Programming Leftovers

posted by Roy Schestowitz on Sep 04, 2026

• Hackaday ☛ Hackaday Europe 2026: Fluid Kernels And Optimizing C++ For MCUs

  Federico Terraneo came to Hackaday Europe to discuss this very topic. He talks about kernel architecture, real-time operating systems, and how to best use C++ in the world of microcontrollers.

• Martin Chang ☛ Least Privilege, Most Shenanigans - Martin's website/blog thingy

  I have been growing more and more careful about security as I develop new services for the Geminispace. I mostly write in C++, which is not known to be the safest language around. Plus, AI agents can now be ultra-persistent about pwning your service. This is not good... but I refuse to use Rust because I am yet to understand it well enough to know its best practices and pitfalls. So, in the meantime, I looked into the tricks OpenBSD uses to make life literal hell for attackers, even when a bug exists. Make finding a bug the 1st step in the attacker's many problems to come, instead of the be-all and end-all of your security. If tokens are cheap and attacks are therefore cheap, we can make attackers burn them like power plants and get nothing in return: [...]

• PulkoMandy ☛ A bicycle for the mind

  This article has been updated with extra links to relevant sources.

• Jon Chiappetta: Elliptic Curve Memory Refresher

• Jon Chiappetta: Finally got multi-queue batch-io linux kernel tun interface in C!

  Thanks to Google’s Hey Hi (AI) code snippets, I was able to finally implement multiple threads all reading from a singular tun interface as well as each thread performing larger multiple batch reads/writes in one singular syscall (up to 65536 bytes per call)!

• Kore Nordmann ☛ How to Guarantee You Never Ship

  In a run of posts I have argued against a handful of things one at a time: splitting code across many repositories, long-lived feature branches, reaching for microservices to model separation, dedicated quality assurance, one fixed test coverage target for every change, and pull-request review as your quality gate. Each of those is a problem on its own. This post is about adopting all of them at once, which is more common than it should be, because each arrives wearing the badge of a best practice.

  So let me write the inverse of everything else in this series. If your goal were to build an organisation that never delivers anything, while every individual decision still looked responsible in the meeting where it was made, here is how you would do it.

• Perl / Raku

  • Ruben Schade ☛ Randal Schwartz on Perl and timestamps

    From chapter 13 of Learning Perl:

    There’s no “reasonableness” value for the timestamps: you can make a file look arbitrarily old or as though it were modified at some time in the distant future (useful if you are writing science fiction stories).

  • Perl ☛ AmberDB - An Embedded NoSQL Database Engine for Perl

    AmberDB is an embedded, schema-driven NoSQL database engine for Perl, designed for applications that need structured records, fast indexed queries, full-text search, transactions, and a simple deployment model.

    It is built on top of Berkeley DB through DB_File, but AmberDB provides a much higher-level database API rather than exposing the underlying key-value store directly.

• Python

  • Daniel Lemire ☛ Python sets and dictionaries can have quadratic-time performance

    In Python, the dict data structure is the conventional key-value structure. E.g., you might store a list of names as keys and have their phone numbers as values. Valentin Ignatev wrote this amusing post on X: [...]

• R / R-Script

  • Dirk Eddelbuettel ☛ Dirk Eddelbuettel: RcppExamples 0.1.11 on CRAN: Very Minor Maintenance

    A new version 0.1.11 of the RcppExamples been built for r2u.

    fairly) simple examples, more interesting, compelling (and generally longer) examples are at the Rcpp Gallery.

  • Ben Johnston ☛ R For SEO Part 10: SEO Reporting With Google Sheets & OpenRouter

    Welcome back, and we’re finally at the end of my R for SEO series, at least for now. We’ve gone through quite a lot over the course of this series, everything from the basics, to where we are today: using everything we’ve learned to build a shiny SEO report, using Google Sheets and OpenRouter in R.

    If you’re new, or you’ve fallen out along the way, here’s a run-down of everything we’ve covered in the series.

  • [Old] Ben Johnston ☛ R for SEO Part 9: Web Scraping With R & Rvest

    Today, we’re going to discuss the rvest package, look at the different scraping methods available, pull data from multiple pages and then look at how we can do so without bringing our target sites down. This is going to be fairly important for our final piece, so it’s worth paying attention today.

