Godot GitHub issue statistics

This repository gathers hardware and software information reported by users on the issue tracker of the main Godot repository. This information is then displayed on a website.

As such, these statistics are not representative of the entire Godot community, but they allow seeing what kind of hardware and software is popular among issue reporters.

How it works

Backend

• Using GitHub's GraphQL API, 30 requests are performed to fetch the description, author and creation date of the 3,000 latest issues.
• In the resulting data, the System information field of the issue is parsed in a case-sensitive, punctuation-insensitive manner.
  • The operating system, CPU and GPU is detected using this information provided by the user. All other information (such as the number of physical cores or amount of video memory) is inferred from the model names reported by the user.¹
  • If there's no valid System information section or it contains no usable information, the issue is ignored.
• A dictionary of set() values is created with all possible values that users may be counted in. Each detected value is added to a set of users who have reported this information. This ensures that a user may only increment each statistic once, even if they've reported several issues with the same hardware and software configuration. If a single user has reported several issues with different hardware and software configurations, then all configurations are counted from this user.
• The dictionary is written to a JSON file, with the set() value replaced by the number of users who have been detected to be using the hardware/software in question.
• The resulting JSON file + the frontend is deployed to GitHub Pages using GitHub Actions every day.

Frontend

• The frontend is a single index.html page, plus the third-party dependencies mentioned below. No frontend building is required.
• Frappe Charts is used to display charts.
• Ky is used to make an HTTP request to the JSON file.
• Water.css is used for styling the page.

Development

Follow these instructions to set up this site locally for development purposes:

• Make sure you have Python 3.7 or later, pip and virtualenv.
• Create a virtualenv and activate it: virtualenv venv && . venv/bin/activate.
• Within the virtualenv, install dependencies by running pip install -r requirements.txt.
• Copy .env.example to .env and fill in the GitHub API key with a personal access token. You can generate one here (it must have the public_repo scope).
• Run python build.py to fetch issue data from the GitHub API.
• Start a local web server in the root directory then browse index.html.

License

Copyright © 2023-present Hugo Locurcio and contributors

Unless otherwise specified, files in this repository are licensed under the MIT license. See LICENSE.md for more information.

Footnotes

1. In rare scenarios, this can be inaccurate. In this case, the script errs on the side of the most popular variant. For instance, the GeForce GTX 1060 is considered to always have 6 GB of VRAM, even though it also exists in a less popular 3 GB variant. See comments in build.py's hardware detection routine for details. ↩