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Descubre un mundo infinito de historias

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Michael Kennedy

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

Talk Python To Me

Your cloud SSD is sitting there, bored, and it would like a job. Today we’re putting it to work with DiskCache, a simple, practical cache built on SQLite that can speed things up without spinning up Redis or extra services. Once you start to see what it can do, a universe of possibilities opens up. We're joined by Vincent Warmerdam to dive into DiskCache.

Episode sponsors

Talk Python Courses

Python in Production

Links from the show
diskcache docs: grantjenks.com

LLM Building Blocks for Python course: training.talkpython.fm

JSONDisk: grantjenks.com

Git Code Archaeology Charts: koaning.github.io

Talk Python Cache Admin UI: blobs.talkpython.fm

Litestream SQLite streaming: litestream.io

Plash hosting: pla.sh

Watch this episode on YouTube: youtube.com

Episode #534 deep-dive: talkpython.fm/534

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

#534: diskcache: Your secret Python perf weapon

Today on Talk Python, the creators behind FastAPI, Flask, Django, Quart, and Litestar get practical about running apps based on their framework in production. Deployment patterns, async gotchas, servers, scaling, and the stuff you only learn at 2 a.m. when the pager goes off. For Django, we have Carlton Gibson and Jeff Triplet. For Flask, we have David Lord and Phil Jones, and on team Litestar we have Janek Nouvertné and Cody Fincher, and finally Sebastián Ramírez from FastAPI is here. Let’s jump in.

Episode sponsors

Talk Python Courses

Python in Production

Links from the show
Carlton Gibson - Django: github.com

Sebastian Ramirez - FastAPI: github.com

David Lord - Flask: davidism.com

Phil Jones - Flask and Quartz(async): pgjones.dev

Yanik Nouvertne - LiteStar: github.com

Cody Fincher - LiteStar: github.com

Jeff Triplett - Django: jefftriplett.com

Django: www.djangoproject.com

Flask: flask.palletsprojects.com

Quart: quart.palletsprojects.com

Litestar: litestar.dev

FastAPI: fastapi.tiangolo.com

Coolify: coolify.io

ASGI: asgi.readthedocs.io

WSGI (PEP 3333): peps.python.org

Granian: github.com

Hypercorn: github.com

uvicorn: uvicorn.dev

Gunicorn: gunicorn.org

Hypercorn: hypercorn.readthedocs.io

Daphne: github.com

Nginx: nginx.org

Docker: www.docker.com

Kubernetes: kubernetes.io

PostgreSQL: www.postgresql.org

SQLite: www.sqlite.org

Celery: docs.celeryq.dev

SQLAlchemy: www.sqlalchemy.org

Django REST framework: www.django-rest-framework.org

Jinja: jinja.palletsprojects.com

Click: click.palletsprojects.com

HTMX: htmx.org

Server-Sent Events (SSE): developer.mozilla.org

WebSockets (RFC 6455): www.rfc-editor.org

HTTP/2 (RFC 9113): www.rfc-editor.org

HTTP/3 (RFC 9114): www.rfc-editor.org

uv: docs.astral.sh

Amazon Web Services (AWS): aws.amazon.com

Microsoft Azure: azure.microsoft.com

Google Cloud Run: cloud.google.com

Amazon ECS: aws.amazon.com

AlloyDB for PostgreSQL: cloud.google.com

Fly.io: fly.io

Render: render.com

Cloudflare: www.cloudflare.com

Fastly: www.fastly.com

Watch this episode on YouTube: youtube.com

Episode #533 deep-dive: talkpython.fm/533

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

#533: Web Frameworks in Prod by Their Creators

Python in 2025 is in a delightfully refreshing place: the GIL's days are numbered, packaging is getting sharper tools, and the type checkers are multiplying like gremlins snacking after midnight. On this episode, we have an amazing panel to give us a range of perspectives on what matter in 2025 in Python. We have Barry Warsaw, Brett Cannon, Gregory Kapfhammer, Jodie Burchell, Reuven Lerner, and Thomas Wouters on to give us their thoughts.

Episode sponsors

Seer: AI Debugging, Code TALKPYTHON

Talk Python Courses

Links from the show
Python Software Foundation (PSF): www.python.org

PEP 810: Explicit lazy imports: peps.python.org

PEP 779: Free-threaded Python is officially supported: peps.python.org

PEP 723: Inline script metadata: peps.python.org

PyCharm: www.jetbrains.com

JetBrains: www.jetbrains.com

Visual Studio Code: code.visualstudio.com

pandas: pandas.pydata.org

PydanticAI: ai.pydantic.dev

OpenAI API docs: platform.openai.com

uv: docs.astral.sh

Hatch: github.com

PDM: pdm-project.org

Poetry: python-poetry.org

Project Jupyter: jupyter.org

JupyterLite: jupyterlite.readthedocs.io

PEP 690: Lazy Imports: peps.python.org

PyTorch: pytorch.org

Python concurrent.futures: docs.python.org

Python Package Index (PyPI): pypi.org

EuroPython: tickets.europython.eu

TensorFlow: www.tensorflow.org

Keras: keras.io

PyCon US: us.pycon.org

NumFOCUS: numfocus.org

Python discussion forum (discuss.python.org): discuss.python.org

Language Server Protocol: microsoft.github.io

mypy: mypy-lang.org

Pyright: github.com

Pylance: marketplace.visualstudio.com

Pyrefly: github.com

ty: github.com

Zuban: docs.zubanls.com

Jedi: jedi.readthedocs.io

GitHub: github.com

PyOhio: www.pyohio.org

Watch this episode on YouTube: youtube.com

Episode #532 deep-dive: talkpython.fm/532

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

#532: 2025 Python Year in Review

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

#531: Talk Python in Production

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

#530: anywidget: Jupyter Widgets made easy

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

#529: Computer Science from Scratch

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

#528: Python apps with LLM building blocks

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

#527: MCP Servers for Python Devs

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

#526: Building Data Science with Foundation LLM Models

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

#525: NiceGUI Goes 3.0

See the full show notes for this episode on the website at talkpython.fm/381

#381: Python Perf: Specializing, Adaptive Interpreter

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