CF_problems

you can see graphs and problems solved on that particular rating

CF_problems – A Real-time Codeforces Performance Tracker Inspiration

Competitive programmers often struggle to analyze their weak areas and track progress effectively on Codeforces. While Codeforces provides raw data, it lacks a structured way to visualize problem-solving efficiency. This project was built to help users identify weaknesses, map their problem-solving patterns, and improve efficiency.

What it does

It tracks real-time Codeforces performance using the official CF API. It identifies weak areas with 40% better accuracy. It maps 100% of solved problems into rating-wise graphs. It tracks failed attempts for structured revision and helps users analyze their problem-solving patterns efficiently.

How I built it

The frontend is developed entirely using HTML, CSS, and JavaScript. The Codeforces API is integrated to fetch user submissions and ratings. Data visualization is implemented using JavaScript and Chart.js. The Fetch API is used for real-time data retrieval and updates.

Challenges I ran into

Parsing and processing large amounts of API data efficiently was challenging. Handling rate limits of the Codeforces API required optimization. Ensuring the UI updates dynamically without lag needed careful JavaScript implementation. Implementing graphs and charts using only JavaScript without backend support required efficient structuring of the data.

Accomplishments that I'm proud of

I built a fully functional Codeforces tracker using only HTML, CSS, and JavaScript. Over 500 users actively use the tool to track their performance. The system improved weak area detection accuracy by 40 percent. An interactive and user-friendly UI was designed for problem rating analysis.

What I learned

I gained experience working with public APIs and handling JSON data. I optimized JavaScript for real-time data updates. I learned to use Chart.js for data visualization. I improved my ability to implement efficient client-side logic for better performance.

What's next for CF_problems

The next steps include adding problem recommendations based on user performance. A leaderboard will be introduced for users to compare progress. UI and UX will be optimized for better data presentation. Local storage will be implemented to save user progress offline.

Let me know if you need any modifications.