programming - Semicolon Software

Semicolon Software

programming

A collection of 6 posts

Python Decorators, Explained

Python Decorators, Explained

Decorators in Python are a very powerful albeit mind-bending and under-documented tool. They are useful for many things, including changing how a function is executed (e.g. for denoting that an API endpoint requires authentication) or to register a function as a handler (e.g. to register different parser functions

D/Tox - Will it cure you or kill you?

D/Tox - Will it cure you or kill you?

For this year's christmas project, I have worked on a little game idea — introducing D/Tox, a game that lets you figure out if you can tell if a molecule is good or bad for you. The game will randomly select 10 out of a set of 6486

Marching Squares in Rust+WebAssembly

Marching Squares in Rust+WebAssembly

After previous forays into creating fancy backgrounds using JavaScript, I've been playing with an implementation of one of my favourite computer graphics algorithms in Rust. It seems that my second, more efficient implementation is a lot faster than the old JavaScript code (I didn't benchmark them

Cross-compiling Rust Code using GitLab CI

Cross-compiling Rust Code using GitLab CI

I've been excited to learn the Rust language for two years now since it compiles the performance properties of statically-compiled languages with modern language ergonomics (and allows you to parallelize things you normally wouldn't dare to thanks to its safety model). Another nice, less highlighted aspect

A bot that learns how you play rock-paper-scissors

A bot that learns how you play rock-paper-scissors

As a small project, I wrote a bot for learning player patterns when playing rock-paper-scissors using a first-order Markov chain. This is definitely not the first time someone has had this idea, but I still thought I would give it a go. My implementation simply models a combination of computer

Programming R like it's JavaScript / Python

Programming R like it's JavaScript / Python

R is the king of statistics languages for a good reason: There are hundreds of packages on CRAN for all sorts of analyses and the language is fluent for processing data in a variety of ways, especially when taking advantage of the hadleyverse packages. In my opinion, dplyr is the