Talk Python To Me - Python Conversations For Passionate Developers

In this episode, I'm joined by JJ Allaire, founder and executive chairman at Posit, and Carlos Scheidegger, a software engineer at Posit, to explore Quarto, an open-source tool revolutionizing technical publishing. We discuss how Quarto empowers users to seamlessly transform Jupyter notebooks into polished reports, dashboards, e-books, websites, and more. JJ shares his journey from creating RStudio to developing Quarto as a versatile, multi-language tool, while Carlos delves into its roots in reproducibility and the challenges of academic publishing. Don't miss this deep dive into a tool that's shaping the future of data-driven storytelling! Episode sponsors Talk Python Courses DigitalOcean Links from the show JJ Allaire JJ on LinkedIn: linkedin.com JJ on GitHub: github.com Carlos Scheidegger Personal site: cscheid.net Mastodon: @scheidegger Fast AI: fast.ai nbdev: nbdev.fast.ai nbsanity - Share Notebooks as Polished Web Pages in Seconds: answer.ai Pandoc: pandoc.org Observable: github.com Quarto Pub: qu

Join me as I chat with Rich Iannone and Michael Chow from Posit where we explore the transformative power of data tables with the Great Tables library. We'll cover practical applications of Great Tables, showcasing how thoughtful design and advanced formatting can elevate your data presentations. And you'll learn about innovative features like nano plots and interactive elements and the importance of structure, format, and style in crafting tables that both inform and inspire. Whether you're a seasoned data scientist or just starting out, this episode is packed with valuable tips and inspiring examples to enhance your data storytelling. Episode sponsors Talk Python Courses DigitalOcean Links from the show Michael Chow: github.com/machow Richard Iannone: github.com/rich-iannone Episode Deep Dives Writeup: talkpython.fm/blog Great Tables: github.com Making Beautiful, Publication Quality Tables PyCon talk: youtube.com Andrew Weatherman's Visualization Gallery: aweatherman.com Bureau of the Census Manual of

Join me for an insightful conversation with Alex Monahan, who works on documentation, tutorials, and training at DuckDB Labs. We explore why DuckDB is gaining momentum among Python and data enthusiasts, from its in-process database design to its blazingly fast, columnar architecture. We also dive into indexing strategies, concurrency considerations, and the fascinating way MotherDuck (the cloud companion to DuckDB) handles large-scale data seamlessly. Don’t miss this chance to learn how a single pip install could totally transform your Python data workflow! Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Data Citizens Podcast Talk Python Courses Links from the show Alex on Mastodon: @__Alex__ DuckDB: duckdb.org MotherDuck: motherduck.com SQLite: sqlite.org Moka-Py: github.com PostgreSQL: www.postgresql.org MySQL: www.mysql.com Redis: redis.io Apache Parquet: parquet.apache.org Apache Arrow: arrow.apache.org Pandas: pandas.pydata.org Polars: pola.rs Pyodide: pyodide.org DB-API (PEP 249): peps.pyt

If you're a Django developer, I'm sure you've heard so many people raving about FastAPI and Pydantic. But you really love Django and don't want to switch. Then you might want to give Django Ninja a serious look. Django Ninja is highly inspired by FastAPI, but is also deeply integrated into Django itself. We have Vitaliy Kucheryaviy the creator of Django Ninja on this show to tell us all about it. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Bluehost Talk Python Courses Links from the show Vitaly: github.com/vitalik Vitaly on X: @vital1k Top 5 Episodes of 2024: talkpython.fm/blog/posts/top-talk-python-podcast-episodes-of-2024 Django Ninja: django-ninja.dev Motivation section we talked through: django-ninja.dev/motivation LLM for Django Ninja: llm.django-ninja.dev Nano Django: github.com/vitalik/nano-django Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon

Peter Wang has been pushing Python forward since the early days of its data science roots. We're lucky to have him back on the show. We're going to talk about the Anaconda Toolbox for Excel as well as many other trends and topics that are hot in the Python space right now. I'm sure you'll enjoy listening to the two of us exchanging our takes on the topics and trends. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Bluehost Talk Python Courses Links from the show Peter on BSky: @wang.social Michael on BSky: @mkennedy.codes Michael's Curated BSky Starter List: bsky.app Python Blsky Starter Pack List: blueskydirectory.com Anaconda Toolbox for Microsoft Excel: anaconda.com JupyterLite: jupyter.org 8 of the Biggest Excel Mistakes of All Time: blog.hurree.co The Five Demons of Python Packaging PyBay talk: youtube.com PEP 759: peps.python.org TIOBE Index: tiobe.com pyscript: pyscript.net Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscr

