Episodes

2d ago

#531: Talk Python in Production

Have you ever thought about getting your small product into production, but are worried about the cost of the big cloud providers? Or maybe you think your current cloud service is over-architected and costing you too much? Well, in this episode, we interview Michael Kennedy, author of "Talk Python in Production," a new book that guides you through deploying web apps at scale with right-sized engineering. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Christopher Trudeau - guest host : www.linkedin.com Michael's personal site : mkennedy.codes Talk Python in Production Book : talkpython.fm glances : github.com btop : github.com Uptimekuma : uptimekuma.org Coolify : coolify.io Talk Python Blog : talkpython.fm Hetzner (€20 credit with link) : hetzner.cloud OpalStack : www.opalstack.com Bunny.net CDN : bunny.net Galleries from the book : github.com Pandoc : pandoc.org Docker : www.docker.com Watch this episode on YouTube : youtube.com Episode #531 deep-dive : talkpython.fm/531 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

Dec 13

#530: anywidget: Jupyter Widgets made easy

For years, building interactive widgets in Python notebooks meant wrestling with toolchains, platform quirks, and a mountain of JavaScript machinery. Most developers took one look and backed away slowly. Trevor Manz decided that barrier did not need to exist. His idea was simple: give Python users just enough JavaScript to unlock the web’s interactivity, without dragging along the rest of the web ecosystem. That idea became anywidget, and it is quickly becoming the quiet connective tissue of modern interactive computing. Today we dig into how it works, why it has taken off, and how it might change the way we explore data. Episode sponsors Seer: AI Debugging, Code TALKPYTHON PyCharm, code STRONGER PYTHON Talk Python Courses Links from the show Trevor on GitHub : github.com anywidget GitHub : github.com Trevor's SciPy 2024 Talk : www.youtube.com Marimo GitHub : github.com Myst (Markdown docs) : mystmd.org Altair : altair-viz.github.io DuckDB : duckdb.org Mosaic : uwdata.github.io ipywidgets : ipywidgets.readthedocs.io Tension between Web and Data Sci Graphic : blobs.talkpython.fm Quak : github.com Walk through building a widget : anywidget.dev Widget Gallery : anywidget.dev Video: How do I anywidget? : www.youtube.com PyCharm + PSF Fundraiser : pycharm-psf-2025 code STRONGER PYTHON Watch this episode on YouTube : youtube.com Episode #530 deep-dive : talkpython.fm/530 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

Dec 3

#529: Computer Science from Scratch

A lot of people building software today never took the traditional CS path. They arrived through curiosity, a job that needed automating, or a late-night itch to make something work. This week, David Kopec joins me to talk about rebuilding computer science for exactly those folks, the ones who learned to program first and are now ready to understand the deeper ideas that power the tools they use every day. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON NordStellar Talk Python Courses Links from the show David Kopec : davekopec.com Classic Computer Science Book : amazon.com Computer Science from Scratch Book : computersciencefromscratch.com Computer Science from Scratch at NoStartch (CSFS30 for 30% off) : nostarch.com Watch this episode on YouTube : youtube.com Episode #529 deep-dive : talkpython.fm/529 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

Nov 30

#528: Python apps with LLM building blocks

In this episode, I’m talking with Vincent Warmerdam about treating LLMs as just another API in your Python app, with clear boundaries, small focused endpoints, and good monitoring. We’ll dig into patterns for wrapping these calls, caching and inspecting responses, and deciding where an LLM API actually earns its keep in your architecture. Episode sponsors Seer: AI Debugging, Code TALKPYTHON NordStellar Talk Python Courses Links from the show Vincent on X : @fishnets88 Vincent on Mastodon : @koaning LLM Building Blocks for Python Co-urse : training.talkpython.fm Top Talk Python Episodes of 2024 : talkpython.fm LLM Usage - Datasette : llm.datasette.io DiskCache - Disk Backed Cache (Documentation) : grantjenks.com smartfunc - Turn docstrings into LLM-functions : github.com Ollama : ollama.com LM Studio - Local AI : lmstudio.ai marimo - A Next-Generation Python Notebook : marimo.io Pydantic : pydantic.dev Instructor - Complex Schemas & Validation (Python) : python.useinstructor.com Diving into PydanticAI with marimo : youtube.com Cline - AI Coding Agent : cline.bot OpenRouter - The Unified Interface For LLMs : openrouter.ai Leafcloud : leaf.cloud OpenAI looks for its "Google Chrome" moment with new Atlas web browser : arstechnica.com Watch this episode on YouTube : youtube.com Episode #528 deep-dive : talkpython.fm/528 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

