🎓 Student Performance Tracker

A comprehensive web-based academic management system built with Streamlit and SQLite for tracking student performance, generating analytics, and managing educational data.

🚀 Live Demo

🌐 Access the Application

📋 Table of Contents

Overview
Features
Tech Stack
Installation
Usage Guide
Project Structure
Technical Implementation
Screenshots
Contributing
License
Contact

🎯 Overview

The Student Performance Tracker is a full-stack web application designed to streamline academic performance management for educational institutions. Built with modern web technologies, it provides real-time analytics, automated grade calculations, and comprehensive reporting capabilities.

🎨 Key Highlights

📊 Real-time Analytics: Live performance dashboards with interactive visualizations
🎯 Automated Grading: Intelligent grade calculation system (A+ to F)
📱 Responsive Design: Cross-platform compatibility with modern UI/UX
⚡ SQLite Database: Lightweight, portable database with optimized queries
🛡️ Data Validation: Comprehensive input validation and error handling
📤 Export Capabilities: CSV export for all data types

✨ Features

👥 Student Management System

Complete CRUD operations with search and filtering
Class and section-based organization (10A, 10B, 11A, etc.)
Student profile management with date of birth tracking
Bulk data export functionality
Advanced search with multiple criteria

📚 Subject Management

Dynamic subject creation and organization
Quick-add functionality for common subjects
Subject-wise performance tracking
Unique subject validation to prevent duplicates

📝 Assessment & Marks Management

Flexible marks entry with multiple assessment types (Quiz, Assignment, Midterm, Final)
Real-time percentage calculation and grade assignment
Assessment date tracking and validation
Maximum marks customization (default: 100)
Input validation to prevent invalid data entry

📋 Performance Analytics & Reporting

Individual student report cards with detailed breakdowns
Class-wise performance analytics with comparative metrics
Subject-wise performance analysis and trends
Grade distribution analysis across classes
Pass/fail rate tracking with visual indicators
Top performers identification and ranking

📊 Interactive Visualizations

Grade distribution pie charts and bar graphs
Class performance comparison charts
Subject performance analysis with range visualization
Performance trends over time
Pass/fail analysis with risk assessment
Top performers leaderboard with ranking

⚙️ System Administration

Database management and monitoring
Sample data generation for testing
Data backup and export functionality
Application settings and preferences
System statistics and health monitoring

🛠️ Tech Stack

Frontend & Web Framework

Streamlit - Modern web app framework for rapid development
Pandas - Data manipulation and analysis
Plotly - Interactive data visualizations
Altair - Statistical visualizations

Backend & Database

Python 3.8+ - Core programming language
SQLite - Lightweight, serverless database
SQLAlchemy-style queries - Optimized database operations

Development & Deployment

Git - Version control
GitHub - Code repository and collaboration
Streamlit Cloud - Cloud deployment platform

🚀 Installation

Prerequisites

Python 3.8 or higher
Git (for cloning the repository)

Quick Start

Clone the Repository

git clone https://github.com/Its-Kratik/student-performance-tracker.git
cd student-performance-tracker

Install Dependencies

pip install -r requirements.txt

Run the Application

streamlit run app.py

Access the Application

Open your browser and navigate to http://localhost:8501
The database will be automatically initialized with sample data

Alternative Setup

python install.py  # For Python 3.13 compatibility

📖 Usage Guide

Getting Started Workflow

🏠 Dashboard: Overview of system statistics and quick actions
👥 Manage Students: Add, edit, delete, and search students
📚 Manage Subjects: Create and organize subject curriculum
📝 Enter Marks: Input student assessments and grades
📋 Report Cards: Generate individual student reports
📊 Class Analytics: Analyze class and section performance
📈 Visual Reports: Interactive charts and insights
⚙️ Settings: Configure application preferences

Key Operations

Adding Students: Navigate to "Manage Students" → "Add New Student"
Entering Marks: Go to "Enter Marks" → Select student and subject → Input scores
Viewing Analytics: Access "Class Analytics" → Select class/section → View insights
Exporting Data: Use export buttons in any section → Download CSV files

📁 Project Structure

student-performance-tracker/
├── 📄 app.py                    # Main application entry point
├── 📂 pages/                    # Streamlit pages
│   ├── 1_Manage_Students.py     # Student management interface
│   ├── 2_Manage_Subjects.py     # Subject management interface
│   ├── 3_Enter_Update_Marks.py  # Marks entry and updating
│   ├── 4_Student_Report_Card.py # Individual report generation
│   ├── 5_Class_Analytics.py     # Class performance analytics
│   ├── 6_Visual_Reports.py      # Interactive visual dashboards
│   └── 7_Settings.py            # Application configuration
├── 📂 models/                   # Data models and business logic
│   ├── student.py               # Student model and operations
│   ├── subject.py               # Subject model and operations
│   └── marks.py                 # Marks model and calculations
├── 📂 db/                       # Database layer
│   └── connection.py            # SQLite connection and utilities
├── 📂 utils/                    # Utility functions
│   └── analytics.py             # Advanced analytics functions
├── 📂 tests/                    # Test suite
│   └── test_cases.py            # Unit and integration tests
├── 📄 requirements.txt          # Python dependencies
├── 📄 install.py                # Installation script
├── 📄 README.md                 # Project documentation
└── 📄 student_tracker.db        # SQLite database (auto-generated)

