GitHub Follow Check 📊

A Streamlit web app that analyzes your GitHub network to see who follows you and who doesn't follow you back.

Features

• Network Overview: See stats on your followers, following, and mutual connections
• Profile Cards: Browse through your connections with visual profile cards
• Not Following Back: Easily identify users who don't follow you back
• Data Visualizations:
  • Network composition pie chart
  • Geographic distribution of your connections
  • Top users analysis by public repositories
• Follow-Back Opportunities: Find active users who follow you that you might want to follow back
• Historical Analysis: Track changes in your network over time
• CSV Export: Download your data for offline analysis

Technologies

• Streamlit: Powers the interactive web interface
• GitHub API: Fetches user and connection data
• SQLite: Stores user profiles and relationship data
• Pandas: Data manipulation and analysis
• Plotly: Interactive data visualizations
• Matplotlib & Seaborn: Additional charting capabilities
• Python: Core programming language

Installation

# Clone the repository
git clone https://github.com/saajann/github-followers-analyzer.git

# Navigate to project directory
cd github-follow-check

# Install required packages
pip install -r requirements.txt

# Run the app
streamlit run scripts/app.py

Usage

1. Enter your GitHub username in the sidebar
2. Optionally add a GitHub token for higher API rate limits
3. Click "Fetch Data" to analyze your network
4. Navigate through the tabs to explore different insights:
   • Overview: General stats and connections table/cards
   • Not Following Back: Users who don't reciprocate your follow
   • Visualizations: Charts and analytics about your network
   • History: Compare network changes over time

Color Legend

• 🟥 Red: You follow them, they don't follow back
• 🟩 Green: Mutual follow connection
• ⬜ White: They follow you, you don't follow back

Database

The app uses SQLite to store:

• User profile information
• Connection relationships
• Historical analysis data

All data is stored locally in the data directory.

Privacy & Rate Limits

• All data is stored locally on your machine
• Using a GitHub token increases API rate limits (strongly recommended for users with large networks)
• The app respects GitHub's API guidelines

Contributing

Contributions are welcome! Please feel free to submit a pull request.