Explorez tous les épisodes du podcast Talk Python To Me

Do you know what's actually slow in your Python app? Or are you guessing? Until now, profiling Python meant a tracing profiler that made your code 2 to 3 times slower. Or a third-party tool that broke with every new release. Python 3.15 fixes that. It ships Tachyon, a sampling profiler built into the standard library. It attaches to live production apps with almost zero overhead. My guests are Pablo Galindo Salgado, CPython core developer and Steering Council member, and László Kiss Kollár from Bloomberg's Python infrastructure team. Their first prototype ran at two samples a second. Now it does over a million hz. And it lands in Python 3.15 this October.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Python in Production
Talk Python Courses

Links from the show Guests
László Kiss Kollár: linkedin.com
Pablo Galindo Salgado

3.11: talkpython.fm
Memray: talkpython.fm
PyStack: talkpython.fm
profile and cProfile: docs.python.org
py-spy: github.com
Austin: github.com
PEP 799: peps.python.org
PEP 768: peps.python.org
PyCon US 2026 talk: us.pycon.org
The docs: docs.python.org
Backport to 3.14: github.com

Watch this episode on YouTube: youtube.com
Episode #565 deep-dive: talkpython.fm/565
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

Every ship in EVE Online eventually undocks and leaves the station. This time, it's the whole game. EVE has run on Python 2 since it launched in 2003, all 2.4 million lines of it, on a custom Stackless interpreter that stopped at 3.8 and was archived last year. Destination: Python 3.12. The route runs through 6,500 lines of division that decide who wins a fight, and 100 gigabytes of pickled Python objects that have to survive the jump intact. Kristinn Sigurbergsson was on this show ten years ago. He's back, with Jamie Bannister, who is flying the EVE Online migration right now, and Thomas Dähling, who took EVE Frontier through first. In EVE, a destroyed ship is gone for good. There are no do-overs, and the universe has to stay online the whole way.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Talk Python Courses

Links from the show Guests
Jamie Bannister: linkedin.com
Thomas Dähling: linkedin.com
Kristinn Sigurbergsson: linkedin.com

EVE Online: www.eveonline.com
EVE Frontier: evefrontier.com
2.4 million lines of Python: www.eveonline.com
Example of graphics, ships walk-through: www.youtube.com
Stackless: www.stackless.com
futurize: python-future.org
blue: github.com
Dev blog on the Frontier upgrade: evefrontier.com
Upgrading CARBON to Python 3: www.youtube.com
carbon-scheduler: github.com
Scheduling in Carbon: Leaving Stackless Python Behind: www.youtube.com
All of Carbon is on GitHub now: github.com
did a whole course: training.talkpython.fm
Trade Wars BBS (Wikipedia): en.wikipedia.org
TW 3002 - TradeWars 2002, reimagined as a modern browser game: www.reddit.com

Watch this episode on YouTube: youtube.com
Episode #564 deep-dive: talkpython.fm/564
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

Lint the entire CPython code base from scratch. It takes 0.3 seconds. Three blinks of an eye.

That is ruff, and it is written in Rust. So are Pydantic, Polars, uv, and Granian. Rust shows up in Python three ways: tools that happen to be Rust, libraries Python imports, and servers that run Python inside Rust. This is Rust for Python developers, not Rust experts.

Christopher Trudeau is back on Talk Python to discuss Rust and his latest course Up and Running with Rust. The core rule is that only one thing can own a value at a time. Pass it around freely in Python and the garbage collector cleans up. Do that in Rust and it will not compile.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Python in Production
Talk Python Courses

Links from the show Up and Running with Rust course: training.talkpython.fm

Rust: rust-lang.org
pydantic: pydantic.dev
ruff: docs.astral.sh
granian: github.com
By example: doc.rust-lang.org
rust-lang.org: rust-lang.org
rustup.rs: rustup.rs
crates.io: crates.io
main.rs: main.rs
PyO3: github.com
https://github.com/ritwiktiwari/awesome-python-rs: github.com
ty: docs.astral.sh
pyrefly: pyrefly.org
uv: github.com
polars: pola.rs

Watch this episode on YouTube: youtube.com
Episode #563 deep-dive: talkpython.fm/563
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

How many files does your query read before it reads any data? On some data lakes, you go through JSON and metadata files first, just to learn which Parquet files matter. DuckLake asks one SQL question instead. The metadata lives in a real database. The data stays in plain Parquet. That's the entire format.