Nov 10

#527: MCP Servers for Python Devs

Today we’re digging into the Model Context Protocol, or MCP. Think LSP for AI: build a small Python service once and your tools and data show up across editors and agents like VS Code, Claude Code, and more. My guest, Den Delimarsky from Microsoft, helps build this space and will keep us honest about what’s solid versus what's just shiny. We’ll keep it practical: transports that actually work, guardrails you can trust, and a tiny server you could ship this week. By the end, you’ll have a clear mental model and a path to plug Python into the internet of agents. Episode sponsors Sentry AI Monitoring, Code TALKPYTHON NordStellar Talk Python Courses Links from the show Den Delimarsky : den.dev Agentic AI Programming for Python Course : training.talkpython.fm Model Context Protocol : modelcontextprotocol.io Model Context Protocol Specification (2025-03-26) : modelcontextprotocol.io MCP Python Package (PyPI) : pypi.org Awesome MCP Servers (punkpeye) GitHub Repo : github.com Visual Studio Code Docs: Copilot MCP Servers : code.visualstudio.com GitHub MCP Server (GitHub repo) : github.com GitHub Blog: Meet the GitHub MCP Registry : github.blog MultiViewer App : multiviewer.app GitHub Blog: Spec-driven development with AI (open source toolkit) : github.blog Model Context Protocol Registry (GitHub) : github.com mcp (GitHub organization) : github.com Tailscale : tailscale.com Watch this episode on YouTube : youtube.com Episode #527 deep-dive : talkpython.fm/527 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

Nov 1

#526: Building Data Science with Foundation LLM Models

Today, we’re talking about building real AI products with foundation models. Not toy demos, not vibes. We’ll get into the boring dashboards that save launches, evals that change your mind, and the shift from analyst to AI app builder. Our guide is Hugo Bowne-Anderson, educator, podcaster, and data scientist, who’s been in the trenches from scalable Python to LLM apps. If you care about shipping LLM features without burning the house down, stick around. Episode sponsors Posit NordStellar Talk Python Courses Links from the show Hugo Bowne-Anderson : x.com Vanishing Gradients Podcast : vanishinggradients.fireside.fm Fundamentals of Dask: High Performance Data Science Course : training.talkpython.fm Building LLM Applications for Data Scientists and Software Engineers : maven.com marimo: a next-generation Python notebook : marimo.io DevDocs (Offline aggregated docs) : devdocs.io Elgato Stream Deck : elgato.com Sentry's Seer : talkpython.fm The End of Programming as We Know It : oreilly.com LorikeetCX AI Concierge : lorikeetcx.ai Text to SQL & AI Query Generator : text2sql.ai Inverse relationship enthusiasm for AI and traditional projects : oreilly.com Watch this episode on YouTube : youtube.com Episode #526 deep-dive : talkpython.fm/526 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

Oct 27

#525: NiceGUI Goes 3.0

Building a UI in Python usually means choosing between "quick and limited" or "powerful and painful." What if you could write modern, component-based web apps in pure Python and still keep full control? NiceGUI, pronounced "Nice Guy" sits on FastAPI with a Vue/Quasar front end, gives you real components, live updates over websockets, and it’s running in production at Zauberzeug, a German robotic company. On this episode, I’m talking with NiceGUI’s creators, Rodja Trappe and Falko Schindler, about how it works, where it shines, and what’s coming next. With version 3.0 releasing around the same time this episode comes out, we spend the end of the episode celebrating the 3.0 release. Episode sponsors Posit Agntcy Talk Python Courses Links from the show Rodja Trappe : github.com Falko Schindler : github.com NiceGUI 3.0.0 release : github.com Full LLM/Agentic AI docs instructions for NiceGUI : github.com Zauberzeug : zauberzeug.com NiceGUI : nicegui.io NiceGUI GitHub Repository : github.com NiceGUI Authentication Examples : github.com NiceGUI v3.0.0rc1 Release : github.com Valkey : valkey.io Caddy Web Server : caddyserver.com JustPy : justpy.io Tailwind CSS : tailwindcss.com Quasar ECharts v5 Demo : quasar-echarts-v5.netlify.app AG Grid : ag-grid.com Quasar Framework : quasar.dev NiceGUI Interactive Image Documentation : nicegui.io NiceGUI 3D Scene Documentation : nicegui.io Watch this episode on YouTube : youtube.com Episode #525 deep-dive : talkpython.fm/525 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

