My Digital Life – Digital Habit Tracker

A Python-based digital habit tracker and dashboard that helps you log daily habits, analyze your mood and activities, and scan your file system for organization. Visualize your progress and gain insights into your daily routines!

Features

• Daily Habit Logger:
  Log your mood, study hours, sleep hours, entertainment hours, and topics studied. Data is saved to both a CSV file and a MySQL database.

• Visualization Dashboard:
  Generate insightful charts:

  • Mood trend over time
  • Average time spent per activity
  • Correlation heatmap between mood and activities
  • Study vs. mood bubble chart
  • Stacked bar chart of daily time allocation

• File & Folder Scanner:
  Scan any directory to generate a CSV report of all files, including size, type, modification time, and path.

Project Structure

my digital life/
  ├── assets/                # Generated charts and plots
  ├── data/                  # CSV logs and reports
  ├── utils/                 # Database connection and creation scripts
  ├── dashboard.py           # Visualization and dashboard code
  ├── habit_logger.py        # Daily habit logger
  ├── system_scanner.py      # File/folder scanner
  ├── main.py                # Main menu/entry point
  ├── requirements.txt       # Python dependencies

Setup Instructions

1. Clone the Repository

git clone <repo-url>
cd "my digital life"

2. Install Python Dependencies

pip install -r requirements.txt

3. MySQL Database Setup

• Ensure you have MySQL installed and running.
• The default connection uses:
  • host: localhost
  • user: root
  • password: system
  • database: daily_habit_tracker
• You can change these credentials in utils/db_connect.py and utils/db_creation.py if needed.
• The database and table are created automatically on first run.

4. Run the Application

python main.py

Usage

You will see a menu with the following options:

1. Daily logger – Log your daily mood, study, sleep, entertainment, and topics.
2. Files and Folder Scanner – Enter a folder path to scan and generate a CSV report.
3. Visualization Generator – Generate and save summary charts in the assets/ folder.
4. Exit – Quit the application.

Dependencies

See requirements.txt for the full list. Key packages:

• numpy
• pandas
• matplotlib
• seaborn
• pymysql
• scipy
• cryptography
• fpdf

Data Storage

• CSV: All logs are appended to data/daily_logs.csv.
• MySQL: All logs are also stored in the daily_habit_tracker.daily_logs table.

Output

• Charts: Saved in the assets/ directory.
• File scan reports: Saved as data/logs.csv.

Customization

• Change database credentials in utils/db_connect.py and utils/db_creation.py.
• Modify or extend logging fields in habit_logger.py and database schema in db_creation.py.

License

MIT License.