Pedro Holanda joined DuckDB in 2018, when it was still a research prototype at CWI. He's the lead DuckLake developer. Guillermo Sanchez Dionis works on DuckLake and the new Quack protocol.

With Quack as the catalog, DuckLake handles 200 transactions a second under heavy contention. No other open table format comes close.

Episode sponsors

Six Feet Up
Talk Python Courses

Links from the show Guests
Pedro Holanda: pedroholanda.org
Guillermo Sanchez: linkedin.com

PhD on progressive indexes: ir.cwi.nl
SQLite: www.sqlite.org
Litestream: litestream.io
boring hardware: talkpython.fm
DuckDB: duckdb.org
episode 491: talkpython.fm
Iceberg: iceberg.apache.org
manifesto: ducklake.select
DuckLake: ducklake.select
spec: ducklake.select
this diagram: blobs.talkpython.fm
Data inlining: ducklake.select
ducklake-dataframe: github.com
Polars course: training.talkpython.fm
CSV parser: duckdb.org
Zero-copy Arrow: duckdb.org
ART index: duckdb.org
async I/O: duckdb.org
v1.0: ducklake.select
Git-like branching: ducklake.select

Watch this episode on YouTube: youtube.com
Episode #562 deep-dive: talkpython.fm/562
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

How many cores does your machine have, 10, 18? Your async Python code uses just one of them. That isn't a bug in asyncio. That's the design, and optimizing event loops to be faster by 20% doesn't change it. So Giovanni Barillari started over. Joe is the creator of Granian, the Rust-based server that powers Talk Python. His new project is TonIO, an async runtime written from scratch for free-threaded Python. Real threads, a handful of primitives instead of asyncio's pile of them, and it flat out refuses to start if the GIL is on.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Python in Production
Talk Python Courses

Links from the show Guest
Giovanni Barillari: github.com

Granian: github.com
Hyper: github.com
Free threaded Python: docs.python.org
Sort of: labs.quansight.org
did a whole course: training.talkpython.fm
uvloop: github.com
rloop: github.com
TonIO: github.com
your EuroPython 2026 talk: www.youtube.com
Michael's Cutting Python Web App Memory Over 31% Article: mkennedy.codes

Watch this episode on YouTube: youtube.com
Episode #561 deep-dive: talkpython.fm/561
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

In 2020, a gastroenterologist in Glasgow did the math on his new research study and came up with 30,000 samples, arriving over two years from three cities and a dozen hospitals. He asked around about how researchers keep track of that. The answer was Microsoft Excel. Shaun Chuah had written some HTML by hand in Notepad back in high school and that was about the whole of his programming experience, so he opened the Django tutorial and started reading. Six years later that app is Foundry120, holding 10 terabytes of clinical and genomics data with an agentic AI running on top of it.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Talk Python Courses
Talk Python Courses

Links from the show Guest
Shaun Chuah: github.com

Up and Running with Rust Course: talkpython.fm

Foundry120: www.foundry120.com
Designing Data Intensive Applications: www.oreilly.com
Microsoft Foundry: ai.azure.com
ChatIBD: www.chatibd.com
Blog: shaunchuah.github.io
@drshaunchuah: x.com
github.com/shaunchuah: github.com

Watch this episode on YouTube: youtube.com
Episode #560 deep-dive: talkpython.fm/560
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

