🏆 Unified Ranking System

🎉 NEW: Enhanced Database System v2.0 - Production-ready architecture with advanced analytics and user management!

A comprehensive coding skills assessment platform that integrates multiple programming platforms with educational achievements to provide unified rankings.

🌟 Complete Overview

The Unified Ranking System is a sophisticated Python application that revolutionizes how programmers track and assess their coding skills across multiple platforms. By combining competitive programming ratings, educational achievements, and activity patterns, it provides a holistic view of your programming prowess.

🎯 What It Does

📊 Multi-Platform Integration: Automatically fetches ratings from CodeForces, LeetCode, CodeChef, and AtCoder
🎓 Educational Tracking: Scrapes Coursera profiles to extract course completions and calculate intelligent bonus points
📈 Activity Visualization: Generates GitHub-style heatmaps showing coding consistency across platforms
🔢 Unified Rankings: Uses sophisticated algorithms to combine platform ratings with educational bonuses
👥 Multi-User Support: Secure authentication system supporting multiple users with persistent data
💾 Data Persistence: SQLite database stores all user data locally with encrypted passwords

🚀 Key Features

🏅 Platform Rating Integration

CodeForces (Max: 3000) - Competitive programming excellence
LeetCode (Max: 2500) - Interview preparation mastery
CodeChef (Max: 1800) - Programming contest proficiency
AtCoder (Max: 2800) - Japanese competitive programming platform

Smart Auto-Fetch System:

🔄 Automatic rating retrieval via official APIs
🔄 Real-time data validation and error handling
🔄 Intelligent fallback to manual entry when needed

🎓 Educational Bonus System

Coursera Profile Scraping:

📚 Automatic extraction of completed courses from public profiles
🏛️ Institution recognition (Harvard, Stanford, MIT get premium scores)
📅 Completion date tracking for timeline analysis
🧮 AI-powered bonus calculation based on multiple factors

Intelligent Bonus Calculation (Max: 45 points per course):

Institution Factor (0-10): University prestige and global ranking
Duration Factor (0-5): Course depth, specialization length
Field Factor (0-10): Relevance to tech industry (AI, Data Science, Programming)
Skills Factor (0-20): Market demand analysis and salary impact

📈 Advanced Analytics

GitHub-Style Activity Heatmaps:

🟩 Daily coding activity visualization across all platforms
📊 Combined activity metrics from multiple sources
🎨 Beautiful visual progress representation
📅 Yearly overview with streak tracking

Sophisticated Ranking Algorithm:

⚖️ Weighted platform scores based on difficulty
📊 Normalized rating scales for fair comparison
🎯 Platform difficulty consideration in weighting
🎓 Seamless educational bonus integration
📈 Final unified ranking calculation

🗄️ Enhanced Database System v2.0

🚀 Production-Ready Architecture

The system now features a comprehensive, normalized database schema designed for scalability and performance:

🔒 Enhanced Security & Authentication

bcrypt password hashing (upgraded from SHA-256)
Session management with tracking and analytics
Email verification system (ready for activation)
Rich user profiles with timezone, language preferences

📊 Advanced Data Management

15 specialized tables with proper relationships
Foreign key constraints ensuring data integrity
Strategic indexes for optimal query performance
Generated columns for automatic calculations

🏆 Comprehensive Tracking

Platform Management: 6 pre-configured platforms with auto-fetch
Course Intelligence: 12 top institutions + 14 smart categories
Achievement System: Badges, milestones, and gamification
Analytics Engine: System-wide insights and reporting

🛠️ Database Management Tools

# System health check
python db_analyzer.py

# Generate analytics report
python db_manager.py report

# Create backup
python db_manager.py backup

# Export data
python db_manager.py export

🎮 Three Application Modes

1. 🔧 Simple Version (Recommended)

Perfect for: Beginners, most users, systems with compatibility issues

✅ Visible password input (universal compatibility)
✅ Complete feature set with intuitive interface
✅ Automatic platform rating fetching
✅ Full Coursera integration and bonus calculation
✅ Heatmap generation and user profiles

2. 🛡️ Advanced Version (Secure)

Perfect for: Security-conscious users, advanced developers

✅ Hidden password input with enhanced security
✅ All Simple Version features plus security enhancements
✅ Advanced error handling and logging
✅ Object-oriented architecture for maintainability
✅ Enhanced data validation and sanitization

3. 📊 Original Single-User Version

Perfect for: Quick testing, demonstration, single-session use

✅ No registration required - immediate access
✅ Direct platform input and instant calculations
✅ Full ranking computation and heatmap generation
⚠️ No data persistence between sessions
⚠️ Single user only (no authentication system)

🚀 Quick Start

Prerequisites

Python 3.7+ installed on your system
Internet connection for API calls and web scraping
Public profiles on coding platforms (for auto-fetch)
Public Coursera profile (optional, for course bonus)

Installation & Launch

Download/Clone this repository
Navigate to the backend folder
Double-click start.bat (Windows) or run from command line

The intelligent launcher will:

✅ Automatically detect Python installation
📦 Install required packages if missing
🎯 Present you with three version options
🛠️ Handle errors and provide guidance

📊 How It Works

🔢 Ranking Calculation

Total Score = (Weighted Platform Score) + (Course Bonus Points)

Where:
- Weighted Platform Score = Σ(Platform Rating × Platform Weight)
- Course Bonus Points = Σ(Individual Course Bonuses)
- Platform Weights = Dynamic based on difficulty and participation

