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Michael Kennedy

Talk Python to Me is a weekly podcast hosted by developer and entrepreneur Michael Kennedy. We dive
 deep into the popular packages and software developers, data scientists, and incredible hobbyists doing
 amazing things with Python. If you're new to Python, you'll quickly learn the ins and outs of the community
 by hearing from the leaders. And if you've been Pythoning for years, you'll learn about your favorite
 packages and the hot new ones coming out of open source.

Talk Python To Me

The OWASP Top 10 just got a fresh update, and there are some big changes: supply chain attacks, exceptional condition handling, and more. Tanya Janca is back on Talk Python to walk us through every single one of them. And we're not just talking theory, we're going to turn Claude Code loose on a real open source project and see what it finds. Let's do it.

Episode sponsors

Temporal

Talk Python Courses

Links from the show
DevSec Station Podcast: www.devsecstation.com

SheHacksPurple Newsletter: newsletter.shehackspurple.ca

owasp.org: owasp.org

owasp.org/Top10/2025: owasp.org

from here: github.com

Kinto: github.com

A01:2025 - Broken Access Control: owasp.org

A02:2025 - SecuA02 Security Misconfiguration: owasp.org

ASP.NET: ASP.NET

A03:2025 - Software Supply Chain Failures: owasp.org

A04:2025 - Cryptographic Failures: owasp.org

A05:2025 - Injection: owasp.org

A06:2025 - Insecure Design: owasp.org

A07:2025 - Authentication Failures: owasp.org

A08:2025 - Software or Data Integrity Failures: owasp.org

A09:2025 - Security Logging and Alerting Failures: owasp.org

A10 Mishandling of Exceptional Conditions: owasp.org

https://github.com/KeygraphHQ/shannon: github.com

anthropic.com/news/mozilla-firefox-security: www.anthropic.com

generalpurpose.com/the-distillation/claude-mythos-what-it-means-for-your-business: www.generalpurpose.com

Python Example Concepts: blobs.talkpython.fm

Watch this episode on YouTube: youtube.com

Episode #545 deep-dive: talkpython.fm/545

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: @talkpython@fosstodon.org

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @mkennedy@fosstodon.org

Michael on X.com: @mkennedy

#545: OWASP Top 10 (2025 List) for Python Devs

When you pip install a package with compiled code, the wheel you get is built for CPU features from 2009. Want newer optimizations like AVX2? Your installer has no way to ask for them. GPU support? You're on your own configuring special index URLs. The result is fat binaries, nearly gigabyte-sized wheels, and install pages that read like puzzle books. A coalition from NVIDIA, Astral, and QuanSight has been working on Wheel Next: A set of PEPs that let packages declare what hardware they need and let installers like uv pick the right build automatically. Just uv pip install torch and it works. I sit down with Jonathan Dekhtiar from NVIDIA, Ralf Gommers from Quansight and the NumPy and SciPy teams, and Charlie Marsh, founder of Astral and creator of uv, to dig into all of it.

Episode sponsors

Sentry Error Monitoring, Code talkpython26

Temporal

Talk Python Courses

Links from the show
Guests

Charlie Marsh: github.com

Ralf Gommers: github.com

Jonathan Dekhtiar: github.com

CPU dispatcher: numpy.org

build options: numpy.org

Red Hat RHEL: www.redhat.com

Red Hat RHEL AI: www.redhat.com

RedHats presentation: wheelnext.dev

CUDA release: developer.nvidia.com

requires a PEP: discuss.python.org

WheelNext: wheelnext.dev

Github repo: github.com

PEP 817: peps.python.org

PEP 825: discuss.python.org

uv: docs.astral.sh

A variant-enabled build of uv: astral.sh

pyx: astral.sh

pypackaging-native: pypackaging-native.github.io

PEP 784: peps.python.org

Watch this episode on YouTube: youtube.com

Episode #544 deep-dive: talkpython.fm/544

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: @talkpython@fosstodon.org

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @mkennedy@fosstodon.org

Michael on X.com: @mkennedy

#544: Wheel Next + Packaging PEPs

When you type a question into ChatGPT, the model only has what you typed to work with. But tools like Claude Code can plan, iterate, test, and recover from mistakes. They work more like we do. The difference is the agent harness: Planning tools, file system access, sub-agents, and carefully crafted system prompts that turn a raw LLM into something genuinely capable.

Sydney Runkle is back on Talk Python representing LangChain and their new open source library, Deep Agents: A framework for building your own deep agents with plain Python functions, middleware hooks, and MCP support. This is how the magic works under the hood.