Your site is down. It's 3am. Is it a bug, a bill, or a breach? You can't tell yet, and everyone is watching you find out. Matt Lea has spent fifteen years being the person companies call when an outage is costing them real money per hour, and his whole argument is that everything you'd want in that moment gets decided months earlier, on ordinary afternoons, when someone chose the convenient thing. We walk his top twelve dos and don'ts in AWS - infrastructure as code, IAM roles instead of access keys, private subnets, no wildcards, no public buckets - and I push on which of them actually matter if you're one person on a small VPS. Then we get to Cloud War Games, where Matt breaks things on purpose so your team's first real incident isn't their first incident. Let's get into it.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Talk Python Courses
Talk Python Courses

Links from the show Guest
Matt Lea: linkedin.com

Talk Python Certificates: training.talkpython.fm/certificates

Schematical: schematical.com
CloudWarGames.com: cloudwargames.com
Zero to Hero on AWS Security: www.oreilly.com
Repo: github.com
Custom Wheel Offset: customwheeloffset.com
2012 TechCrunch Disrupt Hackathon: techcrunch.com
tech comics: schematical.com
shhgit: github.com
Zero Trust in 200ms: Implementing Identity-Per-Transaction: us.pycon.org
Coolify: coolify.io
returned to full GA Nov 2025: aws.amazon.com
Signed URLs/cookies: docs.aws.amazon.com
Cloudflare: www.cloudflare.com
Bunny Shield: bunny.net
Cloud War Games One: www.youtube.com
Cloud War Games Two: www.youtube.com
LinkedIn: linkedin.com
YouTube: youtube.com
KnocKnoc: knocknoc.io

Watch this episode on YouTube: youtube.com
Episode #559 deep-dive: talkpython.fm/559
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

Every company has one. The little internal tool that Jane built back in 2021, and then Jane left. Nobody understands it, nobody will touch it. There are two unwritten rules around it: don't change it, it's working. And if you break it, you bought it. That's dark-matter enterprise software.

For every app you can actually see, there are ten of these sitting in the shadows, frozen. Michael Booth thinks that just changed. He read my article on hyper-personal software and ran with it, writing about hyper-team software: small teams inside big companies finally building the tools that were never going to get built.

We cover where this works, where it quietly goes wrong, and the guardrails that keep it from turning into a mess. Let's get into it.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Python in Production
Talk Python Courses

Links from the show Guest
Michael Booth: github.com

Talk Python AI Integrations: talkpython.fm/blog

From Hyper-Personal to Hyper-Team Software: Small Team-Built, AI-Assisted Tools Inside the Enterprise: www.databooth.com.au

What hyper-personal software looks like (MK's article): mkennedy.codes

Databooth Site: www.databooth.com.au

Wall Street just lost $285 billion because of 13 markdown files: martinalderson.com
SaaSpocalypse is real but everyone is panicking about the wrong thing: www.reddit.com
Warp Terminal: www.warp.dev

Watch this episode on YouTube: youtube.com
Episode #558 deep-dive: talkpython.fm/558
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

Security has always been the vegetables of software. Everyone agrees it matters, and somehow it never quite makes it onto the plate. At PyCon US this year, that changed. For the first time ever, security got its own dedicated, day-long track, one of just two at the whole conference, sitting right next to AI. And the room was packed to the back wall.

On this episode, I'm joined by the three people at the center of it. Seth Larson, Security Developer in Residence at the Python Software Foundation and, very recently, a CPython core developer. Juanita Gomez, a PhD researcher at UC Santa Cruz in open source security, who co-chaired the track. And Mike Fiedler, PyPI's Safety and Security Engineer, one of the very few people paid full-time to keep the packages you install safe.

We use the arc of the track's talks to take the temperature of Python security right now: supply chain attacks, dependency cooldowns, zero trust, SBOMs, and the push to bring Rust into CPython. And why not one of us thinks security is anywhere close to solved. Turns out that's the good news. It's why the room was full.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Talk Python Courses

Links from the show Guests
Juanita Gomez: linkedin.com
Mike Fiedler: miketheman.dev
Seth Michael Larson: sethmlarson.dev

