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A package to visualize your browser history :D

Project description

Browser History Analytics 2

A Python package that analyzes and visualizes your browser history data with interactive charts and insights.


Features Overview Preview
  • Category Analysis: Automatically categorizes websites (Social Media, Development, Entertainment, etc.)
  • Time-based Insights: Hourly and daily browsing patterns with heatmaps
  • Summary Statistics: Key metrics about your browsing habits
  • Interactive Filters: Filter by date range and categories
  • Raw Data View: Search and export your browsing data
  • Multi-browser Support: Works with Chrome, Firefox, Safari, and more
Preview GIF

Installation

Option 1: Install from source

git clone https://github.com/arpy8/browser-history-analytics-2.git
cd browser-history-analytics-2
pip install -e .

Option 2: Install directly

pip install https://github.com/arpy8/browser-history-analytics-2/archive/main.zip

Usage

Command prompt:

pip install https://github.com/arpy8/browser-history-analytics-2/archive/main.zip && bha

Powershell:

pip install https://github.com/arpy8/browser-history-analytics-2/archive/main.zip ; bha

This will launch the web application in your default browser.

What You'll See

Dashboard Tabs

  1. Home: Main dashboard with visualizations and summary statistics
  2. Raw Data: Searchable table with export functionality
  3. Additional Info: Detailed insights and browsing habits analytics

Visualizations

  • Top Domains: Bar chart of most visited websites
  • Activity Timeline: Daily visits over time
  • Activity Heatmap: Browsing patterns by hour and day of week
  • Category Distribution: Pie chart of website categories
  • Hourly Patterns: Bar chart showing peak browsing hours

Requirements

  • Python 3.7+
  • Browser history data (automatically detected)

Dependencies

  • streamlit
  • plotly
  • pandas
  • browser-history
  • numpy
  • seaborn
  • matplotlib
  • urllib3

Privacy Note

This tool only reads your local browser history files. No data is sent to external servers – everything runs locally on your machine.

Supported Browsers

  • Google Chrome
  • Mozilla Firefox
  • Safari
  • Microsoft Edge
  • Opera

Contributing

Feel free to open issues and submit pull requests!

License

MIT License

Author

Arpit Sengar (@arpy8)

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