Oct 20

#524: 38 things Python developers should learn in 2025

Python in 2025 is different. Threads really are about to run in parallel, installs finish before your coffee cools, and containers are the default. In this episode, we count down 38 things to learn this year: free-threaded CPython, uv for packaging, Docker and Compose, Kubernetes with Tilt, DuckDB and Arrow, PyScript at the edge, plus MCP for sane AI workflows. Expect practical wins and migration paths. No buzzword bingo, just what pays off in real apps. Join me along with Peter Wang and Calvin Hendrix-Parker for a fun, fast-moving conversation. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Calvin Hendryx-Parker : github.com/calvinhp Peter on BSky : @wang.social Free-Threaded Wheels : hugovk.github.io Tilt : tilt.dev The Five Demons of Python Packaging That Fuel Our ... : youtube.com Talos Linux : talos.dev Docker: Accelerated Container Application Development : docker.com Scaf - Six Feet Up : sixfeetup.com BeeWare : beeware.org PyScript : pyscript.net Cursor: The best way to code with AI : cursor.com Cline - AI Coding, Open Source and Uncompromised : cline.bot Watch this episode on YouTube : youtube.com Episode #524 deep-dive : talkpython.fm/524 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

Oct 13

#523: Pyrefly: Fast, IDE-friendly typing for Python

Python typing got fast enough to feel invisible. Pyrefly is a new, open source type checker and IDE language server from Meta, written in Rust, with a focus on instant feedback and real-world DX. Today, we will dig into what it is, why it exists, and how it plays with the rest of the typing ecosystem. We have Abby Mitchell, Danny Yang, and Kyle Into from Pyrefly here to dive into the project. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Abby Mitchell : linkedin.com Danny Yang : linkedin.com Kyle Into : linkedin.com Pyrefly : pyrefly.org Pyrefly Documentation : pyrefly.org Pyrefly Installation Guide : pyrefly.org Pyrefly IDE Guide : pyrefly.org Pyrefly GitHub Repository : github.com Pyrefly VS Code Extension : marketplace.visualstudio.com Introducing Pyrefly: A New Type Checker and IDE Experience for Python : engineering.fb.com Pyrefly on PyPI : pypi.org InfoQ Coverage: Meta Pyrefly Python Typechecker : infoq.com Pyrefly Discord Invite : discord.gg Python Typing Conformance (GitHub) : github.com Typing Conformance Leaderboard (HTML Preview) : htmlpreview.github.io Watch this episode on YouTube : youtube.com Episode #523 deep-dive : talkpython.fm/523 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

Oct 6

#522: Data Sci Tips and Tricks from CodeCut.ai

Today we’re turning tiny tips into big wins. Khuyen Tran, creator of CodeCut.ai, has shipped hundreds of bite-size Python and data science snippets across four years. We dig into open-source tools you can use right now, cleaner workflows, and why notebooks and scripts don’t have to be enemies. If you want faster insights with fewer yak-shaves, this one’s packed with takeaways you can apply before lunch. Let’s get into it. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Khuyen Tran (LinkedIn) : linkedin.com Khuyen Tran (GitHub) : github.com CodeCut : codecut.ai Production-ready Data Science Book (discount code TalkPython) : codecut.ai Why UV Might Be All You Need : codecut.ai How to Structure a Data Science Project for Readability and Transparency : codecut.ai Stop Hard-coding: Use Configuration Files Instead : codecut.ai Simplify Your Python Logging with Loguru : codecut.ai Git for Data Scientists: Learn Git Through Practical Examples : codecut.ai Marimo (A Modern Notebook for Reproducible Data Science) : codecut.ai Text Similarity & Fuzzy Matching Guide : codecut.ai Loguru (Python logging made simple) : github.com Hydra : hydra.cc Marimo : marimo.io Quarto : quarto.org Show Your Work! Book : austinkleon.com Watch this episode on YouTube : youtube.com Episode #522 deep-dive : talkpython.fm/522 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

