Without any understanding of how to build a parser and surface-level knowledge of Zig, this project was a disaster. I've finished, with what may be the fastest available Lookml parser known to man, but the code behind it is of the hottest garbāge.

I wanted a way to keep my Looker view files consistent and comprehensive, so I created a GitHub Marketplace Action to do just that.

I needed a way to preview the contents of localized labels while working on lookml files, so I created a VS Code extension to do just that.

How much pandas can be replaced by SQL and dbt?

I wanted an excuse to use Zig, so I found one.

I wanted a customizable, free way to analyze my own bike rides. So the obvious answer was an end-to-end data pipeline to achieve this.

Using dbt (data build tool), I created analytics for myself regarding my own cycling training.

There are some quick and easy ways to do this and then there's Airflow.

I needed a way to get my bike rides from Garmin, convert them to a useful format and save the files in Cloud Storage.

Who in their right mind enjoys typing into a garbage, homemade CMS? Here's how I use Obsidian and markdown to publish posts.