LanceDB is a developer-friendly, open source database for AI. It's used by well-known companies such as Midjourney and Character.ai. We have Chang She, the CEO and cofounder of LanceDB on to give us a look at the concept of multi-modal data and how you can use LanceDB in your own Python apps. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Bluehost Talk Python Courses Links from the show Chang She: @changhiskhan Chang on Github: github.com LanceDB: lancedb.com LanceDB Source: github.com Embeddings API: github.com MinIO: min.io LanceDB Quickstart: github.com VectorDB-recipes: github.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

There has been a lot of changes in the low-level Python space these days. The biggest has to be how many projects have rewritten core performance-intensive sections in Rust. Or even the wholesale adoption of Rust for newer projects such as uv and ruff. On this episode, we dive into the tools and workflow needed to build these portions of Python apps in Rust with David Seddon and Samuel Colvin. Episode sponsors Posit Data Citizens Podcast Talk Python Courses Links from the show Samuel Colvin: github.com/samuelcolvin David Seddon: github.com/seddonym David's blog: seddonym.me Pydantic: pydantic.dev PEP 0759: peps.python.org TypeShed: github.com Maturin: maturin.rs rloop: github.com Install Rust: rust-lang.org Py03: pyo3.rs The Rust Programming Language (book): https://doc.rust-lang.org/book/ Grimp: github.com Grimp Workflows: github.com White House recommends memory safe languages: whitehouse.gov Installing Rust: rust-lang.org jiter: github.com import-linter: github.com Logfire: pydantic.dev Crabs in Snake

If you are a .NET developer or work in a place that has some of those folks, wouldn't it be great to fully leverage the entirety of PyPI with it's almost 600,000 packages inside your .NET code? But how would you do this? Previous efforts have let you write Python syntax but using the full libraries (especially the C-based ones) has been out of reach, until CSnakes. This project by Anthony Shaw and Aaron Powell unlocks some pretty serious integration between the two languages. We have them both here on the show today to tell us all about it. Episode sponsors Posit Bluehost Talk Python Courses Links from the show Anthony Shaw: github.com Aaron Powell: github.com Introducing CSnakes: tonybaloney.github.io CSnakes: tonybaloney.github.io Talk Python: We've moved to Hetzner: talkpython.fm/blog Talk Python: Talk Python rewritten in Quart (async Flask): talkpython.fm/blog Pyjion - A JIT for Python based upon CoreCLR: github.com Iron Python: ironpython.net Python.NET: pythonnet.github.io The buffer protocol: do

What do developers need to know about AppSec and building secure software? We have Tonya Janca (AKA SheHacksPurple) on the show to tell us all about it. We talk about what developers should expect from threat modeling events as well as concrete tips for security your apps and services. Episode sponsors Posit Bluehost Talk Python Courses Links from the show Tanya on X: @shehackspurple She Hacks Purple website: shehackspurple.ca White House recommends memory safe languages: whitehouse.gov Python Developer Survey Results: jetbrains.com Bandit: github.com Semgrep Academy: academy.semgrep.dev Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Have you heard about HTMX? We've discussed it a time or two on this show. We're back with another episode on HTMX, this time with a real-world success story and lessons learned. We have Sheena O'Connell on to tell us how she moved from a React-Django app to pure Django with HTMX. Episode sponsors Posit Bluehost Talk Python Courses Links from the show Sheena O'Connell: sheenaoc.com An HTMX success story essay: sheenaoc.com Sheena's HTMX Workshop: prelude.tech - discount code: talk_python Talk Python's HTMX Courses HTMX + Flask course: training.talkpython.fm HTMX + Django course: training.talkpython.fm Build An Audio AI App course: training.talkpython.fm HTMX: htmx.org Playwright: playwright.dev django-template-partials: github.com Michael's jinja_partials: github.com django-guardian: github.com Talk Python Courses HTMX Example: training.talkpython.fm/courses/all Alpine.js: alpinejs.dev David Guillot SaaS video: youtube.com awesome-htmx: github.com Guild of Educators: guildofeducators.org The big rewrite

