Episodios

  • #526: Building Data Science with Foundation LLM Models

    #526: Building Data Science with Foundation LLM Models
    Nov 1 2025
    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
    Más Menos
    1 h y 7 m
  • #525: NiceGUI Goes 3.0

    #525: NiceGUI Goes 3.0
    Oct 27 2025
    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
    Más Menos
    1 h y 18 m
  • #524: 38 things Python developers should learn in 2025

    #524: 38 things Python developers should learn in 2025
    Oct 20 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
    Más Menos
    1 h y 9 m
  • #523: Pyrefly: Fast, IDE-friendly typing for Python

    #523: Pyrefly: Fast, IDE-friendly typing for Python
    Oct 13 2025
    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
    Más Menos
    1 h y 7 m
  • #522: Data Sci Tips and Tricks from CodeCut.ai

    #522: Data Sci Tips and Tricks from CodeCut.ai
    Oct 6 2025
    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
    Más Menos
    1 h y 10 m
  • #521: Red Teaming LLMs and GenAI with PyRIT

    #521: Red Teaming LLMs and GenAI with PyRIT
    Sep 29 2025
    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
    Más Menos
    1 h y 3 m
  • #520: pyx - the other side of the uv coin (announcing pyx)

    #520: pyx - the other side of the uv coin (announcing pyx)
    Sep 23 2025
    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
    Más Menos
    1 h
  • #519: Data Science Cloud Lessons at Scale

    #519: Data Science Cloud Lessons at Scale
    Sep 18 2025
    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
    Más Menos
    1 h y 3 m