Programming Leftovers
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Keith Harrison ☛ Swift Testing Completion Handlers
I use a custom subclass of NSPersistentContainer when working with Core Data. My subclass performs some extra configuration when loading the store but otherwise works the same way. The loadPersistentStores method calls a completion handler for each store it loads: [...]
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Max Bernstein ☛ Representing type lattices compactly
Types, as a concept, name sets of objects—sets of instances. Some types (say, int8) have finite members. There are only ever 256 potential values for an 8-bit integer. Some times, (say, list) are infinite. Given enough storage, one could keep generating bigger and bigger instances. Since it’s not possible to store all elements of a set, we refer to types by a name.
This reduces precision. Maybe there is some bizarre case where you know that an object could be one of a thousand different possible lists, so giving up and saying “it’s a list” loses information. But it also saves a bunch of space and analysis time, because now we’re dealing with very small labels. Let’s start off by giving a couple built-in types names and calling it a day.
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Noë Flatreaud ☛ Linux reverse shell in x86 assembly
I wanted to test out some sockets in x86 assembly. So why not re-creating a reverse shell ?
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Michał Sapka ☛ Codeberg
I’ve been hosting my git in public for quite some now, but I will no more. The amount of traffic LLM scrapers do is annoying, to say the least. I’ve been playing whack-a-mole with them, and now the traffic is not significant, but still. I don’t want to do that!
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Rlang ☛ Word-Online: recreating Karpathy’s char-RNN (with supervised linear online learning of word embeddings) for text completion
In this post, I implement a simple word completion model, based on Karpathy’s char-RNN, but using supervised linear online learning of word embeddings. More precisely, I use the SGDClassifier from scikit-learn, which is a simple linear classifier that can be updated incrementally.
Keep in mind that this is an illustrative example, based on a few words and small vocabulary. There are many, many ways to improve the model, and many other configurations could be envisaged. So, feel free to experiment and extend this example. Nonetheless, the grammatical structure of the generated text (don’t generalize this result yet) is surprisingly good.
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Rlang ☛ (News from) Probabilistic Forecasting of univariate and multivariate Time Series using Quasi-Randomized Neural Networks (Ridge2) and Conformal Prediction
A blog post describing univariate and multivariate probabilistic forecasting of time series using Ridge2 and conformal prediction
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KDAB ☛ Model/View Drag and Drop in Qt - Part 2
In this follow-up to our drag-and-drop guide, we explore how to move items between views in Qt’s model/view framework. Learn how to set up both drag and drop sides, handle MIME data, and implement key model methods. Whether you're working with model/view separation or with item widgets, this post provides practical examples to help you customize UI interactions effectively.
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Josef Strzibny: Predownloading embedding models in Rails with Kamal
If you are building AI-powered applications in Ruby on Rails, you might have come across Informers or Transformers.rb gems for transformer inference. Here’s how to improve the production deployment of their models in Kamal setups.
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Perl / Raku
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Rakulang ☛ Rakudo Weekly 2025.10 Final CFP Week
The Call For Presentations for the Conference in Greenville, SC on June 27-29 2025 closes on 15 March. If you plan to do a presentation, make sure it is submitted before the deadline! Foundation News Saif Ahmed has posted an update to the Raku Ecosystem Grant Report.
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Python
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dwaves.de ☛ GNU/Linux basic python based mongodb performance testing benchmark
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LWN ☛ Python tail-call speedup based on LLVM regression
The Python project's recent switch to a tail-calling interpreter may not provide as large a speed advantage as initially thought. A blog post from Nelson Elhage gives the details. In short, switching to a tail-call-based interpreter accidentally works around an unfixed regression in LLVM 19. On other compilers, the performance benefit (while still present) is more moderate.
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Shell/Bash/Zsh/Ksh
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TecAdmin ☛ A Shell Script to Create Minikube K8s Cluster on Ubuntu
Hello friends! Today, we will learn how to put Minikube on your Ubuntu computer. Minikube is a tool that runs Kubernetes, a very popular thing for managing apps, on your own machine.
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Rust
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Niko Matsakis: Rust in 2025: Targeting foundational software
Rust turns 10 this year. It’s a good time to take a look at where we are and where I think we need to be going. This post is the first in a series I’m calling “Rust in 2025”. This first post describes my general vision for how Rust fits into the computing landscape. The remaining posts will outline major focus areas that I think are needed to make this vision come to pass. Oh, and fair warning, I’m expecting some controversy along the way—at least I hope so, since otherwise I’m just repeating things everyone knows.
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