🎓 Course Bonus Examples

Stanford Machine Learning: ~40-45 points (top-tier institution + high-demand field)
MIT Computer Science: ~35-40 points (prestigious institution + core programming)
Google Data Analytics: ~25-30 points (industry recognition + practical skills)
Harvard CS50: ~30-35 points (prestigious + comprehensive programming)

📈 Platform Weighting

Difficulty Assessment: Harder platforms receive higher weights
Participation Analysis: Active user bases get consideration
Rating Distribution: Normalized across different rating scales
Industry Recognition: Platform reputation in hiring processes

🛠️ Technical Architecture

🏗️ Core Components

Authentication System: Secure user management with bcrypt password hashing
API Integration Layer: Robust web scraping and API calls with error handling
Ranking Engine: Sophisticated algorithms for unified score calculation
Visualization Engine: Beautiful heatmap generation with statistical analysis
Data Persistence: SQLite database with optimized queries and data integrity

🔧 Platform APIs

CodeForces API: Official REST API for contest and user data
LeetCode GraphQL: Advanced querying for comprehensive profile data
CodeChef Web Scraping: Intelligent parsing with rate limiting
Coursera Profile Scraping: Selenium-based extraction with mock data fallback

📱 User Experience Features

🎯 Smart Auto-Detection

Platform Profile Validation: Real-time verification of usernames
Rating Verification: Cross-reference with platform data
Course Certificate Validation: Only certified completions count
Error Recovery: Intelligent fallbacks and user guidance

📊 Rich Analytics

Progress Tracking: Historical rating changes over time
Activity Patterns: Peak coding times and consistency metrics
Achievement Insights: Course completion impact on overall ranking
Comparative Analysis: Performance across different platforms

🔒 Privacy & Security

Local Data Storage: All information stays on your machine
No Cloud Dependencies: Complete offline functionality
Encrypted Credentials: Secure password storage with bcrypt
Ethical Scraping: Respectful rate limiting and public data only

📚 Full Documentation

For complete setup instructions, troubleshooting, and advanced usage:

📖 Complete README.md

📂 Project Structure

normalization_main/
├── backend/                        # 🎯 Main application directory
│   ├── start.bat                   # 🚀 Universal launcher
│   ├── main_simple.py             # 🔧 Simple version
│   ├── main_oop_fixed.py          # 🛡️ Advanced version
│   ├── main.py                    # 📊 Original single-user
│   ├── README.md                  # 📖 Complete documentation
│   │
│   ├── services/                  # 🏗️ Core business logic
│   │   ├── auth_service.py        #   👤 User authentication
│   │   ├── ranking_service.py     #   � Rating calculations
│   │   └── input_handlers/        #   🎮 User interface logic
│   │
│   ├── rating_scraper_api/        # 🔌 Platform integrations
│   │   ├── CodeForces_api.py      #   🟦 CodeForces API
│   │   ├── leetcode_api.py        #   🟨 LeetCode GraphQL
│   │   └── CodeChef_api.py        #   � CodeChef scraping
│   │
│   ├── cousera/                   # 🎓 Educational features
│   │   └── coursera_scraper.py    #   🕷️ Profile extraction
│   │
│   ├── bonus_calculatorF/         # 🧮 Bonus calculation
│   │   └── bonus_calculator.py    #   💰 Intelligent scoring
│   │
│   ├── heatmap/                   # 📈 Visualization
│   │   └── heat_map.py            #   🎨 GitHub-style graphs
│   │
│   ├── logic_formulas/            # 🔢 Ranking algorithms
│   │   ├── formula_main.py        #   ⚖️ Core ranking logic
│   │   └── ranking_platform.py    #   🏗️ Platform management
│   │
│   └── [additional modules]       # 🔧 Supporting functionality
│
└── README.md                      # 📄 This overview file

🎉 Success Stories & Use Cases

🎯 Career Development

"Used the unified ranking to showcase my skills during job interviews. The combination of competitive programming ratings and educational certificates gave recruiters a complete picture of my abilities."

📈 Progress Tracking

"The heatmap visualization motivated me to code more consistently. Seeing my activity patterns helped me identify and fix gaps in my practice routine."

🎓 Educational Impact

"Adding my Coursera certifications boosted my ranking significantly. The intelligent bonus system recognized the value of my Stanford ML course and Google certificates."

🏆 Competitive Analysis

"Compared my performance across platforms and identified where to focus my efforts. The weighted scoring system showed that improving my CodeForces rating had the biggest impact."

🚀 Getting Started

Ready to unify your coding achievements? Here's how:

🎯 Immediate Use

Download or clone this repository
Open the backend folder
Run start.bat (Windows) or execute from terminal
Choose your preferred version (Simple recommended for first-time users)
Follow the guided setup process

📊 First Steps

Register your account (Simple/Advanced versions)
Add your coding platform usernames
Connect your Coursera profile (optional but recommended)
Generate your first unified ranking
Explore heatmaps and analytics

🎓 Maximizing Your Score

Optimize Platform Performance: Focus on platforms with higher weights
Strategic Course Selection: Choose high-value courses from prestigious institutions
Consistent Activity: Maintain regular coding practice for better heatmap metrics
Profile Optimization: Keep platform profiles public for automatic data fetching

<<<<<<< HEAD 🏆 Transform how you track and showcase your programming journey. Start building your unified coding profile today!

🚀 Get Started Now - Go to Backend Folder Readme

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