git-auto-commit-action VS simonw

We are also using the auto-commit action to commit the changes. We can configure the commit message and other options. Read more about the auto-commit action here. This is optional - we can also use the git action to commit the changes manually.

commit and push the changes, if any.

Stefan Zweifel - Committing the changes file from a workflow

If you want to see a real world example I encourage you to take a look at the tests I've written for git-auto-commit. You can find them on GitHub.

Everything @simonw has worked on, honestly: https://github.com/simonw

You can create a repo at https://github.com/simonw/simonw (only using your username twice) and the README.md file in there will be used to populate your profile page.

I'd leave the forked repos there, and then use pinned repositories on your profile to highlight the repositories you are most proud of. You can also use a personal README to customize your profile - I have one here for example: https://github.com/simonw

Here's one of mine that runs three times an hour: https://github.com/simonw/simonw/blob/main/.github/workflows/build.yml

As I was browsing examples for some inspiration, I stumbled upon Simon Willison's version, which features some dynamic content like recent work and blog publications. He explained how he used a combination of GitHub Actions and Python to achieve this in a blog post, and I decided to do something similar with PHP.

I have GitHub sponsors setup: https://github.com/simonw

If you really want to please me, consider sponsoring Simon Willinson the author of the framework I'm relying on .

I have 112 mostly-maintained released project listed on https://github.com/simonw/simonw/blob/main/releases.md now - most of which are tools for loading data into SQLite database files (a surprisingly under-served use-case given how ubiquitous SQLite is) and plugins for my https://datasette.io/ project for reading data back out of SQLite again.

I realized a few years ago that SQLite was the perfect tool for doing data analysis at the small-data scale, where small data is less that 10GB which is pretty much everything you might want to analyze - especially for personal projects.

So I've been building tools to fill that niche!