GitHub Organization Wrapped Generator

Overview

A GitHub Org Data Analyzer is a tool designed to analyze GitHub activity data. It provides insights into various metrics such as total active days, longest gaps, busiest days, longest streaks, month-wise activity, time-wise activity, developer activity, and repository activity based on logs of GitHub activity.

Features

• Total Active Days: Calculate the total number of active days.
• Longest Gap: Identify the longest gap between activities.
• Busiest Day: Find the day with the highest number of activities.
• Longest Streak: Determine the longest streak of consecutive active days.
• Month-wise Activity: Visualize activity on a monthly basis.
• Time-wise Activity: Visualize activity based on the time of day.
• Developer Activity: Analyze the activity of individual developers.
• Repository Activity: Analyze the activity of repositories.

Setup

Prerequisites

• Get logs of your organization's using webhook created on discord through github
• use extension like Discrub to download the logs in csv format
• Setup virtual environment

  python -m venv venv
  source venv/bin/activate

Installation

1. Clone the repository:

   git clone https://github.com/dk-a-dev/github-org-wrapped-gen.git
   cd github-org-wrapped-gen

2. Install the required packages:

   pip install -r requirements.txt

Warning: clean the data before uploading it to the application

Usage

1. Run the Streamlit application:

   streamlit run core/ui.py

2. Open your web browser and navigate to the URL provided by Streamlit.
3. Upload a CSV file containing GitHub activity data.
4. The application will display various metrics and visualizations based on the uploaded data.

File Structure

• core/main.py: Contains the core functions for data analysis.
• core/ui.py: Contains the Streamlit UI code.
• config.yaml: Configuration file for authentication.
• README.md: Project documentation.

Example

https://gdsc-wrapped-2024.streamlit.app/ (Required organization logs to be uploaded, with data access perms)

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

License

This project is licensed under the MIT License. See the LICENSE file for more information.

Contact

For any questions or feedback, please contact Dev Keshwani.