Sep 29

#521: Red Teaming LLMs and GenAI with PyRIT

English is now an API. Our apps read untrusted text; they follow instructions hidden in plain sight, and sometimes they turn that text into action. If you connect a model to tools or let it read documents from the wild, you have created a brand new attack surface. In this episode, we will make that concrete. We will talk about the attacks teams are seeing in 2025, the defenses that actually work, and how to test those defenses the same way we test code. Our guides are Tori Westerhoff and Roman Lutz from Microsoft. They help lead AI red teaming and build PyRIT, a Python framework the Microsoft AI Red Team uses to pressure test real products. By the end of this hour you will know where the biggest risks live, what you can ship this quarter to reduce them, and how PyRIT can turn security from a one time audit into an everyday engineering practice. Episode sponsors Sentry AI Monitoring, Code TALKPYTHON Agntcy Talk Python Courses Links from the show Tori Westerhoff : linkedin.com Roman Lutz : linkedin.com PyRIT : aka.ms/pyrit Microsoft AI Red Team page : learn.microsoft.com 2025 Top 10 Risk & Mitigations for LLMs and Gen AI Apps : genai.owasp.org AI Red Teaming Agent : learn.microsoft.com 3 takeaways from red teaming 100 generative AI products : microsoft.com MIT report: 95% of generative AI pilots at companies are failing : fortune.com A couple of "Little Bobby AI" cartoons Give me candy : talkpython.fm Tell me a joke : talkpython.fm Watch this episode on YouTube : youtube.com Episode #521 deep-dive : talkpython.fm/521 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

Sep 23

#520: pyx - the other side of the uv coin (announcing pyx)

A couple years ago, Charlie Marsh lit a fire under Python tooling with Ruff and then uv. Today he’s back with something on the other side of that coin: pyx. Pyx isn’t a PyPI replacement. Think server, not just index. It mirrors PyPI, plays fine with pip or uv, and aims to make installs fast and predictable by letting a smart client talk to a smart server. When the client and server understand each other, you get new fast paths, fewer edge cases, and the kind of reliability teams beg for. If Python packaging has felt like friction, this conversation is traction. Let’s get into it. Episode sponsors Six Feet Up Talk Python Courses Links from the show Charlie Marsh on Twitter : @charliermarsh Charlie Marsh on Mastodon : @charliermarsh Astral Homepage : astral.sh Pyx Project : astral.sh Introducing Pyx Blog Post : astral.sh uv Package on GitHub : github.com UV Star History Chart : star-history.com Watch this episode on YouTube : youtube.com Episode #520 deep-dive : talkpython.fm/520 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

Sep 18

#519: Data Science Cloud Lessons at Scale

Today on Talk Python: What really happens when your data work outgrows your laptop. Matthew Rocklin, creator of Dask and cofounder of Coiled, and Nat Tabris a staff software engineer at Coiled join me to unpack the messy truth of cloud-scale Python. During the episode we actually spin up a 1,000 core cluster from a notebook, twice! We also discuss picking between pandas and Polars, when GPUs help, and how to avoid surprise bills. Real lessons, real tradeoffs, shared by people who have built this stuff. Stick around. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Talk Python Courses Links from the show Matthew Rocklin : @mrocklin Nat Tabris : tabris.us Dask : dask.org Coiled : coiled.io Watch this episode on YouTube : youtube.com Episode #519 deep-dive : talkpython.fm/519 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

Aug 29

#518: Celebrating Django's 20th Birthday With Its Creators

Twenty years after a scrappy newsroom team hacked together a framework to ship stories fast, Django remains the Python web framework that ships real apps, responsibly. In this anniversary roundtable with its creators and long-time stewards: Simon Willison, Adrian Holovaty, Will Vincent, Jeff Triplett, and Thibaud Colas, we trace the path from the Lawrence Journal-World to 1.0, DjangoCon, and the DSF; unpack how a BSD license and a culture of docs, tests, and mentorship grew a global community; and revisit lessons from deployments like Instagram. We talk modern Django too: ASGI and async, HTMX-friendly patterns, building APIs with DRF and Django Ninja, and how Django pairs with React and serverless without losing its batteries-included soul. You’ll hear about Django Girls, Djangonauts, and the Django Fellowship that keep momentum going, plus where Django fits in today’s AI stacks. Finally, we look ahead at the next decade of speed, security, and sustainability. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Sentry AI Monitoring, Code TALKPYTHON Talk Python Courses Links from the show Guests Simon Willison : simonwillison.net Adrian Holovaty : holovaty.com Will Vincent : wsvincent.com Jeff Triplett : jefftriplett.com Thibaud Colas : thib.me Show Links Django's 20th Birthday Reflections (Simon Willison) : simonwillison.net Happy 20th Birthday, Django! (Django Weblog) : djangoproject.com Django 2024 Annual Impact Report : djangoproject.com Welcome Our New Fellow: Jacob Tyler Walls : djangoproject.com Soundslice Music Learning Platform : soundslice.com Djangonaut Space Mentorship for Django Contributors : djangonaut.space Wagtail CMS for Django : wagtail.org Django REST Framework : django-rest-framework.org Django Ninja API Framework for Django : django-ninja.dev Lawrence Journal-World : ljworld.com Watch this episode on YouTube : youtube.com Episode #518 deep-dive : talkpython.fm/518 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

