Talk Python

Personal AI Agents for Pythonistas - Talk Python to Me Ep. 567

1.1K views · 2d ago · 1:10:01

The most popular Python project you've probably never heard of has 252,000 GitHub stars and merged over 1,800 pull requests in a single week. It's Hermes, a self-hosted AI agent you program just by talking to it. And it never clocks out. It runs 24/7 on a box in your house, wakes up every 15 minutes, keeps your YouTube channel in sync, and has your morning briefing ready before you're up. Mine started as a few config files.

State of the art in Python 2026 - Talk Python to Me Ep. 566

3.4K views · 1w ago · 1:14:27

Which of your Python tools would you still pick if you started fresh today? For a long time, the answer was easy. The stack felt settled. AI has reopened almost every one of those choices. Some tools got faster. Others got replaced outright. On this episode, a panel takes stock of the state of the art in Python for 2026. Calvin Hendryx-Parker is CTO and co-founder of Six Feet Up. Pat Decker works in DevOps at Hibu. Reuven Lerner has trained Python developers for 15 years.

Topics: Python Developers on Their Tool Stacks · AI Coding Editors: From VS Code to Slack · Modern Terminals, SSH, and Agent Workflows · Why UV Is Reshaping Python Packaging · FastAPI vs. Django for API Projects · Pydantic for Validation and AI Data

Tachyon, Python 3.15's Built-in Sampling Profiler - Talk Python to Me Ep. 565

2.6K views · 4w ago · 1:28:44

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.

EVE Online Departs for Python 3 - Talk Python to Me Ep. 564

1.4K views · 1mo ago · 1:10:27

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.

Getting Started with Rust as Python Devs - Talk Python to Me Ep. 563

1.9K views · 1mo ago · 1:09:25

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.

DuckLake: The Lakehouse That's Just SQL and Parquet - Talk Python to Me Ep. 562

2.2K views · 1mo ago · 1:12:48

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.

12 Things You Should (and Shouldn't) Do in AWS - Talk Python to Me Ep. 559

876 views · 1mo ago · 1:09:37

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.

TonIO, a Multi-threaded Async Runtime for Python - Talk Python to Me Ep. 561

1.2K views · 1mo ago · 1:22:46

▬▬▬▬ About the podcast ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ ▬▬▬▬ Guests ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Giovanni Barillari ▬▬▬▬ Links and resources from the show ▬▬▬▬▬▬▬▬▬▬▬▬ Granian Hyper Free threaded Python Sort of did a whole course uvloop rloop TonIO your EuroPython 2026 talk Michael's Cutting Python Web App Memory Over 31% Article

Building a Research OS: From Django to 30,000 Samples - Talk Python to Me Ep. 560

1.4K views · 2mo ago · 1:03:31

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.

Hyper-Personal Software with Python - Talk Python to Me Ep. 558

432 views · 3mo ago · 1:13:26

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.

Security of everything at PyCon 2026 - Talk Python to Me Ep. 557

690 views · 3mo ago · 1:10:03

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.

Updates on Django's Async Story - Talk Python to Me Ep. 556

725 views · 3mo ago · 1:07:26

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.

Marimo Pair - A Canvas for Agent + Developers Collaboration - Talk Python to Me Ep. 555

537 views · 4mo ago · 1:06:31

Guest: Marimo Pair

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.

Trustworthy AI in Healthcare and Longevity - Talk Python to Me Ep. 554

341 views · 4mo ago · 1:04:21

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.

AI Contributions and Maintainer Load in Open Source - Talk Python to Me Ep. 550

315 views · 5mo ago · 1:06:53

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.