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.
When you learn on your own, you're responsible for: Choosing what to learn next Deciding what "good enough" looks like Knowing when you're ready to move on Evaluating whether your work reflects real-world expectations Most beginners don't struggle because they lack discipline. They struggle because they don't yet have the context to make good learning decisions.
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:
By comparing how AI models and humans map these words to numerical percentages, we uncovered significant gaps between humans and large language models. While the models do tend to agree with humans on extremes like 'impossible,' they diverge sharply on hedge words like 'maybe.' For example, a model might use the word 'likely' to represent an 80% probability, while a human reader assumes it means closer to 65%.
One thing I always do when I prompt a coding agent is to tell it to ask me any questions that it might have about what I've asked it to do. (I need to add this to my default system prompt...) And, holy mackerel, if it doesn't ask good questions. It almost always asks me things that I should have thought of myself.
Open-source AI coding tool OpenCode features a native terminal-based UI, multi-session support, and compatibility with over 75 models, including Claude, OpenAI, Gemini, and local models. In addition to its CLI tool, OpenCode is also available as a desktop app and and an IDE extension for VS Code, Cursor, and other tools. OpenCode allows developers to use their existing subscriptions to paid services such as ChatGPT Plus/Pro, GitHub Copilot. Additionally, it includes a set of free models that can be used locally through LM Studio.
