Talk Python To Me

When LLMs write code to accomplish a task, that code has to actually run somewhere. And right now, the options aren't great. Spin up a sandboxed container and you're paying a full second of cold start overhead plus the complexity of another service. Let the LLM loose on your actual machine and... well, you'd better be watching.



On this episode, I sit down with Samuel Colvin, creator of Pydantic, now at 10 billion downloads, to explore Monty, a Python interpreter written from scratch in Rust, purpose-built to run LLM-generated code. It starts in microseconds, is completely sandboxed by design, and can even serialize its entire state to a database and resume later. We dig into why this deliberately limited interpreter might be exactly what the AI agent era needs.

Episode sponsors

Talk Python Courses

Python in Production

Links from the show

Guest

Samuel Colvin: github.com

CPython: github.com

IronPython: ironpython.net

Jython: www.jython.org

Pyodide: pyodide.com

monty: github.com

Pydantic AI: pydantic.dev

Python AI conference: pyai.events

bashkit: github.com

just-bash: github.com

Narwhals: narwhals-dev.github.io

Polars: pola.rs

Strands Agents: aws.amazon.com

Subscribe Running Pydantic’s Monty Rust sandboxed Python subset in WebAssembly: simonwillison.net

Rust Python: github.com

Valgrind: valgrind.org

Cod Speed: codspeed.io

Watch this episode on YouTube: youtube.com

Episode #541 deep-dive: talkpython.fm/541

Episode transcripts: talkpython.fm

Theme Song: Developer Rap

🥁 Served in a Flask 🎸: talkpython.fm/flasksong

---== Don't be a stranger ==---

YouTube: youtube.com/@talkpython

Bluesky: @talkpython.fm

Mastodon: @[email protected]

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @[email protected]

Michael on X.com: @mkennedy

Monorepos -- you've heard the talks, you've read the blog posts, maybe you've seen a few tantalizing glimpses into how Google or Meta organize their massive codebases. But it's often in the abstract and behind closed doors. What if you could crack open a real, production monorepo, one with over a million lines of Python and over 100 of sub-packages, and actually see how it's built, step by step, using modern tools and standards? That's exactly what Apache Airflow gives us.



On this episode, I sit down with Jarek Potiuk and Amogh Desai, two of Airflow's top contributors, to go inside one of the largest open-source Python monorepos in the world and learn how they manage it with uv, pyproject.toml, and the latest packaging standards, so you can apply those same patterns to your own projects.

Episode sponsors

Agentic AI Course

Python in Production

Talk Python Courses

Links from the show

Guests

Amogh Desai: github.com

Jarek's GitHub: github.com

definition of a monorepo: monorepo.tools

airflow: airflow.apache.org

Activity: github.com

OpenAI: airflowsummit.org

Part 1. Pains of big modular Python projects: medium.com

Part 2. Modern Python packaging standards and tools for monorepos: medium.com

Part 3. Monorepo on steroids - modular prek hooks: medium.com

Part 4. Shared “static” libraries in Airflow monorepo: medium.com

PEP-440: peps.python.org

PEP-517: peps.python.org

PEP-518: peps.python.org

PEP-566: peps.python.org

PEP-561: peps.python.org

PEP-660: peps.python.org

PEP-621: peps.python.org

PEP-685: peps.python.org

PEP-723: peps.python.org

PEP-735: peps.python.org

uv: docs.astral.sh

uv workspaces: blobs.talkpython.fm

prek.j178.dev: prek.j178.dev

your presentation at FOSDEM26: fosdem.org

Tallyman: github.com

Watch this episode on YouTube: youtube.com

Episode #540 deep-dive: talkpython.fm/540

Episode transcripts: talkpython.fm

Theme Song: Developer Rap

🥁 Served in a Flask 🎸: talkpython.fm/flasksong

---== Don't be a stranger ==---

YouTube: youtube.com/@talkpython

Bluesky: @talkpython.fm

Mastodon: @[email protected]

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @[email protected]

Michael on X.com: @mkennedy

You're adding type hints to your Python code, your editor is happy, autocomplete is working great. But then you switch tools and suddenly there are red squiggles everywhere. Who decides what a float annotation actually means? Or whether passing None where an int is expected should be an error? It turns out there's a five-person council dedicated to exactly these questions -- and two brand-new Rust-based type checkers are raising the bar. On this episode, I sit down with three members of the Python Typing Council -- Jelle Zijlstra, Rebecca Chen, and Carl Meyer -- to learn how the type system is governed, where the spec and the type checkers agree and disagree, and get the council's official advice on how much typing is just enough.