Trailblazing Python Security: us.pycon.org
Everything Security at PyCon US 2026 (PSF blog): pyfound.blogspot.com
Dependency Cooldowns: cooldowns.dev
Anatomy of a Phishing Campaign (Mike Fiedler) Recording: www.youtube.com
FedRAMP: www.gsa.gov
Zero Trust in 200ms: Implementing Identity-Per-Transaction with Python & Serverless-Tristan McKinnon: www.youtube.com
Rust for CPython project: blog.python.org
pre-PEP: discuss.python.org
Rust for CPython: Making Python Safer and More Robust for Everyone - Emma Smith: www.youtube.com
SBOMit: github.com
Asleep at the Wheel: Getting your SBOMs to pay attention... - Sanchit Sahay, Abhishek Reddypalle: www.youtube.com
Volatility: volatilityfoundation.org
Post Incident Runtime SBOM Generation from Python Memory - Hala Ali: www.youtube.com
zizmor: docs.zizmor.sh
GitHub Actions security in Python packages (Andrew Nesbitt write-up): nesbitt.io
andrew/pycon: data & analysis for the GitHub Actions security talk: github.com
GitHub Actions Security in Python Packages - Andrew Nesbitt: www.youtube.com
gh-profiler: examine a GitHub user's profile to gauge their contributions: github.com
PyCon US YouTube channel: www.youtube.com
SBOMit: adding verification to SBOMs (OpenSSF): openssf.org
Ecosystems: ecosyste.ms

Watch this episode on YouTube: youtube.com
Episode #557 deep-dive: talkpython.fm/557
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

For years, "Django and async" came with an asterisk. The docs themselves warned you off it. Scary performance notes, a story that felt half-finished. Well, that story just got rewritten, literally, and the person who rewrote it is here to tell you why the old framing was wrong.

Carlton Gibson is a former Django Fellow, sat on the security team for eight years, and he's on the steering council. On this episode we get into the async topic doc rewrite, what actually remains versus what was just fear, the new Tasks framework in 6.0, DB-level cascades and fetch modes landing in 6.1, and why free-threading is the bet that's about to pay off big for Django. If you've been told Django's async story isn't ready, this is the episode that puts that myth to bed.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Python in Production
Talk Python Courses

Links from the show DjangoCon Europe: djangocon.eu
PyCon Italia: pycon.it
Django on the Med: djangomed.eu
Django Mantle: noumenal.es
PyPI: pypi.org
release notes: docs.djangoproject.com
on_delete: docs.djangoproject.com
Fetch modes: docs.djangoproject.com
HttpRequest.multipart_parser_class: docs.djangoproject.com
async topic doc: docs.djangoproject.com
docs: docs.djangoproject.com
DEP 14: github.com
django-tasks: github.com
django-tasks-local: github.com
Celery: docs.celeryq.dev
PEP 703: peps.python.org
free-threading HOWTO: docs.python.org
PEP 779: peps.python.org
ASGI: docs.djangoproject.com
PGBouncer: www.pgbouncer.org
Channels: channels.readthedocs.io
sync_to_async / async_to_sync: docs.djangoproject.com
noumenal.es: noumenal.es
Django Chat: djangochat.com
@carlton@fosstodon.org: fosstodon.org
Article: Cutting Python Web App Memory Over 31%: mkennedy.codes

Watch this episode on YouTube: youtube.com
Episode #556 deep-dive: talkpython.fm/556
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

Coding agents have gotten really good at one kind of work. You scope a feature, edit some files, run the tests, ship it. It all happens on disk. But that is not how data work feels. You load something, you look at it, you run a cell, you watch how it responds, and you decide the next move from whatever is sitting in memory. And until now, your agent couldn't see any of that. It only saw the files. Never the live state.

