Generate visualizations of GitHub user and repository statistics using GitHub Actions.

Overview

GitHub Stats Visualization

Generate visualizations of GitHub user and repository statistics using GitHub Actions.

This project is currently a work-in-progress; there will always be more interesting stats to display.

Background

When someone views a profile on GitHub, it is often because they are curious about a user's open source projects and contributions. Unfortunately, that user's stars, forks, and pinned repositories do not necessarily reflect the contributions they make to private repositories. The data likewise does not present a complete picture of the user's total contributions beyond the current year.

This project aims to collect a variety of profile and repository statistics using the GitHub API. It then generates images that can be displayed in repository READMEs, or in a user's Profile README.

Since the project runs on GitHub Actions, no server is required to regularly regenerate the images with updated statistics. Likewise, since the user runs the analysis code themselves via GitHub Actions, they can use their GitHub access token to collect statistics on private repositories that an external service would be unable to access.

Disclaimer

If the project is used with an access token that has sufficient permissions to read private repositories, it may leak details about those repositories in error messages. For example, the aiohttp library—used for asynchronous API requests—may include the requested URL in exceptions, which can leak the name of private repositories. If there is an exception caused by aiohttp, this exception will be viewable in the Actions tab of the repository fork, and anyone may be able to see the name of one or more private repositories.

Due to some issues with the GitHub statistics API, there are some situations where it returns inaccurate results. Specifically, the repository view count statistics and total lines of code modified are probably somewhat inaccurate. Unexpectedly, these values will become more accurate over time as GitHub caches statistics for your repositories. Additionally, repositories that were last contributed to more than a year ago may not be included in the statistics due to limitations in the results returned by the API.

For more information on inaccuracies, see issue #2, #3, and #13.

Installation

  1. Create a personal access token (not the default GitHub Actions token) using the instructions here. Personal access token must have permissions: read:user and repo. Copy the access token when it is generated – if you lose it, you will have to regenerate the token.
    • Some users are reporting that it can take a few minutes for the personal access token to work. For more, see #30.
  2. Click here to create a copy of this repository. Note: this is not the same as forking a copy because it copies everything fresh, without the huge commit history.
  3. If this is the README of your fork, click this link to go to the "Secrets" page. Otherwise, go to the "Settings" tab of the newly-created repository and go to the "Secrets" page (bottom left).
  4. Create a new secret with the name ACCESS_TOKEN and paste the copied personal access token as the value.
  5. It is possible to change the type of statistics reported.
    • To ignore certain repos, add them (in owner/name format e.g., jstrieb/github-stats) separated by commas to a new secret—created as before—called EXCLUDED.
    • To ignore certain languages, add them (separated by commas) to a new secret called EXCLUDED_LANGS.
    • To show statistics only for "owned" repositories and not forks with contributions, add an environment variable (under the env header in the main workflow) called EXCLUDE_FORKED_REPOS with a value of true.
  6. Go to the Actions Page and press "Run Workflow" on the right side of the screen to generate images for the first time. The images will be periodically generated every hour, but they can be manually regenerated by manually running the workflow.
  7. Check out the images that have been created in the generated folder.
  8. To add your statistics to your GitHub Profile README, copy and paste the following lines of code into your markdown content. Change the username value to your GitHub username.
    ![](https://github.com/username/github-stats/blob/master/generated/overview.svg)
    ![](https://github.com/username/github-stats/blob/master/generated/languages.svg)
  9. Link back to this repository so that others can generate their own statistics images.
  10. Star this repo if you like it!

Support the Project

There are a few things you can do to support the project:

  • Star the repository (and follow me on GitHub for more)
  • Share and upvote on sites like Twitter, Reddit, and Hacker News
  • Report any bugs, glitches, or errors that you find

These things motivate me to to keep sharing what I build, and they provide validation that my work is appreciated! They also help me improve the project. Thanks in advance!

If you are insistent on spending money to show your support, I encourage you to instead make a generous donation to one of the following organizations. By advocating for Internet freedoms, organizations like these help me to feel comfortable releasing work publicly on the Web.

Related Projects

Owner
Aditya Thakekar
Electronics engineer turned consultant with over 7 years of experience.
Aditya Thakekar
With Holoviews, your data visualizes itself.