Let's say you want to create a web app and you know Python really well. Your first thought might be Flask or Django or even FastAPI? All good choices but there is a lot to get a full web app into production. The framework we'll talk about today, Reflex, allows you to just write Python code and it turns it into a full web app running FastAPI, NextJS, React and more plus it handles the deployment for you. It's a cool idea. Let's talk to Elvis Kahoro and Nikhil Rao from Reflex.dev. Episode sponsors Posit Bluehost Talk Python Courses Links from the show Elvis: github.com Nikhil: github.com Reflex Framework: reflex.dev Reflex source: github.com Reflex docs: reflex.dev Reflex Roadmap: github.com AG Grid: ag-grid.com Warp terminal: warp.dev A Stroll Down Startup Lane episode: talkpython.fm PuePy: Reactive frontend framework in Python episode: talkpython.fm Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow

Do you struggle to make sure your code is always correct before you check it in? What about your team members' code? That one person who never wants to run the linter? Tired of dealing with tons of conflicts and spurious git changes? You need git pre-commit hooks. We're lucky to have Stefanie Molin on this episode who has done a bunch of writing and teaching of git hooks. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Bluehost Talk Python Courses Links from the show Stefanie Molin: stefaniemolin.com Talk Python Blog: talkpython.fm/blog How to Set Up Pre-Commit Hooks: stefaniemolin.com Common Pre-Commit Errors and How to Solve Them: stefaniemolin.com A Behind-the-Scenes Look at How Pre-Commit Works: stefaniemolin.com Pre-Commit Hook Creation Guide: stefaniemolin.com (Pre-)Commit to Better Code Workshop: stefaniemolin.com exif-stripper: stefaniemolin.com exif-stripper on GitHub: github.com docstring-validation-using-pre-commit-hook: numpydoc.readthedocs.io Data Morph: Moving Beyond the Datasaur

Hynek has been writing and speaking on some of the most significant topics in the Python space and I've enjoyed his takes. So I invited him on the show to share them with all of us. This episode really epitomizes one of the reasons I launched Talk Python 9 years ago. It's as if we run into each other at a bar during a conference and I ask Hynek, "So what are your thoughts on ..." and we dive down the rabbit hole for an hour. I hope you enjoy it. Episode sponsors WorkOS Bluehost Talk Python Courses Links from the show Hynek Schlawack on Mastodon: @hynek Why I Still Use Python Virtual Environments in Docker: hynek.me Production-ready Python Docker Containers with uv: hynek.me Attrs: github.com uv: astral.sh What’s New In Python 4: python.org BusyBox: busybox.net Hynek's YouTube Channel: youtube.com MOPUp for macOS: github.com Homebrew Python Is Not For You: justinmayer.com argon2-cffi: Argon2 for Python: github.com pytest-freethreaded: github.com LM Studio: lmstudio.ai StackOverflow Trends Graph: trends.st

If you work in data science, you definitely know about data frame libraries. Pandas is certainly the most popular, but there are others such as cuDF, Modin, Polars, Dask, and more. They are all similar but definitely not the same APIs and Polars is quite different. But here's the problem. If you want to write a library that is for users of more than one of these data frame frameworks, how do you do that? Or if you want to leave open the possibility of changing yours after the app is built, same problem. That's the problem that Narwhals solves. We have Marco Gorelli on the show to tell us all about it. Episode sponsors WorkOS Talk Python Courses Links from the show Marco Gorelli: @marcogorelli Marco on LinkedIn: linkedin.com Narwhals: github.io Narwhals on Github: github.com DuckDB: duckdb.org Ibis: ibis-project.org modin: readthedocs.io Pandas and Beyond with Wes McKinney: talkpython.fm Polars: A Lightning-fast DataFrame for Python: talkpython.fm Polars: pola.rs Pandas: pandas.pydata.org Watch this epis

You're about to launch your new app or API, or even just a big refactor of your current project. Will it stand up and deliver when you put it into production or when that big promotion goes live? Or will it wither and collapse? How would you know? Well you would test that of course. We have Anthony Shaw back on the podcast to dive into a wide range of tools and techniques for performance and loading testing of web apps. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON WorkOS Talk Python Courses Links from the show Anthony on Twitter: @anthonypjshaw Anthony's PyCon Au Talk: youtube.com locust load testing tool: locust.io playwright: playwright.dev mimesis: github.com mimesis providers: mimesis.name vscode pets: marketplace.visualstudio.com vscode power-mode: marketplace.visualstudio.com opentelemetry: opentelemetry.io uptime-kuma: github.com Talk Python uptime / status: talkpython.fm/status when your serverless computing bill goes parabolic...: youtube.com Watch this episode on YouTube: youtube.co