This episode, that wall comes down. marimo pair drops a coding agent right inside a running notebook, with full access to every variable Python is holding in memory. The notebook becomes a shared canvas. You point, it runs the code. You tell it to zoom in on the Picasso paintings, and the chart just updates. No MCP tools to wire up, no schema to describe. Just Python, and an agent that can finally see what you see. Trevor Manz is back to walk us through it.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Talk Python Courses

Links from the show marimo pair: marimo.io/pair

Course transcripts announcement: talkpython.fm/blog

anywidget: Jupyter Widgets made easy: talkpython.fm
marimo: marimo.io
blog: marimo.io
GitHub: github.com
given this: martinalderson.com
llms.txt: talkpython.fm
mcp: talkpython.fm
cli: talkpython.fm
open issues: github.com
Discord: marimo.io
Marimo Pair: marimo.io
OpenCode: opencode.ai
AI Tooling for Software Engineers in 2026: newsletter.pragmaticengineer.com

Watch this episode on YouTube: youtube.com
Episode #555 deep-dive: talkpython.fm/555
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

You ask an AI a question and it answers with total confidence. Most of the time, a confidently wrong answer is just an annoyance. But what if the question is medical, and there's a real patient on the other end? In that world, a hallucination isn't a bug, it's a patient-safety event. Sumit Gundawar is a London-based software engineer who builds the clinical platform for a UK longevity and aesthetic-medicine clinic, and his whole argument is that in high-stakes AI, the model is the easy part. Earning trust is the real engineering. We dig into grounding, refusal logic, human-in-the-loop design, and the messy frontier of longevity and biohacking, plus a live demo of an assistant that refuses to answer when it can't back up the claim. Let's get into it.

Episode sponsors

Six Feet Up
Talk Python Courses

Links from the show Guest
Sumit Gundawar: linkedin.com

Course transcripts announcement: talkpython.fm/blog

Sumit Gundawar - JAX London Speaker: jaxlondon.com
Anthropic: anthropic.com
OpenAI Platform: platform.openai.com
Anthropic: anthropic.com
LangChain: langchain.com
OWASP: owasp.org
Pydantic: pydantic.dev
EU AI Act - Regulatory Framework: digital-strategy.ec.europa.eu
HIPAA - HHS: www.hhs.gov
NHS: www.nhs.uk
Llama: llama.com
Qwen - QwenLM on GitHub: github.com
OpenAI Platform: platform.openai.com
Hugging Face: huggingface.co
Llama: llama.com
Granola: www.granola.ai
HIPAA - HHS: www.hhs.gov
CodeRabbit: www.coderabbit.ai
Cursor Origin: cursor.com
GitHub Status: www.githubstatus.com
Midjourney Medical: www.midjourney.com
Neko Health: www.nekohealth.com
CERN: home.cern
ATLAS Experiment: atlas.cern

Watch this episode on YouTube: youtube.com
Episode #554 deep-dive: talkpython.fm/554
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

This episode is a fun crossover from our Python news and tips podcast, Python Bytes. We have had some big changes over there. Brian Okken has moved on and Calvin Hendryx-Parker has joined the show as the new co-host. To kick off this new era, we decided to do a longer and more personal episode called "All Our Tools". The idea is both of us talk about some of our most useful day-to-day developer and business owner tools that we think you all would find useful. It was so well received, that I'm bringing it to you all as a crossover episode. Enjoy and we hope you find something new and awesome to help you with your software and data science day to day.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Python in Production
Talk Python Courses

Links from the show Guest
Calvin Hendryx-Parker: linkedin.com

@calvinhp@sixfeetup.social: sixfeetup.social
@calvinhp.com: bsky.app
calvinhp.com: calvinhp.com

Original airing on Python Bytes: pythonbytes.fm

pi: pi.dev
superpowers: github.com
Warp.dev: Warp.dev
OhMyZSH: ohmyz.sh
Commandbookapp.com: Commandbookapp.com
Blink: blink.sh
kitty: sw.kovidgoyal.net
mosh: mosh.org
tmux: github.com
Claude code: www.anthropic.com
Claude.md: Claude.md
MacWhisper: goodsnooze.gumroad.com
Handy: handy.computer
Tailscale: tailscale.com
Talk Python episode with Alex: talkpython.fm
Telescopo: www.telescopo.app
Typora markdown: typora.io
formal documentation for many of my open source packages: mkennedy.codes
Great Docs: posit-dev.github.io
Statement on the US government directive to suspend access to Fable 5 and Mythos 5: www.anthropic.com
No second date: x.com