🔧 Technical Implementation

Database Schema

Student Table

CREATE TABLE Student (
    student_id INTEGER PRIMARY KEY AUTOINCREMENT,
    name TEXT NOT NULL CHECK(length(trim(name)) >= 2),
    class TEXT NOT NULL CHECK(class IN ('10', '11', '12')),
    section TEXT NOT NULL CHECK(section IN ('A', 'B', 'C')),
    dob DATE,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
)

Subject Table

CREATE TABLE Subject (
    subject_id INTEGER PRIMARY KEY AUTOINCREMENT,
    subject_name TEXT NOT NULL UNIQUE CHECK(length(trim(subject_name)) >= 2),
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
)

Marks Table

CREATE TABLE Marks (
    mark_id INTEGER PRIMARY KEY AUTOINCREMENT,
    student_id INTEGER NOT NULL,
    subject_id INTEGER NOT NULL,
    marks_obtained INTEGER NOT NULL CHECK(marks_obtained >= 0),
    max_marks INTEGER DEFAULT 100 CHECK(max_marks > 0),
    assessment_date DATE DEFAULT (date('now')),
    assessment_type TEXT DEFAULT 'Assignment' 
        CHECK(assessment_type IN ('Quiz', 'Assignment', 'Midterm', 'Final', 'Project')),
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    FOREIGN KEY (student_id) REFERENCES Student(student_id) ON DELETE CASCADE,
    FOREIGN KEY (subject_id) REFERENCES Subject(subject_id) ON DELETE CASCADE,
    CHECK(marks_obtained <= max_marks)
)

Grade Calculation System

Percentage Range	Grade	Description
90% - 100%	A+	Outstanding
80% - 89%	A	Excellent
70% - 79%	B+	Very Good
60% - 69%	B	Good
50% - 59%	C+	Above Average
40% - 49%	C	Average
Below 40%	F	Fail

Key Algorithms

Percentage Calculation

def calculate_percentage(marks_obtained: int, max_marks: int) -> float:
    if max_marks == 0:
        return 0.0
    return round((marks_obtained / max_marks) * 100, 2)

Grade Assignment

def calculate_grade(percentage: float) -> str:
    if percentage >= 90: return "A+"
    elif percentage >= 80: return "A"
    elif percentage >= 70: return "B+"
    elif percentage >= 60: return "B"
    elif percentage >= 50: return "C+"
    elif percentage >= 40: return "C"
    else: return "F"

Performance Optimizations

Database Indexing: Optimized queries with proper indexes
Connection Pooling: Efficient database connection management
Caching: Streamlit caching for improved performance
Query Optimization: Optimized SQL queries for large datasets

📸 Screenshots

Dashboard Overview

Student Management

Class Analytics

Visual Reports

🤝 Contributing

We welcome contributions to improve the Student Performance Tracker! Here's how you can help:

Getting Started

Fork the Repository

git fork https://github.com/Its-Kratik/student-performance-tracker.git

Create a Feature Branch

git checkout -b feature/amazing-feature

Make Your Changes
- Follow Python PEP 8 style guidelines
- Add tests for new functionality
- Update documentation as needed
Commit Your Changes

git commit -m "Add amazing feature"

Push to Your Branch

git push origin feature/amazing-feature

Open a Pull Request

Development Guidelines

Code Style: Follow PEP 8 conventions
Testing: Add unit tests for new features
Documentation: Update README and inline docs
Commits: Use clear, descriptive commit messages

Areas for Contribution

🔧 New Features: Additional analytics, reporting capabilities
🐛 Bug Fixes: Identify and resolve issues
📚 Documentation: Improve guides and examples
🎨 UI/UX: Enhance user interface and experience
⚡ Performance: Optimize database queries and rendering

🙋♂️ Contact

Kratik Jain - Full Stack Developer & Data Enthusiast

📧 Email: kratikjain121@gmail.com
📱 Phone: +91 7410990404
💼 LinkedIn: kratik-jain12
🔗 GitHub: Its-Kratik
🌐 Live App: Student Performance Tracker

🙏 Acknowledgments

Streamlit Team for the amazing framework
SQLite for the reliable database engine
Pandas for powerful data manipulation
Plotly for interactive visualizations
Open Source Community for inspiration and support

🔮 Future Roadmap

Phase 1 - Enhanced Analytics

Advanced statistical analysis and predictive modeling
Comparative benchmarking across institutions
Performance trend forecasting

Phase 2 - Extended Features

PDF report generation with custom templates
Email notification system for parents/teachers
Multi-language support for international use
Advanced user roles and permissions system

Phase 3 - Integration & APIs

REST API development for third-party integrations
Mobile application development
Cloud storage integration
Real-time collaboration features

⭐ Show Your Support

If you find this project helpful, please consider:

⭐ Starring the repository
🐛 Reporting issues and bugs
💡 Suggesting new features
🤝 Contributing to the codebase
📢 Sharing with others

Built with ❤️ by Kratik Jain

Empowering education through data-driven insights 📚✨

Name		Name	Last commit message	Last commit date
Latest commit History 11 Commits
.streamlit		.streamlit
db		db
models		models
pages		pages
tests		tests
utils		utils
Readme.md		Readme.md
app.py		app.py
install.py		install.py
requirements.txt		requirements.txt

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