Do you have kids? Maybe nieces and nephews? Or maybe you work in a school environment? Maybe it's just friend's who know you're a programmer and ask about how they should go about introducing programming concepts with them. Anna-Lena Popkes is back on the show to share her research on when and how to teach kids programming. We spend the second half of the episode talking about concrete apps and toys you might consider for each age group. Plus, some of these things are fun for adults too. ;) Episode sponsors WorkOS Talk Python Courses Links from the show Anna-Lena: alpopkes.com Magical universe repo: github.com Machine learning basics repo: github.com PyData recording "when and how to start coding with kids": youtube.com Robots and devices Bee Bot: terrapinlogo.com Cubelets: modrobotics.com BBC Microbit: microbit.org RaspberryPi: raspberrypi.com Adafruit Qualia ESP32 for CircuitPython: adafruit.com Zumi: robolink.com Board games Think Fun Robot Turtles Board Game: amazon.com Visual programming: Scratc

Do you have text that you want to process automatically? Maybe you want to pull out key products or topics of conversation? Maybe you want to get the sentiment? The possibilities are many with this week's topic: NLP with spaCy and Python. Our guest, Vincent D. Warmerdam, has worked on spaCy and other tools at Explosion AI and he's here to give us his tips and tricks for working with text from Python. Episode sponsors Posit Talk Python Courses Links from the show Course: Getting Started with NLP and spaCy: talkpython.fm Vincent on X: @fishnets88 Vincent on Mastodon: @koaning Programmable Keyboards on CalmCode: youtube.com Sample Space Podcast: youtube.com spaCy: spacy.io Course: Build An Audio AI App: talkpython.fm Lemma example: github.com Code for spaCy course: github.com Python Bytes transcripts: github.com scikit-lego: github.com Projects that import "this": calmcode.io Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on Yo

A couple of weeks ago, Charlie Marsh and the folks at Astral made another big splash with a major release of uv called "uv: Unified Python packaging" which has many far reaching features. We had to have Charlie on the show to give us the inside look into this development. Let's get to it. Episode sponsors Posit Talk Python Courses Links from the show Charlie Marsh on Twitter: @charliermarsh Charlie Marsh on Mastodon: @charliermarsh Episode follow up: Wrote up how we use uv at Talk Python: mkennedy.codes uv: Unified Python packaging: astral.sh Python executable management: astral.sh Projects: astral.sh Tools: astral.sh Scripts: astral.sh Rye and uv: August is Harvest Season for Python Packaging: lucumr.pocoo.org Python Build Standalone releases: github.com Rules: astral.sh Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Every year the core developers meet to discuss and propose the major changes and trends in Python itself. This invite-only conference of about 50 people happens inside PyCon in the US. Because it's private, we rarely get detailed looks inside this event. On this episode, we have Seth Michael Larson here to give us his account of the sessions and proposals. It's a unique look into the zeitgeist of CPython. Episode sponsors Posit Talk Python Courses Links from the show Seth on Mastodon: @sethmlarson@fosstodon.org Seth on Twitter: @sethmlarson Seth on Github: github.com The Python Language Summit 2024: blogspot.com PEP 2026: Calendar versioning for Python: github.com PSF authorized as a CVE Numbering Authority: python.org Recommends Memory-Safe Programming Languages: blogspot.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Python performance has come a long way in recent times. And it's often the data scientists, with their computational algorithms and large quantities of data, who care the most about this form of performance. It's great to have Stan Seibert back on the show to talk about Python's performance for data scientists. We cover a wide range of tools and techniques that will be valuable for many Python developers and data scientists. Episode sponsors Posit Talk Python Courses Links from the show Stan on Twitter: @seibert Anaconda: anaconda.com High Performance Python with Numba training: learning.anaconda.cloud PEP 0703: peps.python.org Python 3.13 gets a JIT: tonybaloney.github.io Numba: numba.pydata.org LanceDB: lancedb.com Profiling tips: docs.python.org Memray: github.com Fil: a Python memory profiler for data scientists and scientists: pythonspeed.com Rust: rust-lang.org Granian Server: github.com PIXIE at SciPy 2024: github.com Free threading Progress: py-free-threading.github.io Free Threading Compatibility