afaqAhmadK/GithubRepo-Analyzer

GitHub Repository Analyzer 📊

This project delves into any public GitHub repository to assess the health status of open-source projects. Specifically, it explores the following key areas:

1. 1.Commit History 🕰️
2. 2.Most Active Users 🧑‍💻

This project is additionally maintained on GitHub. Please note that both versions are maintained separately.

🚀 How it Works

The analyzer collects data from two essential open-source GitHub API endpoints:

• —Contributors: https://api.github.com/repos/facebook/react/contributors
• —Commits: https://api.github.com/repos/facebook/react/commits

This collected JSON information is then consolidated and presented in various useful formats:

1. 1.Streamlit Deployed App 🌐: Access the live application here. (Please note: The link may occasionally be down. Feel free to email if you'd like it to be reactivated.)
2. 2.Generated PDF Report 📄
3. 3.Supportive Visualizations (Images) 🖼️

Additional Notes:

• —When running the script locally via argparse, the PDF report and supporting images will be saved to your local machine.
• —When utilizing the Streamlit application, the PDF will only be saved upon clicking the 'Generate PDF' button.
• —All generated figures will be displayed directly within the Streamlit interface.

📁 File Structure & Explanation

Here's a breakdown of the project's key files:

• —main.py: 🧩 The central file that orchestrates different parts of the program.

Files located in the scripts/ directory:

• —app.py: 📱 Contains the core Streamlit application logic.
• —contributors.py: 📊 Gathers information about repository contributors, including:
• —Top and lowest contributors.
• —Respective bar-plot visualizations of their contributions.
• —commits.py: 📜 Collects data regarding the repository's commit history, offering:
• —Prints authors by greatest commit count & timeline.
• —Enables in-line (CMD) visualization using Python's tabulate module.
• —Produces insightful visualizations such as:
• —Commits per day 📅
• —Commits per day per user 👨‍💻
• —Commit word cloud ☁️
• —variables.py: ⚙️ Houses all global variables and their accompanying documentation.

🚀 Getting Started: How to Run

You have several options to run this project:

1. 1.Local Streamlit App 🖥️:
2. 2.First, fork the repository to your local machine.
3. 3.Ensure you have Streamlit installed (pip install streamlit).
4. 4.Run the application using: streamlit run app.py

1. 1.Streamlit Community Cloud Deployment ☁️:
2. 2.Easily deploy the app using the Streamlit Community Cloud platform.

1. 1.Command-Line Interface (CLI) with Argparse 👨‍ terminals:
2. 2.For help and available arguments, run: python main.py -h
3. 3.You can specify the repository in two ways:
4. 4.python main.py --repo facebook/react
5. 5.python main.py --repo https://github.com/facebook/react
6. 6.Both commands will work seamlessly.

1. 1.Hugging Face Spaces Deployment ✨:
2. 2.The app is also deployed here. Feel free to check it out!

✨ Sample Output

To see an example of the output when the script is run through the command line, please refer to the facebook/react directory within the repository.

Branch Details

1. 1.main: main
2. 2.hf-display: branch used to diagnose any display config problem on hugging face space interface

💡 Possible Future Updates

We're always looking to improve! Here are some potential enhancements:

1. 1.Docker Deployment 🐳
2. 2.Deployment on Additional Free-Hosted Cloud Services (Already Added! Check out this commit for the Hugging Face Spaces deployment) ✅
3. 3.Integration of More API Endpoints 🔗