StudySync — Smart Study Planner

A full-stack web application that helps students optimize their study time by generating personalized, priority-based daily study schedules.

Features

• Smart Course Management: Add courses with exam dates, difficulty ratings, and confidence levels
• Assignment Tracking: Track quizzes, homework, and projects with due dates
• Calendar View: Visual month-by-month calendar showing all assignments and exams
• Intelligent Scheduling Algorithm: Prioritizes study time based on:
  • Course difficulty (1-5 scale)
  • Your confidence level (1-5 scale)
  • Days until exam deadline
• Visual Schedule: Day-by-day study plan with color-coded time blocks
• Responsive Design: Works seamlessly on desktop and mobile devices
• Demo Data: Quick demo mode for testing and presentations

Tech Stack

• Backend: Python 3 with Flask framework
• Frontend: Vanilla HTML, CSS, and JavaScript (no frameworks)
• Database: SQLite (persistent storage)
• Styling: Modern CSS with Inter font, navy/blue color scheme

Installation

1. Clone or download this project

2. Create a virtual environment:

   python3 -m venv venv

3. Activate the virtual environment:

   • On macOS/Linux:

     source venv/bin/activate

   • On Windows:

     venv\Scripts\activate

4. Install dependencies:

   pip install -r requirements.txt

Running the Application

1. Start the Flask server:

   python app.py

2. Open your browser and navigate to:

   http://localhost:5000
   

3. Get started:

   • Click "Get Started" on the landing page
   • Navigate through the three tabs: Courses & Assignments, Calendar, and Schedule
   • Add your courses or click "Load Demo Data" for a quick demo
   • Add assignments to each course (quizzes, homework, projects)
   • View all assignments in the calendar view
   • Set your available study hours per day in the Schedule tab
   • Click "Generate Schedule" to see your optimized study plan

Project Structure

StudyPlanner/
├── app.py                 # Flask backend with API routes and scheduling algorithm
├── requirements.txt       # Python dependencies (Flask)
├── studysync.db          # SQLite database (auto-created on first run)
├── static/
│   ├── css/
│   │   └── style.css     # All styling with responsive design
│   └── js/
│       └── app.js        # Frontend logic and API communication
├── templates/
│   ├── index.html        # Landing page
│   └── planner.html      # Main planner interface
└── tests/
    ├── conftest.py       # Test configuration and fixtures
    ├── test_assignments.py
    └── test_schedule.py

How the Algorithm Works

The scheduling algorithm uses a priority-based approach:

Priority Calculation Formula

priority = difficulty × (6 - confidence) / days_until_exam

Priority Factors

• Higher difficulty → More study time needed
• Lower confidence → More study time needed
• Closer deadline → Higher urgency

Daily Allocation

1. For each day from today until the earliest exam:
   • Calculate priority scores for all active courses
   • Normalize priorities into percentages
   • Allocate available hours proportionally
   • Round to 0.5-hour blocks (minimum 0.5 hours per course)

Example

For a student with 4 hours available per day and these courses:

Course	Difficulty	Confidence	Days Until	Priority Score	Allocated Time
Math	5	2	7	2.86	2.0 hours
Physics	4	4	3	2.67	2.0 hours
History	2	5	14	0.14	0.5 hours (min)

API Endpoints

Pages

• GET / - Landing page
• GET /planner - Main planner interface with tabs

Courses

• GET /api/courses - Get all courses
• POST /api/add-course - Add a new course
• DELETE /api/courses/<id> - Delete a course
• POST /api/load-demo - Load demo data

Assignments

• GET /api/assignments - Get all assignments
• POST /api/assignments - Add a new assignment
• PUT /api/assignments/<id> - Toggle assignment completion status
• DELETE /api/assignments/<id> - Delete an assignment

Schedule

• POST /api/generate-schedule - Generate optimized schedule

Demo Data

The "Load Demo Data" button populates the app with 4 sample courses:

1. Calculus Exam - High difficulty (5), Low confidence (2), 10 days away
2. Physics Final - Medium-high difficulty (4), Medium confidence (3), 7 days away
3. History Essay - Low difficulty (2), High confidence (4), 14 days away
4. Programming Project - High difficulty (5), Medium-high confidence (4), 5 days away

This demonstrates how the algorithm prioritizes urgent, difficult courses while still allocating time to all subjects.

Design Highlights

• Color Palette: Navy (#1a1a2e), Accent Blue (#4361ee), Success Green (#06ffa5)
• Typography: Inter font family from Google Fonts
• UI Components:
  • Card-based layout with smooth transitions and hover effects
  • Tabbed navigation for Courses, Calendar, and Schedule views
  • Interactive calendar with assignment chips
  • Color-coded course assignments
• Responsive: Mobile-first design with breakpoints at 768px and 1024px

Code Quality

The code includes:

• Database schema with courses and assignments tables
• RESTful API endpoints for CRUD operations
• Priority-based scheduling algorithm (step-by-step comments)
• Frontend state management and event handlers
• Comprehensive test suite using pytest

This makes it easy to understand the implementation and extend functionality.

Future Enhancements

Potential features for future development:

• User authentication and persistent user accounts
• Study session tracking and analytics
• Calendar integration (Google Calendar, iCal)
• Study technique recommendations
• Mobile app version
• Export schedule to PDF

License

This project is created for educational purposes.

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Built with ❤️ for students who want to study smarter, not harder.