A while ago I decided to learn a new programming language. I don’t exactly remember why but I felt like I wanted to. There were two candidates I was interested in, Rust and Julia. A colleague of mine really loves Julia and I’ve read a bit about it so I was interested enough to give it a try. Also, it is heavily geared towards scientists and scientific computing including data science so it seemed like a natural thing for me to try. ...
I’m currently experiencing the pleasure of collaborating on an open source project with someone else on GitHub and I love doing it. There was an issue with runtime performance and we looked into it, discussed ideas and coded up several prototypic solutions (I admit mine were rather dirty). At one point I reviewed someone else’s pull request and wanted to add something to it. Sure, I can use the online editing features of GitHub but that doesn’t really tie in well with my code-writing workflow, not to mention that all the autocompletion, linting and inline compiler errors won’t be present. So I looked for a way to push a commit to someone else’s pull request that I could prepare locally. I searched and found a good solution which I’m gonna write up here as reference for future me. ...
I’ve recently realized something. My use of the Linux operating system and all it offers has been evolving in something of a wave-like pattern. When I started out, the first thing I tried was Linux Mint which is something a former Windows user might do as it works in a fairly familiar way. I quickly realized that I wanted to dive deeper and do more things than what Mint let me do easily. In hindsight that’s probably in large part due to me not knowing much about what I was doing but I do remember that I felt constricted and started distrohopping. ...
Whenever you start a project in Python you probably want to do it in a fresh environment so as not to have your dependencies clash with those of other projects, prevent version mismatch or other unexpected breakage. The way to do this is by using virtual environments. As far as I know there are several ways to do this in Python (as always…) but the most prevalent, it seems to me, is using the builtin venv module. ...
A tale as old as time: you configure and tweak your personal machine that you use for work, coding, fun and games or whatever and at some point you wonder how you might preserve all those tweaks. Either, you want to back them up (which is always sensible) or you want to transfer to a new machine or want to show them to other people online so they can just download your setup and get going immediately. ...