An overview of what makes modern CSS so awesome.

This web app displays notes and slides in separate windows,
keeping both synchronised.
It accepts simple, double-width, or double-height PDF presentations:

My take on what could be a project template for Django advanced usage, with modern tooling (for Python and UI dependencies, as well as configuration/environment management), but not too opinionated.

Security testing starts with understanding vulnerabilities. The CVE website lists known software flaws. The OWASP Top Ten highlights common weaknesses. With this knowledge, we can improve our Go development. This article shows how to put in place robust practices. They are to: fuzz inputs, verify dependencies, and use static analysis tools (SAST).

I’ve used a lot of tools over the years, which means I’ve seen a lot of tools hit a plateau. That’s not always a problem; sometimes …

plainweb is a framework using HTMX, SQLite and TypeScript for less complexity and more joy.

The expression problem describes how most types can easily be extended with new ways to produce the type or new ways to consume the type, but not both. When abstract syntax trees are defined as an algebraic data type, for example, they can easily be extended with new consumers, such as print or eval, but adding a new constructor requires the modification of all existing pattern matches. The expression problem is one way to elucidate the difference between functional or data-oriented programs (easily extendable by new consumers) and object-oriented programs (easily extendable by new producers). This difference between programs which are extensible by new producers or new consumers also exists for dependently typed programming, but with one core difference: Dependently-typed programming almost exclusively follows the functional programming model and not the object-oriented model, which leaves an interesting space in the programming language landscape unexplored. In this paper, we explore the field of dependently-typed object-oriented programming by deriving it from first principles using the principle of duality. That is, we do not extend an existing object-oriented formalism with dependent types in an ad-hoc fashion, but instead start from a familiar data-oriented language and derive its dual fragment by the systematic use of defunctionalization and refunctionalization. Our central contribution is a dependently typed calculus which contains two dual language fragments. We provide type- and semantics-preserving transformations between these two language fragments: defunctionalization and refunctionalization. We have implemented this language and these transformations and use this implementation to explain the various ways in which constructions in dependently typed programming can be explained as special instances of the phenomenon of duality.

Most programming language ecosystems provide assert functions in their testing libraries but not Go's. Go's standard testing package follows a more direct and to-the-point approach.

Between our ESP32 prokaryotic organisms and our 24/7 Internet-enabled megafauna servers, there exists a vast and loosely-defined ecosystem of things the B2B world likes to call computer appliances. Picture a bespoke Pi 4 packaged up neatly with some Python scripts, a little fancy plastic embossing, and maybe a well-guarded id_ed25519.pub in case you end up in hot water during the (long - very long, stable cash flow for generations long) maintenance contract, and you’re in the ballpark.

Sales pitches are the only place where “self-serve dashboards" work. In the real world, it's a different story.

Why "business" people don't use metabase/power-bi.

From Erlang, to Elixir and now, GLEAM!?