24K views · Dec 4, 2019 · 1:10:00 · 2 HN recommenders · 3 mentions · discussed 2020–2026
Raymond Hettinger's PyBay 2019 talk on the mental strategies he uses when programming in Python, such as chunking, solving a simpler related problem, and repeating tasks manually until patterns emerge. This version is re-synced with the slides.
Why Hacker News points people here: HN recommends it as an entertaining talk on how working memory shapes code and how to reduce cognitive load.
“Raymond Hettinger gave an entertaining talk [0] on a related topic.”HN comment, 2022
“there is a sync fixed version of the talk”
Synced version of Hettinger's talk, who teaches simply.
Raymond Hettinger is such a treasure! He keeps things simple and in the process you actually learn. I tend to overload the registers when teaching and students do not learn as much. All teachers know the feeling when students eyes glaze over, something that is so much harder to detect in the age of Zoom and Teams. PS this video there is a sync fixed version of the talk
“Raymond Hettinger gave an entertaining talk [0] on a related topic.”
How working memory limits shape code and reduce cognitive load.
Raymond Hettinger gave an entertaining talk [0] on a related topic. He taled about how the working memory limits are reflected in code, and how we can reduce the necessary cognitive load of understanding a piece of code. [0] this video
“Raymond Hettinger explains the philosophy well while discussing the `random` standard library module”
Hettinger explains design philosophy of the random module.
> It's a bit cleaner. That's pretty much the reason why. Raymond Hettinger explains the philosophy well while discussing the `random` standard library module: this video I feel like much of this has been forgotten of late, though. From what I've seen, i's really quite hard to get anything added to the standard library unless you're a core dev who's sufficiently well liked among other core devs, in which case you can pretty much just do it. Everyone else will (understandably) be put through a PhD thesis defense, then asked to try the idea out as a PyPI package first (and somehow also popularize the package), and then if it somehow catches on that way, get declined anyway because it's easy for everyone to just get it from PyPI (see e.g. Requests). I personally was directed to PyPI once when I was proposing new methods for the builtin `str` . Where the entire point was not to have to import or instantiate anything.