Aug 22

#517: Agentic Al Programming with Python

Agentic AI programming is what happens when coding assistants stop acting like autocomplete and start collaborating on real work. In this episode, we cut through the hype and incentives to define “agentic,” then get hands-on with how tools like Cursor, Claude Code, and LangChain actually behave inside an established codebase. Our guest, Matt Makai, now VP of Developer Relations at DigitalOcean, creator of Full Stack Python and Plushcap, shares hard-won tactics. We unpack what breaks, from brittle “generate a bunch of tests” requests to agents amplifying technical debt and uneven design patterns. Plus, we also discuss a sane git workflow for AI-sized diffs. You’ll hear practical Claude tips, why developers write more bugs when typing less, and where open source agents are headed. Hint: The destination is humans as editors of systems, not just typists of code. Episode sponsors Posit Talk Python Courses Links from the show Matt Makai : linkedin.com Plushcap Developer Content Analytics : plushcap.com DigitalOcean Gradient AI Platform : digitalocean.com DigitalOcean YouTube Channel : youtube.com Why Generative AI Coding Tools and Agents Do Not Work for Me : blog.miguelgrinberg.com AI Changes Everything : lucumr.pocoo.org Claude Code - 47 Pro Tips in 9 Minutes : youtube.com Cursor AI Code Editor : cursor.com JetBrains Junie : jetbrains.com Claude Code by Anthropic : anthropic.com Full Stack Python : fullstackpython.com Watch this episode on YouTube : youtube.com Episode #517 deep-dive : talkpython.fm/517 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

Aug 19

#516: Accelerating Python Data Science at NVIDIA

Python’s data stack is getting a serious GPU turbo boost. In this episode, Ben Zaitlen from NVIDIA joins us to unpack RAPIDS, the open source toolkit that lets pandas, scikit-learn, Spark, Polars, and even NetworkX execute on GPUs. We trace the project’s origin and why NVIDIA built it in the open, then dig into the pieces that matter in practice: cuDF for DataFrames, cuML for ML, cuGraph for graphs, cuXfilter for dashboards, and friends like cuSpatial and cuSignal. We talk real speedups, how the pandas accelerator works without a rewrite, and what becomes possible when jobs that used to take hours finish in minutes. You’ll hear strategies for datasets bigger than GPU memory, scaling out with Dask or Ray, Spark acceleration, and the growing role of vector search with cuVS for AI workloads. If you know the CPU tools, this is your on-ramp to the same APIs at GPU speed. Episode sponsors Posit Talk Python Courses Links from the show RAPIDS : github.com/rapidsai Example notebooks showing drop-in accelerators : github.com Benjamin Zaitlen - LinkedIn : linkedin.com RAPIDS Deployment Guide (Stable) : docs.rapids.ai RAPIDS cuDF API Docs (Stable) : docs.rapids.ai Asianometry YouTube Video : youtube.com cuDF pandas Accelerator (Stable) : docs.rapids.ai Watch this episode on YouTube : youtube.com Episode #516 deep-dive : talkpython.fm/516 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