Watch this episode on YouTube: youtube.com
Episode #553 deep-dive: talkpython.fm/553
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

OpenAI just acquired Astral, the company behind uv, Ruff, and ty. And if your first thought was "wait, is uv toast?", you are not alone. But here's the twist Charlie Marsh shared with me: he thinks they may ship more open source at OpenAI than they ever did at Astral. On this episode, we get into the acquisition, the mixed feelings, the future of your favorite Python tools, and what it's like to build right at the center of the AI universe.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Talk Python Courses

Links from the show Guest
Charlie Marsh: github.com

The announcement: astral.sh
OpenAI: openai.com
uv: github.com
ty: github.com
Ruff: github.com
pyx: astral.sh
Codex team: openai.com
Anthropic did something similar by acquiring Bun: www.anthropic.com
Daily Stars Explorer: emanuelef.github.io

Agentic AI Programming for Python: training.talkpython.fm
Python Web Security: OWASP Top 10 with Agentic AI: training.talkpython.fm

Episode #552 deep-dive: talkpython.fm/552
Episode transcripts: talkpython.fm

Theme Song: Developer Rap
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YouTube: youtube.com/@talkpython

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Michael on Bluesky: @mkennedy.codes
Michael on Mastodon: @mkennedy@fosstodon.org
Michael on X.com: @mkennedy

If you've ever been to PyCon, you know one of the best parts of the expo hall is Startup Row, a stretch of booths where early-stage companies built on Python show off what they're creating. But only attendees get to walk that lane, so let's bring it to everyone. In this episode, we stroll down Startup Row together. We kick things off with the organizers, Jason and Shay, who share the program's origin story going back to Paul Graham and the PSF, plus some surprising stats, including two unicorns among the alumni. Then we meet five startups: Tetrix, bringing AI to institutional investing in private markets. Arcjet, security that lives inside your app as an SDK. Phemeral.dev, serverless hosting built for Python web apps. CapiscIO, an identity and authority layer for AI agents. And Pixeltable, a multimodal database from Marcel Kornacker, co-creator of Apache Parquet. See if you can spot the theme running through them all. Let's go for a walk.

Episode sponsors

AgentField AI
Talk Python Courses

Links from the show Guests
Naunidh Bhalla: linkedin.com
Grant Gittes: linkedin.com
Marcel Kornacker: linkedin.com
Beon de Nood: linkedin.com
Chinmaya Joshi: linkedin.com
David Mytton: linkedin.com
Shea Tate-Di Donna: linkedin.com
Jason Rowley: linkedin.com
Azul Garza: github.com
Renée Rosillo: linkedin.com

Tetrix: tetrix.co
Tetrix Jobs: tetrix.co
Arcjet: arcjet.com
Pixeltable: pixeltable.com
Phemeral.dev: phemeral.dev
CapiscIO: capisc.io

Episode #551 deep-dive: talkpython.fm/551
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

You wake up, brew the coffee, open GitHub, and there it is. Another pull request on your open source project. Thirteen thousand lines added. No issue filed first. No discussion. Just "here, please review this for me."

Over the past year, GitHub activity has spiked roughly twelve times in a few short months, and a huge chunk of that signal is landing on the same small group of maintainers who were already stretched thin. The curl bug bounty got buried under AI-generated noise. Jazzband, the home of Django classics like pip-tools and the Django debug toolbar, hit what its maintainer called an "apocalypse" and started sunsetting. Even CPython just shipped fresh guidelines on AI-assisted contributions this week.

So what does all of this actually look like from the receiving end of the pull request?

On this episode, Paolo Melchiorre joins us to tell that story from inside the maintainer's chair. Paolo is a director of the Django Software Foundation, an organizer of PyCon Italy, a Django Girls coach, and he has spent the past year carefully collecting examples of how AI is reshaping open source contributions. The good, the bad, and the extra fingers.

We dig into his PyCon US talk on AI-assisted contributions and maintainer load, why AI is best understood as an amplifier rather than a new kind of contributor, the wildly different policies across 86 open source foundations, whether projects banning AI today are reacting to last year's models.

