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.
When I got to college, I started off physically writing all of my notes into a notebook but quickly realized that wasn't feasible when I started to writing code blocks.
To solve this, I spent a year and a half trying every text editor under the sun, from Apple Notes ↗ to Bear ↗ and from Notion ↗ to Neovim ↗. All of these worked really well, but each had their own issue that just bugged me ever so slightly. Eventually, I settled on Obsidian ↗ which I have been using for the past year.
In my hunt for the best editor, I didn't think to question the actual "language" I was writing them in. Markdown ↗ is fantastic and better than anything else out there, but it became frustrating to repeatedly hit '#' just to get to get a heading, or ``` to get a code block. I wanted something that was more intuitive and felt natural to the patterns that all of our hands are accustomed to.
Therefore, I created HRML ↗ which allows you to access every major Markdown function without having your hands ever leave the homerow. The "language" is written in Rust, and compiled via WASM ↗ to be accessible in a JavaScript editor that I created alongside it.
However, the end goal is to extend this into Obsidian, where I can feel at home with my nodes.
Everyone waits the whole year for their Spotify Wrapped, but what if you could view it every month? That was (probably) Apple's pitch for Apple Music Replay, which originally started as a yearly rewind, but became monthly in 2024.
However, one feature of Apple Music that I appreciate is the ability to export your library as an XML file, giving you complete control over your information.
I wanted to create a web application that let users import their XML file and gave them a series of rich statistics which rivaled their Replay. The difference is that people can use this whenever they want.
AM2WEB↗ is a Flask + MySQL application that allows a user to create an account, upload their Apple Music XML file, and view a series of rich statistics, informing them on their listening habits.
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.