The query_one() method throughout the Textual documentation allows users to retrieve a single widget that matches a CSS selector or a widget type. You can pass in up to two parameters to query_one(), which are the CSS selector and the widget type, or both at the same time.
Every iOS app I've shipped over the last nine years started the same way: a Rails developer with a great web app, users who want it in the App Store, and weeks spent on Xcode, signing certificates, and Swift boilerplate that has nothing to do with the actual product.
Which Algorithm Is This? If you step back, this maps almost perfectly to the Top K Frequent Elements problem.We usually solve it for integers in a list. Here, the "elements" are audience profiles age and body-type combinations. First, define what an audience profile looks like: case class Profile(age: Int, height: Int, weight: Int) What we want is a function like this:
React tutorial: Get started with the React libraryDespite the endless churn of new frameworks, React remains the quintessential reactive engine. This updated guide walks you through the fundamentals of React development, including a This is Spinal Tap variant on the canonical counter application. Sometimes, your components just need to go to 11.
But for-loops do something subtle: they ask us to think about how work is performed rather than what the work represents. Before we can express a business rule, we must decide: how to iterate, where to accumulate results, when to branch, which state to mutate, and how the structure should evolve over time. All of that comes before we say anything meaningful about the domain.
Anthropic has launched Claude Sonnet 4.6, an update to the company's hybrid reasoning model that brings improvements in coding consistency and instruction following, Anthropic said. Introduced February 17, Claude Sonnet 4.6 is a full upgrade of the model's skills across coding, computer use, long-context reasoning, agent planning, design, and knowledge work, according to Anthropic. the model also features a 1M token context window in beta.
If there's one universal experience with AI-powered code development tools, it's how they feel like magic until they don't. One moment, you're watching an AI agent slurp up your codebase and deliver a remarkably sharp analysis of its architecture and design choices. And the next, it's spamming the console with "CoreCoreCoreCore" until the scroll-back buffer fills up and you've run out of tokens.
Kacper Borucki blogged about parameterizing exception testing, and linked to pytest docs and a StackOverflow answer with similar approaches. The common way to test exceptions is to use pytest.raises as a context manager, and have separate tests for the cases that succeed and those that fail. Instead, this approach lets you unify them. I tweaked it to this, which I think reads nicely: One parameterized test that covers both good and bad outcomes. Nice.
One of my oldest open-source projects - Bob - has celebrated 15 a couple of months ago. Bob is a suite of implementations of the Scheme programming language in Python, including an interpreter, a compiler and a VM. Back then I was doing some hacking on CPython internals and was very curious about how CPython-like bytecode VMs work; Bob was an experiment to find out, by implementing one from scratch for R5RS Scheme.