Episode sponsors

AgentField AI
Talk Python Courses

Links from the show Guest
Paolo Melchiorre: github.com

DSF: www.djangoproject.com
djangonaut-space: djangonaut.space
PyCon Italia: 2026.pycon.it
uDjango: github.com
My PyCon US 2026 post: www.paulox.net
AI-Assisted Contributions and Maintainer Load: www.paulox.net
Senior Engineer Tries Vibe Coding: www.youtube.com
Code Rabbit AI PR Reviews: www.coderabbit.ai
GitHub Usage Graphs: github.blog
Update on CPython's AI Policies: fosstodon.org
High-Quality Chaos from Curl: daniel.haxx.se
The Generative AI Policy Landscape in Open Source: redmonk.com

Watch this episode on YouTube: youtube.com
Episode #550 deep-dive: talkpython.fm/550
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

Your documentation has two audiences now - humans reading the rendered HTML, and AI agents trying to make sense of your library. Rich Iannone and Michael Chow from Posit are back on Talk Python with a brand new Python documentation tool called Great Docs that takes both seriously. Rich is the creator of Great Tables, and before that the R package GT, the man has a serious eye for design, and he's pointed that energy at the Python docs ecosystem. We'll talk about how Great Docs spins up a polished site in three commands, why every page ships as Markdown for your favorite LLM, how it leans on Quarto for executable code blocks and tabbed install sections, and where it lands against Sphinx, MkDocs, and Zensical. Plus, you'll meet Tablin. Here we go.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Temporal
Talk Python Courses

Links from the show Guests
Michael Chow: github.com
Rich lannone: github.com

Python Web Security with OWASP Top 10 and Agentic AI Course: talkpython.fm

Great Docs: posit-dev.github.io/great-docs
Great Tables: posit-dev.github.io
GT Episode: talkpython.fm
Sphinx: www.sphinx-doc.org
mkdocs: www.mkdocs.org
Zensical: zensical.org
Hugo: gohugo.io
Ghost: ghost.org
Rs pkgdown: pkgdown.r-lib.org
Quarto: quarto.org
quickstart: posit-dev.github.io
llms.txt file: llmstxt.org
llms.txt: talkpython.fm
mcp: talkpython.fm
cli: talkpython.fm

Watch this episode on YouTube: youtube.com
Episode #549 deep-dive: talkpython.fm/549
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

What if your database worked more like Git? Every change captured as an immutable event you can replay, instead of a single mutating row that quietly forgets its own history. That's event sourcing, and Chris May is back on Talk Python, fresh off our Datastar panel, to walk us through what it actually looks like in Python. We'll cover the core patterns, the libraries to reach for, when not to use it, and why event sourcing turns out to be a surprisingly good fit for AI-assisted coding.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Temporal
Talk Python Courses

Links from the show Guest
Chris May: everydaysuperpowers.dev

Intro to event sourcing e-book: everydaysuperpowers.gumroad.com

Domain-Driven Design: The Power of CQRS and Event Sourcing: How CQRS/ES Redefine Building Scalable System: ricofritzsche.me
DDD: www.amazon.com
Understanding Eventsourcing (Martin Dilger): www.amazon.com
Event Sourcing Explained using Football Video: www.youtube.com
Why I finally embraced event sourcing and why you should too article: everydaysuperpowers.dev
valkey: valkey.io
diskcache: talkpython.fm
eventsourcing package: github.com
eventsourcing docs: eventsourcing.readthedocs.io
John Bywater: github.com
Datastar: data-star.dev
Microconf: microconf.com
Event Modeling & Event Sourcing Podcast: podcast.eventmodeling.org
Python Package Guides for AI Agents: github.com
Iodine tablets AI joke: x.com
KurrentDb: www.kurrent.io

Watch this episode on YouTube: youtube.com
Episode #548 deep-dive: talkpython.fm/548
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

When OpenAI trained GPT-3, they didn't roll their own orchestration layer. They used Ray, an open source Python framework born out of the same Berkeley research lab lineage that gave us Apache Spark. And here's the twist: Ray was originally built for reinforcement learning research, then quietly faded as RL hit a wall. Until ChatGPT showed up. Suddenly reinforcement learning was back, as the post-training step that turns a raw language model into something genuinely useful.

