Have you heard that Python is not good for writing concurrent asynchronous code?

This is generally a misconception, but there is one class of parallel computing that Python

is not good at CPU-bound work running in the Python layer.

What's the main problem?

It's Python's Gill or global interpreter lock, of course.

Yet the fix for this restriction might have been hiding inside Python for 20 years, subinterpreters.

Join me to talk about PEP 554 with core developer Eric Snow.

This is Talk Python to Me, episode 225, recorded August 2nd, 2019.

Music Welcome to Talk Python to me, a weekly podcast on Python, the language, the libraries, the ecosystem, and the personalities.

This is your host, Michael Kennedy. Follow me on Twitter where I'm at

M. Kennedy. Keep up with the show and listen to past episodes at talk python.fm and follow the show

on Twitter via at Talk Python. This episode is supported by Linode and TopTal. Please check out what

they're offering during their segments. It really helps support the show. Eric, welcome to Talk

Python to me. Hi. How's it going? It's going really well. It's an honor to have helps support the show. Eric, welcome to talk Python to me.

Hi, how's it going? It's going really well. It's an honor to have you on the show.

We met up at Pye Cascades and talked a little bit, but this latest work you're doing to address concurrency in parallelism in Python is super interesting, so I'm looking forward to

you about that. Well, it's super interesting to me, too.

Yeah, I can imagine. I'm glad you're interested. This kind of stuff is, I don't know,

there's just something that draws me in, and I'm really, uh, enjoy exploring it. But before we do,

let's start with your story. How'd you get into programming on Python? Oh, boy, I had all sorts of ideas on what I wanted to do growing up, and computers was not really

one of them.

But then I ended up at school and somehow ended up, signed up for computer stuff, ended up

...