It’s not, actually, any more than any other language. That was Guido’s original plan, but show a page of modern Python code to someone who’s never seen it before and they’ll run screaming. There is a minimal subset where you can say it reads like pseudocode, but that’s a very limited subset, and, like AppleScript, you have to have a fair amount of knowledge to be able to write it fluently.
I am more and more convinced that type checked Python is not always the best idea. The people who are the most virulently pro type checking in Python are not data science folks.
Python's type ecosystem's support for proper type checked data science libraries is abysmal (`nptyping` is pretty much the most feature complete, and it too is far from complete), and has tons of weird bugs.
The Array API standard (https://data-apis.org/array-api/latest/purpose_and_scope.htm...) is a step in the right direction, but until that work is close to some sort of beta version, data science folks will have tons of type errors in their code, in spite of trying their best.
Python absolutely has async/await/promises, and it's actually quite a lot worse than JavaScript in this regard because Python _also_ has synchronous APIs and _no_ tooling whatsoever to make sure you don't call a sync API in an async function thereby blocking your event loop (which, if your application is a networked service with any amount of traffic at all, will typically result in a cascading failure in production). I'm no great fan of JavaScript, and I've written _wayyyyy_ more Python than JS, but async/await/promises is exactly the wrong example to make the case that Python is better.
Structured concurrency with Exception groups make it untouchable for JS. If JS implements structure concurrency like Python, Java, Kotlin, then maybe it can be viable.