Episode sponsors

Sentry Error Monitoring, Code talkpython26

Agentic AI Course

Talk Python Courses

Links from the show
Guest

Sydney Runkle: github.com

Claude Code uses: x.com

Deep Research: openai.com

Manus: manus.im

Blog post announcement: blog.langchain.com

Claudes system prompt: github.com

sub agents: docs.anthropic.com

the quick start: docs.langchain.com

CLIs: github.com

Talk Python's CLI: talkpython.fm

custom tools: docs.langchain.com

DeepAgents Examples: github.com

Custom Middleware: docs.langchain.com

Built in middleware: docs.langchain.com

Improving Deep Agents with harness engineering: blog.langchain.com

Prebuilt middleware: docs.langchain.com

Watch this episode on YouTube: youtube.com

Episode #543 deep-dive: talkpython.fm/543

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: @talkpython@fosstodon.org

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @mkennedy@fosstodon.org

Michael on X.com: @mkennedy

#543: Deep Agents: LangChain's SDK for Agents That Plan and Delegate

If you've built documentation in the Python ecosystem, chances are you've used Martin Donath's work. His Material for MKDocs powers docs for FastAPI, uv, AWS, OpenAI, and tens of thousands of other projects. But when MKDocs 2.0 took a direction that would break Material and 300 ecosystem plugins, Martin went back to the drawing board. The result is Zensical: A new static site generator with a Rust core, differential builds in milliseconds instead of minutes, and a migration path designed to bring the whole community along.

Episode sponsors

Sentry Error Monitoring, Code talkpython26

Talk Python Courses

Links from the show
Guest

Martin Donath: github.com

Zensical: zensical.org

Material for MkDocs: squidfunk.github.io

Getting Started: zensical.org

Github pages: docs.github.com

Cloudflare pages: pages.cloudflare.com

Michaels Example: gist.github.com

Material for MkDocs: zensical.org

gohugo.io/content-management/shortcodes: gohugo.io

a sense of size of the project: blobs.talkpython.fm

Zensical Spark: zensical.org

Watch this episode on YouTube: youtube.com

Episode #542 deep-dive: talkpython.fm/542

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: @talkpython@fosstodon.org

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @mkennedy@fosstodon.org

Michael on X.com: @mkennedy

#541: Monty - Python in Rust for AI

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: @talkpython@fosstodon.org

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @mkennedy@fosstodon.org

Michael on X.com: @mkennedy

#540: Modern Python monorepo with uv and prek

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: @talkpython@fosstodon.org

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @mkennedy@fosstodon.org

Michael on X.com: @mkennedy

#539: Catching up with the Python Typing Council

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: @talkpython@fosstodon.org

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @mkennedy@fosstodon.org

Michael on X.com: @mkennedy

#538: Python in Digital Humanities

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: @talkpython@fosstodon.org

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @mkennedy@fosstodon.org

Michael on X.com: @mkennedy

#537: Datastar: Modern web dev, simplified

You've built your FastAPI app, it's running great locally, and now you want to share it with the world. But then reality hits -- containers, load balancers, HTTPS certificates, cloud consoles with 200 options. What if deploying was just one command? That's exactly what Sebastian Ramirez and the FastAPI Cloud team are building. On this episode, I sit down with Sebastian, Patrick Arminio, Savannah Ostrowski, and Jonathan Ehwald to go inside FastAPI Cloud, explore what it means to build a "Pythonic" cloud, and dig into how this commercial venture is actually making FastAPI the open-source project stronger than ever.

Episode sponsors

Command Book

Python in Production

Talk Python Courses

Links from the show
Guests

Sebastián Ramírez: github.com

Savannah Ostrowski: github.com

Patrick Arminio: github.com

Jonathan Ehwald: github.com

FastAPI labs: fastapilabs.com

quickstart: fastapicloud.com

an episode on diskcache: talkpython.fm

Fastar: github.com

FastAPI: The Documentary: www.youtube.com

Tailwind CSS Situation: adams-morning-walk.transistor.fm

FastAPI Job Meme: fastapi.meme

Migrate an Existing Project: fastapicloud.com

Join the waitlist: fastapicloud.com

Talk Python CLI

Talk Python CLI Announcement: talkpython.fm

Talk Python CLI GitHub: github.com

Command Book

Download Command Book: commandbookapp.com

Announcement post: mkennedy.codes

Watch this episode on YouTube: youtube.com

Episode #536 deep-dive: talkpython.fm/536

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: @talkpython@fosstodon.org

X.com: @talkpython

Michael on Bluesky: @mkennedy.codes

Michael on Mastodon: @mkennedy@fosstodon.org

Michael on X.com: @mkennedy

#536: Fly inside FastAPI Cloud

See the full show notes for this episode on the website at talkpython.fm/459

#459: I Built A Python SaaS with AI

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