Snowmark: Grade Prediction & Study Planning Tool

Transform grade tracking into a targeted study plan. Snowmark helps students prioritize their studying by learning from historical performance and calculating the exact hours needed to meet academic goals.

🎯 Overview

Snowmark is a full-stack web application designed to help students optimize their academic performance. The tool learns from a user's historical grades across different subjects and assignments, predicts future performance, and provides personalized study recommendations.

Development: Built across four weekly sprints by a team of five using Scrum methodology, Git version control, and agile project management.

✨ Key Features

• Grade Tracking: Log assignments, grades, and categories across multiple subjects
• Performance Analysis: Visual insights with pie charts showing study hours by subject
• Grade Prediction: Intelligent algorithm that forecasts future grades based on historical data
• Study Planning: Calculates exact hours needed to reach specific academic goals
• Subject Management: Organize assignments and categories by subject
• Category Weighting: Customize how different assignment categories contribute to final grades
• User Isolation: Secure authentication with separate data for each user
• Responsive Design: Clean, intuitive interface optimized for all devices

🏗️ Architecture

Technology Stack

Component	Technology
Backend	Python Flask
Frontend	HTML5, CSS3, JavaScript
Database	MySQL/MariaDB
Server	Python WSGI

Project Structure

src/
├── app.py                 # Flask application & route handlers
├── db.py                  # Database schema & initialization
├── crud.py                # Create, Read, Update, Delete operations
├── query_db.py            # Database query functions
├── connect2DB.py          # Database connection management
├── requirements.txt       # Python dependencies
├── templates/             # HTML templates
│   ├── index.html        # Main dashboard
│   ├── login.html        # Login page
│   ├── register.html     # Registration page
│   ├── about.html        # About page
│   └── stats.html        # Statistics page
└── static/
    ├── css/styles.css    # Styling
    └── js/main.js        # Client-side logic

tests/                     # Comprehensive test suite
Project/                   # Project documentation & reports

🚀 Getting Started

Prerequisites

• Python 3.8+
• MySQL/MariaDB server
• pip (Python package manager)

Installation

1. Clone the repository

   git clone <repository-url>
   cd Snowmark

2. Install dependencies

   pip install -r src/requirements.txt

3. Configure database connection

   • Update database credentials in src/connect2DB.py
   • Ensure MySQL/MariaDB server is running

4. Initialize the database

   python src/db.py

5. Run the application

   python src/app.py

6. Access the application

   • Open your browser and navigate to http://localhost:5000

📊 Core Functionality

User Management

• Register: Create a new account with secure password storage
• Login/Logout: Session-based authentication
• User Isolation: Each user has separate data and sessions

Grade Management

• Add Assignments: Create new assignments with grades, weights, and categories
• Edit/Delete: Modify or remove existing assignments
• Subject Organization: Manage multiple subjects independently
• Category Management: Group assignments by type (homework, exams, projects, etc.)

Analytics & Prediction

• Grade Summary: View current grades across all subjects and categories
• Visual Analytics: Pie charts showing study hour distribution
• Performance Metrics: Historical grade analysis
• Predictive Modeling: Algorithm that learns from past performance to forecast future grades
• Study Planning: Calculate hours needed to achieve target grades

🧪 Testing

Comprehensive test suite covering:

• Database schema and operations
• Authentication and user isolation
• CRUD operations for all entities
• Grade prediction logic
• Route/API verification
• End-to-end workflows

Run tests:

python -m pytest tests/

📚 Documentation

• Project Charter - Project vision and goals
• Requirements - Detailed functional requirements
• Test Plan - Testing strategy and coverage
• Test Report - Test execution results
• User Stories & Use Cases - User requirements
• Sprint Retrospectives - Team reflections and improvements
• Phase Summaries - Detailed implementation notes for each phase

🔄 Development Process

This project demonstrates professional software engineering practices:

• Scrum Methodology: Four 1-week sprints with daily standups
• Version Control: Git with feature branches and merge requests
• Code Reviews: Peer review process for all changes
• Testing: Test-driven development with comprehensive coverage
• Documentation: Requirements, design docs, and retrospectives
• Team Collaboration: Cross-functional roles (development, testing, QA)

Key Phases

1. Phase 1-2: Core functionality (add, edit, delete assignments)
2. Phase 3-4: Database architecture and user authentication
3. Phase 5-6: Analytics, prediction, and database-only architecture
4. Phase 7: Subject management and final refinements

📈 What We Learned

• Full-Stack Development: Integrating Python backend with web frontend
• Database Design: Schema design, normalization, and optimization
• Agile Project Management: Scrum ceremonies, sprint planning, retrospectives
• Git Workflows: Branching strategies, merge conflicts, collaborative development
• Software Quality: Testing strategies, code reviews, and continuous improvement
• Team Communication: Daily standups, documentation, knowledge sharing

👥 Team

Built by a team of five software engineers practicing Scrum methodology and professional development practices.

📝 License

This project was created as an academic exercise for SE101.

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Last Updated: December 2025 Status: Complete ✅