Tag: code

The algorithms

Honing your skills on CodeWars or HackerRank is definitely a good idea. I’ve myself spent months on the former and some time on the latter, and right there is a display of my issue with them: I lose interest. At first it’s really nice to tackle a bunch of “interesting” problems and feel successful, but as the difficulty of the problems goes up, it soon turns into “how do I get around the shortcomings of the language I use?”

That’s naturally something worth considering, but it just feels so weird when I have to overcome performance tests aimed at C in Ruby (or Clojure). It’s doable (most of the time), but it’s a whole different kind of measure. I recall a problem for which solutions in C were mostly pretty naive loops while something similar in Ruby would fail even the first few load tests.

Counting the milliseconds

I’ve been building a Netty-based web server in Clojure. While I haven’t had the strength to do much with it these past few months because I prioritized the climbing season, now that Hacktoberfest is incoming I’m planning to go pedal to the metal with it (and with my git GUI work-in-progress).

I’m building iny (named after a fox from Fekete Istvan’s Vuk) with the clear goal to replace Aleph. While I’m a huge fan of Aleph and the libraries around it (like Manifold) it’s no longer maintained, which is simply not acceptable when we’re now looking at http/3 coming out sooner than later (support is already in browsers after all).

Going green

There is kind of a status to having your GitHub contributions chart covered in green. For those unfamiliar, it’s a calendar-like chart that shows how active you are on GitHub any given day. It’s assumed that the greener the better. I’m not so sure anymore.

From the start of May to the end of July, I tried filling it up. Do something every day. My conclusion is that this is a typical case of Goodhart’s law. Basically as soon as a certain metric (in this case turning that chart green) becomes a goal in itself, it ceases to be a meaningful metric anymore.

Iced to Electron

I got really frustrated by GitKraken. I’ve been using it for years now both for work and for hobby projects without much to complain about really. Then again I’m not a heavy git user: mostly I just commit and push, only occasionally squashing or cherry picking. I don’t even remember when was the last time I needed a rebase, but it wasn’t yesterday.

However recently GitKraken started having these weird problems with my work repositories. These can get pretty big (by my standards) with tons of branches getting pushed to in parallel (and in the early days some very large blobs got checked in too). Because the branches move really quick it’s important that I can keep my own up to date by merging the head branch back.

GitOps and Kubernetes persistence

A while back I wrote about bootstrapping a Kubernetes cluster. I’ve been refining the setup so that it requires as little manual kubectl‘ing as possible. I still use ArgoCD to get everything rolling, and there is one bit that kept going red: persistent volumes.

可変個! 可変個! そして手動gensym!




Paul Graham: Revenge of the nerds


After last year, I once again decided to take part in the Hacktoberfest fun. I have plenty of repositories lying around (sadly much less well maintained by yours truly than preferable). Of course this also means that I can gather the necessary contributions from updating dependencies in my own repositories, but I’d prefer to instead contribute to those dependencies.


Having played around with the managed Kubernetes offerings of various cloud players (DO, AWS, GCP), I was wondering if it was possible to do this cheap. My site doesn’t have much traffic or anything complicated really, so running it off a $5 DO droplet is reasonable. Sadly managed Kubernetes offerings won’t come out so cheap. (Sure I could leech off the starting $300 GCP credit for a year then keep hopping accounts, but…)

Then I read about k3s. The people behind Rancher made it as a lightweight (but functionally complete) Kubernetes distro. Lightweight, they say… Just how light? (Imagine a weird maniac light in my eyes here.) Could I run it on a $5 droplet?


I think many people of my profession got recommended a certain article by Medium in their weekly digest. The launch-introduction post by Garden got my attention too. I’ve been trying to figure out how to deal with developing on Kubernetes, so every drop of information in that regard is much welcome.


The other day I was thinking about Rich Hickey’s keynote at last year’s Conj. He goes into how the literal maps (or hashes or hashmaps or however a language prefers to call them) are really functions too. A function in maths is a mapping between sets and that’s what maps are.

Then that makes functions we normally write are just like that too, except the mappings are more abstract and defined through code. Because the mappings are so complex and indirect, we write tests to check (automated) that the mapping we defined through code is correct.

Obviously defining the exact mappings for every possible combination of the input set(s) is not feasible (that’d be a map, the end). But if “all” is not possible then how much is? What exactly is the absolute minimum amount of test( case)s that’s useful?