Edward Oakes and Richard Liaw, two founding engineers behind Ray and Anyscale, join me on Talk Python to tell that story. We'll trace Ray from its RISE Lab origins at UC Berkeley to powering some of the largest training runs in the world. We'll talk about what Ray actually is, a distributed execution engine for AI workloads, and how a few lines of Python become work running across hundreds of GPUs. We'll cover Ray Data for multimodal pipelines, the dashboard, the VS Code remote debugger, KubRay for Kubernetes, and where Ray fits alongside Dask, multiprocessing, and asyncio.

If you've ever stared at a single-machine Python script and thought, "there has to be a better way to scale this", this one's for you

Episode sponsors

Sentry Error Monitoring, Code talkpython26
AgentField AI
Talk Python Courses

Links from the show Guests
Richard Liaw: github.com
Edward Oakes: github.com

Ray: www.ray.io
Example code (we used for walk-through): docs.ray.io
Getting Started with Ray: docs.ray.io
Ray Libraries: docs.ray.io
kuberay: github.com

Watch this episode on YouTube: youtube.com
Episode #547 deep-dive: talkpython.fm/547
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

The cloud is convenient until it isn't. You upload your photos, sync your contacts, click through the cookie banners. Then prices go up again or you read about a family that lost their entire Google account over a medical photo sent to a doctor. At some point, the question shifts from "why would I run this myself?" to "why aren't I?"

My guest this week is Alex Kretzschmar, head of DevRel at Tailscale, longtime host of the Self-Hosted podcast, and co-founder of Linuxserver.io. We cover what self-hosting really means in 2026, the apps worth running yourself like Immich and Home Assistant, why Docker Compose ties it all together, and how Tailscale lets you reach any of it from anywhere, without opening a single port. If you've been thinking about pulling your digital life back behind your own walls, this is your roadmap.

Episode sponsors

Temporal
Talk Python Courses

Links from the show Guest
Alex Kretzschmar: alex.ktz.me

Bitflip podcast: bitflip.show
Self-Hosted podcast (Alex's previous show): selfhosted.show
Perfect Media Server: perfectmediaserver.com
KTZ Systems on YouTube: youtube.com/@ktzsystems
Linuxserver.io (co-founded by Alex): linuxserver.io
"How Tailscale Works" blog post: tailscale.com/blog/how-tailscale-works
https://tailscale.com/: tailscale.com

Self-hosted apps discussed
Awesome Self-Hosted (GitHub list): github.com
Immich (Google Photos alternative): immich.app
Home Assistant: home-assistant.io
Open Home Foundation: openhomefoundation.org
Plausible Analytics: plausible.io
Umami Analytics: umami.is
Python integration for umami: pypi.org
Pi-hole: pi-hole.net
AdGuard Home: adguard.com
NextDNS: nextdns.io
Coolify: coolify.io
Docker + ufw: docs.docker.com

Storage, backup & filesystem
OpenZFS: openzfs.org
ZFS.rent (offsite ZFS replication): zfs.rent
Backblaze: backblaze.com
Hetzner Storage Box: hetzner.com
DigitalOcean: digitalocean.com

Secrets management mentioned
OpenBao (open-source Vault fork): openbao.org
HashiCorp Vault: hashicorp.com
Bitwarden: bitwarden.com
1Password: 1password.com

Hardware mentioned
Proxmox VE: proxmox.com
Minisforum MS01: minisforum.com
Zima Board / Zima OS: zimaspace.com

Other references
Cory Doctorow on "enshittification" (Cory's blog where he coined the term): pluralistic.net
Linus Tech Tips' WAN Show (Linus mentioned NAS-building going mainstream): linustechtips.com

Watch this episode on YouTube: youtube.com
Episode #546 deep-dive: talkpython.fm/546
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

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

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