Raymond Hettinger, Keynote on Concurrency, PyBay 2017

What Hacker News said

Strong rec scrollaway · 2018-07 · on “Ask HN: What talks or videos do you suggest to watch on a long flight?”

I've started watching Raymond Hettinger's talks lately. He's a core dev on Python. I love them, the guy is charismatic, very smart and his Python knowledge constantly impresses me. [LINK] My favourite: [this video]

Strong rec culebron21 · 2023-07 · on “How to use a Python multiprocessing module”

I've just left the question open, but the best learning material for me on this was this lecture. Other points down the list, I had to figure out just by trial and error. Raymond Hettinger, Keynote on Concurrency, PyBay 2017 [this video]

Recommends xkgt · 2019-05 · on “Has the Python GIL Been Slain? Subinterpreters in Python 3.8”

It is because only one thread at a time holds the lock in order to avoid race conditions. The keynote[1] by Raymond Hettinger from PyBay '17 will be a great place to start if you are new to this. [1] [this video]

Recommends fastball · 2021-09 · on “The GIL and its effects on Python multithreading”

For anyone looking for something on the same topic but a little bit lighter / more practical, I really enjoyed this talk[1] by Raymond Hettinger at PyBay 2017, where he discussed the GIL as well. [1] [this video]

Cites devxpy · 2018-06 · on “Why Threads Are a Bad Idea (1995) [pdf]”

Threads are not hard. In fact, threads are extremely easy to implement. However, real Threading code is just incredibly difficult to reason, just by looking at it. This makes it easy for you to introduce race conditions without even knowing that there is one! There is also the fact that locks don't lock anything! They are just a flag, that a any code may choose to ignore. They are a not an enforcing tool, just a cooperative one. (More here: [this video] ) P.S. I created a library, that makes it easier to write safer multiprocessing code [LINK]

Cites dangom · 2018-08 · on “JupyterCon: I don't like Notebooks [slides]”

Notebooks may be suitable for scratching things, but not much else. The problems noted by the OP are very serious, specially in the scientific world, where many do not have proper software engineering skills. The real issue is that newcomers do not know better, and so they don't realize the damage they're inflicting upon themselves and others before it's too late (irreproducible code, hidden states, dep. management, etc). Even the fast.ai library, which is a wonder, has broken notebooks. For those who try to follow the course at home, trying to run the notebooks is frustrating, as things are out of order and so errors pop up all the time. Jeremy is a wonderful teacher, but compare following

Cites targafarian · 2021-02 · on “Python Concurrency: The Tricky Bits”

To say concurrency is broken in Python because of the GIL seems to be reiterated adage without actual wisdom behind it.[1] Are you writing an IO-bound task? Then asyncio[2] (even if just viewed as an interface: e.g., you can make it even more performant by using uvloop[3]) is a great way to achieve performant concurrency. As Raymond Hettinger likes to point out, even if you throw away the GIL, you will have to implement locks on shared resources (unless you're writing embarrassingly parallel codes--in which case either you can invoke them separately or use the multiprocessing module to great effect, or see how I do it easily below), and by the time you get all the locks implemented in your G