Guido van Rossum

writer

7 episodes on 6 shows, about 3 hours, since May 2015.

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Topics: Tech & AI.

Recent guest appearances

Show all 7 episodes
  • Episode 30: Live from EuroPython, an Interview with Guido van Rossum
    core.py

    This one is a short one. But it's also a big one. We'd invite you to listen to it, but you don't need to follow us. You don't need to follow anybody! You've got to think for yourselves! You're all individuals! ## Timestamps (00:00:00) INTRO (00:00:36) PART 1: GUIDO VAN ROSSUM (00:01:09) Monty Python reference only GvR understood (00:01:27) Math Olympiad anniversary (00:03:31) Silly hats (00:05:20) perchance (00:09:51) PR OF THE WEEK (not really) (00:11:04) The Grail Web Browser (00:14:31) Generational gaps (00:17:24) Changes in beliefs (00:21:43) Pablo Galindo Salgado was never right (00:23:11) Aesthetics in coding (00:29:16) Rietveld (00:34:14) VScode is the new Emacs (00:35:41) On recognition outside of tech (00:38:11) Taste in music (00:39:51) Cameo in a movie? (00:40:52) OUTRO

  • Rivers Cuomo (Weezer): Come Undone (Computer Programming with Guido Van Rossum)
    Sing for Science

    Rock icon Rivers Cuomo goes deep on coding talk with Python computer language creator and programming icon, Guido Van Rossum. We talk about the history of The Sweater Song, coding vs songwriting, the history of Python and much, much more!

  • Guest: Guido van Rossum
    Lexman Artificial

    Lexman and van Rossum discuss the relationship between Leibniz and poetastering.

  • Interview with Guido van Rossum
    Lexman Artificial

    Lexman interviews the creator of Python, Guido van Rossum. They discuss the drugget, quittors, granger and cingulum models.

  • Software at Scale 34 - Faster Python with Guido van Rossum
    Software at Scale

    Guido van Rossum is the creator of the Python programming language and a Distinguished Engineer at Microsoft. Apple Podcasts | Spotify | Google Podcasts We discuss Guido’s new work on making CPython faster ( PEP 659 ), Tiers of Python Interpreter Execution , and high impact, low hanging fruit performance improvements. Highlights (an edited summary) [00:21] What got you interested in working on Python performance? Guido: In some sense, it was probably a topic that was fairly comfortable to me because it means working with a core of Python, where I still feel I know my way around. When I started at Microsoft, I briefly looked at Azure but realized I never enjoyed that kind of work at Google or Dropbox. Then I looked at Machine Learning, but it would take a lot of time to do something interested with the non-Python, and even Python-related bits. [02:31] What was different about the set of Mark Shannon’s ideas on Python performance that convinced you to go after them? Guido: I liked how he was thinking about the problem. Most of the other approaches around Python performance like PyPy and Cinder are not suitable for all use cases since they aren’t backward compatible with extension modules. Mark has the perspective and experience of a CPython developer, as well as a viable approach that would maintain backward compatibility, which is the hardest problem to solve. The Python Bytecode interpreter is modified often across minor releases (for eg: 3.8 → 3.9) for various reasons like new opcodes, so modifying that is a relatively safe approach. Utsav: [09:45] Could you walk us through the idea of the tiers of execution of the Python Interpreter ? Guido: When you execute a program, you don't know if it's going to crash after running a fraction of a millisecond, or whether it's going to be a three-week-long computation. Because it could be the same code, just in the first case, it has a bug. And so, if it takes three weeks to run the program, maybe it would make sense to spend half an hour ahead of time optimizing all the code that's going to be run. But obviously, especially in dynamic languages like Python, where we do as much as we can without asking the user to tell us exactly how they need it done, you just want to start executing code as quickly as you can. So that if it's a small script, or a large program that happens to fail early, or just exits early for a good reason, you don't spend any time being distracted by optimizing all that code. So, what we try to do there is keep the bytecode compiler simple so that we get to execute the beginning of the code as soon as possible. If we see that certain functions are being executed many times over, then we call that a hot function, and some definition of “hot”. For some purposes, maybe it's a hot function if it gets called more than once, or more than twice, or more than 10 times. For other purposes, you want to be more conservative, and you ca

  • Python past, present, and future with Guido van Rossum
    Talk Python To Me

    See the full show notes for this episode on the website at talkpython.fm/100

  • Interview with Guido van Rossum
    podcast – Mostly Erlang

    Happy Thursday! Here’s an interview with Guido van Rossum, author of the Python programming language. Download Link: https://mostlyerlang.wordpress.com/wp-content/uploads/2015/05/interview-with-guido-van-rossum.mp3 https://mostlyerlang.wordpress.com/wp-content/uploads/2015/05/interview-with-guido-van-rossum.mp3

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Podcasts Guido van Rossum has appeared on

Guido van Rossum shows up most often on Lexman Artificial (2 episodes), with visits to core.py and Sing for Science.

Appearance timeline

Tracked guest appearances by Guido van Rossum, by year.

20152026

Frequently asked questions

What podcasts has Guido van Rossum been on?

Guido van Rossum has appeared on 7 recent podcast episodes across 6 shows, including Lexman Artificial, core.py, Sing for Science.

What is Guido van Rossum's latest podcast appearance?

The latest detected appearance is “Episode 30: Live from EuroPython, an Interview with Guido van Rossum” on core.py, published 28 Jul 2026.

How many hours of Guido van Rossum podcast interviews are there?

GuestVine has tracked about 3 hours of Guido van Rossum guest appearances across 7 episodes, going back to 7 May 2015.

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GuestVine tracks delivered guest appearances, excludes own-show episodes where possible, and links back to the original publisher audio. New appearances are added automatically as they are detected.

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