HoloViews Stop plotting your data - annotate your data and let it visualize itself. HoloViews is an open-source Python library designed to make data a

HoloViz 2.3k Jan 04, 2023
Learn Basic to advanced level Data visualisation techniques from this Repository

Data visualisation Hey, You can learn Basic to advanced level Data visualisation techniques from this Repository. Data visualization is the graphic re

Shashank dwivedi 16 Jan 03, 2023
Python scripts to manage Chia plots and drive space, providing full reports. Also monitors the number of chia coins you have.

Chia Plot, Drive Manager & Coin Monitor (V0.5 - April 20th, 2021) Multi Server Chia Plot and Drive Management Solution Be sure to ⭐ my repo so you can

338 Nov 25, 2022
A minimal Python package that produces slice plots through h5m DAGMC geometry files

A minimal Python package that produces slice plots through h5m DAGMC geometry files Installation pip install dagmc_geometry_slice_plotter Python API U

Fusion Energy 4 Dec 02, 2022
Keir&'s Visualizing Data on Life Expectancy

Keir's Visualizing Data on Life Expectancy Below is information on life expectancy in the United States from 1900-2017. You will also find information

9 Jun 06, 2022
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)

100 pandas puzzles Puzzles notebook Solutions notebook Inspired by 100 Numpy exerises, here are 100* short puzzles for testing your knowledge of panda

Alex Riley 1.9k Jan 08, 2023
A blender import/export system for Defold

defold-blender-export A Blender export system for the Defold game engine. Setup Notes There are no exhaustive documents for this tool yet. Its just no

David Lannan 27 Dec 30, 2022
Functions for easily making publication-quality figures with matplotlib.

Data-viz utils 📈 Functions for data visualization in matplotlib 📚 API Can be installed using pip install dvu and then imported with import dvu. You

Chandan Singh 16 Sep 15, 2022
A Python wrapper of Neighbor Retrieval Visualizer (NeRV)

PyNeRV A Python wrapper of the dimensionality reduction algorithm Neighbor Retrieval Visualizer (NeRV) Compile Set up the paths in Makefile then make.

2 Aug 29, 2021
🐞 📊 Ladybug extension to generate 2D charts

ladybug-charts Ladybug extension to generate 2D charts. Installation pip install ladybug-charts QuickStart import ladybug_charts API Documentation Loc

Ladybug Tools 3 Dec 30, 2022
python partial dependence plot toolbox

PDPbox python partial dependence plot toolbox Motivation This repository is inspired by ICEbox. The goal is to visualize the impact of certain feature

Li Jiangchun 723 Jan 07, 2023
This is Pygrr PolyArt, a program used for drawing custom Polygon models for your Pygrr project!

This is Pygrr PolyArt, a program used for drawing custom Polygon models for your Pygrr project!

Isaac 4 Dec 14, 2021
flask extension for integration with the awesome pydantic package

Flask-Pydantic Flask extension for integration of the awesome pydantic package with Flask. Installation python3 -m pip install Flask-Pydantic Basics v

249 Jan 06, 2023
Monochromatic colorscheme for matplotlib with opinionated sensible default

Monochromatic colorscheme for matplotlib with opinionated sensible default If you need a simple monochromatic colorscheme for your matplotlib figures,

Aria Ghora Prabono 2 May 06, 2022
Joyplots in Python with matplotlib & pandas :chart_with_upwards_trend:

JoyPy JoyPy is a one-function Python package based on matplotlib + pandas with a single purpose: drawing joyplots (a.k.a. ridgeline plots). The code f

Leonardo Taccari 462 Jan 02, 2023
Numerical methods for ordinary differential equations: Euler, Improved Euler, Runge-Kutta.

Numerical methods Numerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary

Aleksey Korshuk 5 Apr 29, 2022
An application that allows you to design and test your own stock trading algorithms in an attempt to beat the market.

StockBot is a Python application for designing and testing your own daily stock trading algorithms. Installation Use the

Ryan Cullen 280 Dec 19, 2022
🐍PyNode Next allows you to easily create beautiful graph visualisations and animations

PyNode Next A complete rewrite of PyNode for the modern era. Up to five times faster than the original PyNode. PyNode Next allows you to easily create

ehne 3 Feb 12, 2022
A small timeseries transformation API built on Flask and Pandas

#Mcflyin ###A timeseries transformation API built on Pandas and Flask This is a small demo of an API to do timeseries transformations built on Flask a

Rob Story 84 Mar 25, 2022
Simple spectra visualization tool for astronomers

SpecViewer A simple visualization tool for astronomers. Dependencies Python = 3.7.4 PyQt5 = 5.15.4 pyqtgraph == 0.10.0 numpy = 1.19.4 How to use py

5 Oct 07, 2021