Aug 11

#515: Durable Python Execution with Temporal

What if your code was crash-proof? That's the value prop for a framework called Temporal. Temporal is a durable execution platform that enables developers to build scalable applications without sacrificing productivity or reliability. The Temporal server executes units of application logic called Workflows in a resilient manner that automatically handles intermittent failures, and retries failed operations. We have Mason Egger from Temporal on to dive into durable execution. Episode sponsors Posit PyBay Talk Python Courses Links from the show Just Enough Python for Data Scientists Course : talkpython.fm Temporal Durable Execution Platform : temporal.io Temporal Learn Portal : learn.temporal.io Temporal GitHub Repository : github.com Temporal Python SDK GitHub Repository : github.com What Is Durable Execution, Temporal Blog : temporal.io Mason on Bluesky Profile : bsky.app Mason on Mastodon Profile : fosstodon.org Mason on Twitter Profile : twitter.com Mason on LinkedIn Profile : linkedin.com X Post by @skirano : x.com Temporal Docker Compose GitHub Repository : github.com Building a distributed asyncio event loop (Chad Retz) - PyTexas 2025 : youtube.com Watch this episode on YouTube : youtube.com Episode #515 deep-dive : talkpython.fm/515 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

Jul 18

#514: Python Language Summit 2025

Every year the core developers of Python convene in person to focus on high priority topics for CPython and beyond. This year they met at PyCon US 2025. Those meetings are closed door to keep focused and productive. But we're lucky that Seth Michael Larson was in attendance and wrote up each topic presented and the reactions and feedback to each. We'll be exploring this year's Language Summit with Seth. It's quite insightful to where Python is going and the pressing matters. Episode sponsors Seer: AI Debugging, Code TALKPYTHON Sentry AI Monitoring, Code TALKPYTHON Talk Python Courses Links from the show Seth on Mastodon : @sethmlarson@fosstodon.org Seth on Twitter : @sethmlarson Seth on Github : github.com Python Language Summit 2025 : pyfound.blogspot.com WheelNext : wheelnext.dev Free-Threaded Wheels : hugovk.github.io Free-Threaded Python Compatibility Tracking : py-free-threading.github.io PEP 779: Criteria for supported status for free-threaded Python : discuss.python.org PyPI Data : py-code.org Senior Engineer tries Vibe Coding : youtube.com Watch this episode on YouTube : youtube.com Episode #514 deep-dive : talkpython.fm/514 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

Jul 14

#513: Stories from Python History

Why do people listen to this podcast? Sure, they're looking for technical explorations of new libraries and ideas. But often it's to hear the story behind them. If that speaks to you, then I have the perfect episode lined up. I have Barry Warsaw, Paul Everitt, Carol Willing, and Brett Cannon all back on the show to share stories from the history of Python. You'll hear about how import this came to be and how the first PyCon had around 30 attendees (two of whom are guests on this episode!). Sit back and enjoy the humorous stories from Python's past. Episode sponsors Posit Agntcy Talk Python Courses Links from the show Barry's Zen of Python song : youtube.com Jake Vanderplas - Keynote - PyCon 2017 : youtube.com Why it’s called “Python” (Monty Python fan-reference) : geeksforgeeks.org import antigravity : python-history.blogspot.com NIST Python Workshop Attendees : legacy.python.org Paul Everitt open-sources Zope : old.zope.dev Carol Willing wins ACM Software System Award : awards.acm.org Watch this episode on YouTube : youtube.com Episode #513 deep-dive : talkpython.fm/513 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

Jul 2

#512: Building a JIT Compiler for CPython

Do you like to dive into the details and intricacies of how Python executes and how we can optimize it? Well, do I have an episode for you. We welcome back Brandt Bucher to give us an update on the upcoming JIT compiler for Python and why it differs from JITs for languages such as C# and Java. Episode sponsors Posit Talk Python Courses Links from the show Brandt Bucher : github.com/brandtbucher PyCon Talk: What they don't tell you about building a JIT compiler for CPython : youtube.com Specializing, Adaptive Interpreter Episode : talkpython.fm Watch this episode on YouTube : youtube.com Episode #512 deep-dive : talkpython.fm/512 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

Jun 25

#511: From Notebooks to Production Data Science Systems

If you're doing data science and have mostly spent your time doing exploratory or just local development, this could be the episode for you. We are joined by Catherine Nelson to discuss techniques and tools to move your data science game from local notebooks to full-on production workflows. Episode sponsors Agntcy Sentry Error Monitoring, Code TALKPYTHON Talk Python Courses Links from the show New Course: LLM Building Blocks for Python : training.talkpython.fm Catherine Nelson LinkedIn Profile : linkedin.com Catherine Nelson Bluesky Profile : bsky.app Enter to win the book : forms.google.com Going From Notebooks to Scalable Systems - PyCon US 2025 : us.pycon.org Going From Notebooks to Scalable Systems - Catherine Nelson – YouTube : youtube.com From Notebooks to Scalable Systems Code Repository : github.com Building Machine Learning Pipelines Book : oreilly.com Software Engineering for Data Scientists Book : oreilly.com Jupytext - Jupyter Notebooks as Markdown Documents : github.com Jupyter nbconvert - Notebook Conversion Tool : github.com Awesome MLOps - Curated List : github.com Watch this episode on YouTube : youtube.com Episode #511 deep-dive : talkpython.fm/511 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

