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
JoelImgu
JoelImgu
This project is an Algorithm Visualizer where a user can visualize algorithms like Bubble Sort, Merge Sort, Quick Sort, Selection Sort, Linear Search and Binary Search.

Algo_Visualizer This project is an Algorithm Visualizer where a user can visualize common algorithms like "Bubble Sort", "Merge Sort", "Quick Sort", "

Rahul 4 Feb 07, 2022
🌀❄️🌩️ This repository contains some examples for creating 2d and 3d weather plots using matplotlib and cartopy libraries in python3.

Weather-Plotting 🌀 ❄️ 🌩️ This repository contains some examples for creating 2d and 3d weather plots using matplotlib and cartopy libraries in pytho

Giannis Dravilas 21 Dec 10, 2022
An open-source tool for visual and modular block programing in python

PyFlow PyFlow is an open-source tool for modular visual programing in python ! Although for now the tool is in Beta and features are coming in bit by

1.1k Jan 06, 2023
Declarative statistical visualization library for Python

Altair http://altair-viz.github.io Altair is a declarative statistical visualization library for Python. With Altair, you can spend more time understa

Altair 8k Jan 05, 2023
Flame Graphs visualize profiled code

Flame Graphs visualize profiled code

Brendan Gregg 14.1k Jan 03, 2023
Here are my graphs for hw_02

Let's Have A Look At Some Graphs! Graph 1: State Mentions in Congressperson's Tweets on 10/01/2017 The graph below uses this data set to demonstrate h

7 Sep 02, 2022
Data aggregated from the reports found at the MCPS COVID Dashboard into a set of visualizations.

Montgomery County Public Schools COVID-19 Visualizer Contents About this project Data Support this project About this project Data All data we use can

James 3 Jan 19, 2022
Python script for writing text on github contribution chart.

Github Contribution Drawer Python script for writing text on github contribution chart. Requirements Python 3.X Getting Started Create repository Put

Steven 0 May 27, 2022
A D3.js plugin that produces flame graphs from hierarchical data.

d3-flame-graph A D3.js plugin that produces flame graphs from hierarchical data. If you don't know what flame graphs are, check Brendan Gregg's post.

Martin Spier 740 Dec 29, 2022
Uniform Manifold Approximation and Projection

UMAP Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, bu

Leland McInnes 6k Jan 08, 2023
Geocoding library for Python.

geopy geopy is a Python client for several popular geocoding web services. geopy makes it easy for Python developers to locate the coordinates of addr

geopy 3.8k Jan 02, 2023
Statistics and Visualization of acceptance rate, main keyword of CVPR 2021 accepted papers for the main Computer Vision conference (CVPR)

Statistics and Visualization of acceptance rate, main keyword of CVPR 2021 accepted papers for the main Computer Vision conference (CVPR)

Hoseong Lee 78 Aug 23, 2022
This is simply repo for line drawing rendering using freestyle in Blender.

blender_freestyle_line_drawing This is simply repo for line drawing rendering using freestyle in Blender. how to use blender2935 --background --python

MaxLin 3 Jul 02, 2022
Lime: Explaining the predictions of any machine learning classifier

lime This project is about explaining what machine learning classifiers (or models) are doing. At the moment, we support explaining individual predict

Marco Tulio Correia Ribeiro 10.3k Dec 29, 2022
A Jupyter - Three.js bridge

pythreejs A Python / ThreeJS bridge utilizing the Jupyter widget infrastructure. Getting Started Installation Using pip: pip install pythreejs And the

Jupyter Widgets 844 Dec 27, 2022
CLAHE Contrast Limited Adaptive Histogram Equalization

A simple code to process images using contrast limited adaptive histogram equalization. Image processing is becoming a major part of data processig.

Happy N. Monday 4 May 18, 2022
An animation engine for explanatory math videos

Powered By: An animation engine for explanatory math videos Hi there, I'm Zheer 👋 I'm a Software Engineer and student!! 🌱 I’m currently learning eve

Zaheer ud Din Faiz 2 Nov 04, 2021
A tool for automatically generating 3D printable STLs from freely available lidar scan data.

mini-map-maker A tool for automatically generating 3D printable STLs from freely available lidar scan data. Screenshots Tutorial To use this script, g

Mike Abbott 51 Nov 06, 2022
The windML framework provides an easy-to-use access to wind data sources within the Python world, building upon numpy, scipy, sklearn, and matplotlib. Renewable Wind Energy, Forecasting, Prediction

windml Build status : The importance of wind in smart grids with a large number of renewable energy resources is increasing. With the growing infrastr

Computational Intelligence Group 125 Dec 24, 2022