Episode sponsors

Sentry Error Monitoring, Code talkpython26

Agentic AI Course

Talk Python Courses

Links from the show

Guests

Carl Meyer: github.com

Jelle Zijlstra: jellezijlstra.github.io

Rebecca Chen: github.com

Typing Council: github.com

typing.python.org: typing.python.org

details here: github.com

ty: docs.astral.sh

pyrefly: pyrefly.org

conformance test suite project: github.com

typeshed: github.com

Stub files: mypy.readthedocs.io

Pydantic: pydantic.dev

Beartype: github.com

TOAD AI: github.com

PEP 747 – Annotating Type Forms: peps.python.org

PEP 724 – Stricter Type Guards: peps.python.org

Python Typing Repo (PRs and Issues): github.com

Watch this episode on YouTube: youtube.com

Episode #539 deep-dive: talkpython.fm/539

Episode transcripts: talkpython.fm

Theme Song: Developer Rap

🥁 Served in a Flask 🎸: talkpython.fm/flasksong

---== Don't be a stranger ==---

YouTube: youtube.com/@talkpython

Bluesky: @talkpython.fm

Mastodon: @[email protected]

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @[email protected]

Michael on X.com: @mkennedy

Digital humanities sounds niche, until you realize it can mean a searchable archive of U.S. amendment proposals, Irish folklore, or pigment science in ancient art. Today I’m talking with David Flood from Harvard’s DARTH team about an unglamorous problem: What happens when the grant ends but the website can’t. His answer, static sites, client-side search, and sneaky Python. Let’s dive in.

Episode sponsors

Sentry Error Monitoring, Code talkpython26

Command Book

Talk Python Courses

Links from the show

Guest

David Flood: davidaflood.com

DARTH: digitalhumanities.fas.harvard.edu

Amendments Project: digitalhumanities.fas.harvard.edu

Fionn Folklore Database: fionnfolklore.org

Mapping Color in History: iiif.harvard.edu

Apatosaurus: apatosaurus.io

Criticus: github.com

github.com/palewire/django-bakery: github.com

sigsim.acm.org/conf/pads/2026/blog/artifact-evaluation: sigsim.acm.org

Hugo: gohugo.io

Water Stories: waterstories.fas.harvard.edu

Tsumeb Mine Notebook: tmn.fas.harvard.edu

Dharma and Punya: dharmapunya2019.org

Pagefind library: pagefind.app

django_webassembly: github.com

Astro Static Site Generator: astro.build

PageFind Python Lib: pypi.org

Frozen-Flask: frozen-flask.readthedocs.io

Watch this episode on YouTube: youtube.com

Episode #538 deep-dive: talkpython.fm/538

Episode transcripts: talkpython.fm

Theme Song: Developer Rap

🥁 Served in a Flask 🎸: talkpython.fm/flasksong

---== Don't be a stranger ==---

YouTube: youtube.com/@talkpython

Bluesky: @talkpython.fm

Mastodon: @[email protected]

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @[email protected]

Michael on X.com: @mkennedy

You love building web apps with Python, and HTMX got you excited about the hypermedia approach -- let the server drive the HTML, skip the JavaScript build step, keep things simple. But then you hit that last 10%: You need Alpine.js for interactivity, your state gets out of sync, and suddenly you're juggling two unrelated libraries that weren't designed to work together.



What if there was a single 11-kilobyte framework that gave you everything HTMX and Alpine do, and more, with real-time updates, multiplayer collaboration out of the box, and performance so fast you're actually bottlenecked by the monitor's refresh rate? That's Datastar.



On this episode, I sit down with its creator Delaney Gillilan, core maintainer Ben Croker, and Datastar convert Chris May to explore how this backend-driven, server-sent-events-first framework is changing the way full-stack developers think about the modern web.

Episode sponsors

Sentry Error Monitoring, Code talkpython26

Command Book

Talk Python Courses

Links from the show

Guests

Delaney Gillilan: linkedin.com

Ben Croker: x.com

Chris May: everydaysuperpowers.dev

Datastar: data-star.dev

HTMX: htmx.org

AlpineJS: alpinejs.dev

Core Attribute Tour: data-star.dev

data-star.dev/examples: data-star.dev

github.com/starfederation/datastar-python: github.com

VSCode: marketplace.visualstudio.com

OpenVSX: open-vsx.org

PyCharm/Intellij plugin: plugins.jetbrains.com

data-star.dev/datastar_pro: data-star.dev

gg: discord.gg

HTML-ivating your Django web app's experience with HTMX, AlpineJS, and streaming HTML - Chris May: www.youtube.com

Senior Engineer tries Vibe Coding: www.youtube.com

1 Billion Checkboxes: checkboxes.andersmurphy.com

Game of life example: example.andersmurphy.com

Watch this episode on YouTube: youtube.com

Episode #537 deep-dive: talkpython.fm/537

Episode transcripts: talkpython.fm

Theme Song: Developer Rap

🥁 Served in a Flask 🎸: talkpython.fm/flasksong

---== Don't be a stranger ==---

YouTube: youtube.com/@talkpython

Bluesky: @talkpython.fm

Mastodon: @[email protected]

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @[email protected]

Michael on X.com: @mkennedy