Jun 18

#531: Talk Python in Production

#530: anywidget: Jupyter Widgets made easy

#529: Computer Science from Scratch

#528: Python apps with LLM building blocks

#527: MCP Servers for Python Devs

#526: Building Data Science with Foundation LLM Models

#525: NiceGUI Goes 3.0

#524: 38 things Python developers should learn in 2025

#523: Pyrefly: Fast, IDE-friendly typing for Python

#522: Data Sci Tips and Tricks from CodeCut.ai

#521: Red Teaming LLMs and GenAI with PyRIT

#520: pyx - the other side of the uv coin (announcing pyx)

#519: Data Science Cloud Lessons at Scale

#518: Celebrating Django's 20th Birthday With Its Creators

#517: Agentic Al Programming with Python

#516: Accelerating Python Data Science at NVIDIA

#515: Durable Python Execution with Temporal

#514: Python Language Summit 2025

#513: Stories from Python History

#512: Building a JIT Compiler for CPython

#511: From Notebooks to Production Data Science Systems

#510: 10 Polars Tools and Techniques To Level Up Your Data Science

#509: GPU Programming in Pure Python

#508: Program Your Own Computer with Python

#507: Agentic AI Workflows with LangGraph

#506: ty: Astral's New Type Checker (Formerly Red-Knot)

#505: t-strings in Python (PEP 750)

#504: Developer Trends in 2025

#503: The PyArrow Revolution

#502: Django Ledger: Accounting with Python

#501: Marimo - Reactive Notebooks for Python

#500: Django Simple Deploy and other DevOps Things

#499: BeeWare and the State of Python on Mobile

#498: Algorithms for high performance terminal apps

#497: Outlier Detection with Python

#496: Scaf: Complete blueprint for new Python Kubernetes projects

#495: OSMnx: Python and OpenStreetMap

#494: Update on Flet: Python + Flutter UIs

#493: Quarto: Open-source technical publishing

#492: Great Tables

#491: DuckDB and Python: Ducks and Snakes living together

#490: Django Ninja

#489: Anaconda Toolbox for Excel and more with Peter Wang

#488: Multimodal data with LanceDB

#487: Building Rust Extensions for Python

#486: CSnakes: Embed Python code in .NET

#485: Secure coding for Python with SheHacksPurple

#484: From React to a Django+HTMX based stack

#483: Reflex Framework: Frontend, Backend, Pure Python

#482: Pre-commit Hooks for Python Devs

#481: Python Opinions and Zeitgeist with Hynek

#480: Ahoy, Narwhals are bridging the data science APIs

#479: Designing Effective Load Tests for Your Python App

#478: When and how to start coding with kids

#477: Awesome Text Tricks with NLP and spaCy

#476: Unified Python packaging with uv

#475: Python Language Summit 2024

#474: Python Performance for Data Science

#473: Being a developer with ADHD

#472: State of Flask and Pallets in 2024

#471: Learning and teaching Pandas

#470: Python in Medicine and Patient Care

#469: PuePy: Reactive frontend framework in Python

#468: Python Trends Episode 2024

#467: Data Science Panel at PyCon 2024

#466: Pydantic Performance Tips

#465: The AI Revolution Won't Be Monopolized

#464: Seeing code flows and generating tests with Kolo

#463: Running on Rust: Granian Web Server

#462: Pandas and Beyond with Wes McKinney

#461: Python in Neuroscience and Academic Labs

#460: Dropbase: Build Internal Tools with Python

#459: I Built A Python SaaS with AI

#458: Serverless Python in 2024

#457: Software Supply Chain Security with Phylum

#456: Building GPT Actions with FastAPI and Pydantic

#455: Land Your First Data Job

#454: Data Pipelines with Dagster

#453: uv - The Next Evolution in Python Packages?