  • [Old] Ben Johnston ☛ R For SEO Part 8: Apply Methods in R, Lapply, Sapply, Mapply

    Applys are a more “R-centric” way of running functions across a range of data. They’re not entirely dissimilar to loops, but tend to be a more efficient way to write them and they do come with additional functionality which can be very useful in a number of situations.

    You’ll have seen some of them being used already through this series, particularly when we talked about using APIs in R. So let’s take a look at the components of the apply family and what they can be used for.

  • [Old] Ben Johnston ☛ R For SEO Part 7: Loops, For Loops While Loops In R

    If you’ve followed along so far, or you’ve tried some experimentation of your own, you’ve probably encountered loops and applys along the way. I know early on in my R journey, it very much seemed like pot luck as to which apply I should use, or whether a loop was easier, so hopefully today’s piece will start to clear that up for you a little.

    I know that most programming courses cover these elements earlier, but for me, it really didn’t click until I’d learned more about the other areas we’ve covered in this series, so that’s why I’ve placed it here.

  • [Old] Ben Johnston ☛ R For SEO Part 6: Using APIs In R

    Wow, we’re at part 6 of my R for SEO series. Welcome back. I really hope you’re finding this useful, and by now have started to use R in your work. Today we’re going to look at one of my favourite topics: using APIs in R.

    There are, obviously, millions of APIs available, so today I will just look at a couple of my favourite SEO-specific ones which will give you a basis for using the different types. We’re going to cover SERPAPI, SEMRush and SE Ranking, how to get data out of them, how to authenticate with them and how to work with the data they give you.

    Now that’s out the way, let’s get started.

  • [Old] Ben Johnston ☛ R For SEO Part 4: Functions

    Today we’re going to start making it feel like we’re programming – we’re going to be writing our own R functions, looking at the anatomy of a function and creating a few of the most common ones that I use in my SEO work.

    I know, again, that this piece is super late. The last eighteen months has been a lot, but hopefully the next few months will give me more time.

  • [Old] Ben Johnston ☛ R For SEO Part 3: Data Visualisation With GGPlot2 & Wordcloud

    In today’s piece, we’re going to use the GGPlot2 package and some Google Analytics and Search Console data to make basic bar charts, line graphs, a combo plot and finally a really cool wordcloud with our search queries.

  • [Old] Ben Johnston ☛ R For SEO P2: Packages, Google Analytics & Search Console With R

    Hello and welcome to part two of my series on using the R programming language for SEO. Hopefully you enjoyed part one and are raring to go with today’s piece. Today, we’re going to be looking at R packages and as an example, we’re going to be using packages to directly pull in data from Google Analytics and Google Search Console. That’s right, no more downloading CSV exports and importing them.

  • [Old] Ben Johnston ☛ R For SEO Part 1: The Basics, Installation & Exploring Data

    The R programming language has lots of benefits for SEOs, but it just doesn’t get as much love in the space as Python. I get it. The barrier to entry is a little higher and there are some things that you can do with Python or other languages that R is just not built for, but when it comes to analysis of chunky datasets or common SEO analytical functions, R can do it just as well as any other language – better in some cases.

    R was the first programming language I learned “properly” after self-teaching a few bits of different ones here and there and, although I’m moving more towards focusing on Python and Julia these days for some of the work I’m doing, R will always hold a special place in my heart. With that in mind, I wanted to share a series of posts where I’ll show you just how you can use R for SEO.

• Java/Golang

  • VictoriaMetrics ☛ How Swiss Tables Work in Go’s Built-in Map

    We have already written about Go maps and their old runtime implementation in Go Maps Explained: How Key-Value Pairs Are Actually Stored. Go 1.24 replaced that implementation with a design based on Swiss Tables, so it is time for an update.

    You do not need to go back and read the old article. We will review how maps behave and the concepts needed here before moving into the new runtime internals.

• Rust

  • Rust Blog ☛ The Rust Programming Language Blog: Announcing Rust 1.98.1

    The Rust team has published a new point release of Rust, 1.98.1. Rust is a programming language that is empowering everyone to build reliable and efficient software.