Smart Study Tracker

A Smart study tracking application with GUI, data visualization, and progress monitoring built with Python and Tkinter.

Features

• Session Logging: Track study sessions with subject, duration, productivity level, and notes
• Data Visualization:
  • Pie chart showing study time distribution by subject
  • Time spent charts for visual analysis
• Progress Monitoring:
  • Weekly summary with total sessions, time studied, and average productivity
  • View all study sessions in a sortable table
• Data Management:
  • Export data to CSV for external analysis
  • Clear all data functionality
  • Persistent storage using JSON

Screenshots

Main Interface

The main application window with session logging form and progress viewing options

All Study Sessions

A view of all logged study sessions with date, subject, duration, productivity, and notes

Weekly Summary

Summary statistics for the last 7 days including total sessions, time studied, and most studied subject

Subject Distribution Chart

Pie chart visualization showing the percentage of time spent on each subject

Installation

1. Clone the repository:

   git clone https://github.com/ksu-is/Smart-Study.git
   cd tracker_app

2. Create and activate a virtual environment:

   python -m venv .venv
   source .venv/bin/activate

3. Install dependencies:

   pip install matplotlib

Usage

Run the application:

python main.py

Logging a Study Session

1. Enter the subject name
2. Enter duration in minutes
3. Set productivity level
4. Add notes
5. Click "Save Study Session"

Viewing Progress

• View Subject Distribution: Pie chart of time allocation across subjects
• View Time Spent Chart: Bar chart showing study time patterns
• Weekly Summary: Statistics for the last 7 days
• View All Sessions: Complete table of all logged sessions
• Export CSV: Download your data in CSV format

Requirements

• Python 3.13+
• tkinter
• matplotlib

License

This project is licensed under the MIT License - see the LICENSE file for details.