SQLite 3
• Frontend: Jinja2, Bootstrap 4, jQuery
• Data Format: JSON

• User authentication & registration
• Import/Export functionality
• Dark mode theme
• Advanced search and filtering
• Statistics dashboard
• REST API with API documentation
• Rate limiting and caching
• Deployment to cloud (Render, Heroku, etc.)

• Database is created automatically on first run in instance/dsa.db
• All 450+ problems are preloaded from data.json
• Uses AJAX for seamless updates without page reload

Original 450 DSA dataset by Love Babbar for his "Cracking the Coding Interview" course.

Flask version conversion: 2026