In my freetime, I love throwing together personal projects. I follow the motto of "move fast and break things" and I learn quickest when I have to fix something.
I use the tool Quizlet ↗ quite a bit, and I find it to be one of the study tools that is most helpful. However, it can be quite bloated as it is hindered by its web app nature.
I wanted something faster, lighter, and easier to use, so I created Swiftlet ↗, a stripped-down version of Quizlet, written entirely in Swift, and accessible via the CLI.
This meant that users could create study sets quickly and with complete control over their content since each file is stored locally.
I am a Raycast ↗ power user, and when I realized there was the opportunity for user extension, I quickly started to toy around with it.
My first foray into this was the Breathe extension, which provided users quick access to mindfulness meditation.
Through Markdown, TypeScript, and a bit of hacking, I was able to show users a simple gif that guided them through breathing exercises.
Some of my first API work was with quotable.io ↗, a simple but strong API that holds a massive repository of easily accessible quotes.
I wanted Raycast users to be able to quickly get a variety of quotes right from their Spotlight search.
A quick connection via this API allowed me to easily generate and regenerate quotes and format them with Markdown.
If you read the brief introduction I gave, then you know that I adore cars. In particular, I adore all 80 Porsche 964 Turbo 3.6 S ↗.
However, due to their low production run and general heritage, they trade hands for around $1,000,000. Therefore, I wanted to understand if there was any chance for me to own an air-cooled 911.
To do this, I scraped data from Cars&Bids ↗ and used matplotlib and NumPy to create a graph of all sold air-cooled 911s.