Podcasts about python2

If you're looking to leverage the insane power of modern GPUs for data science and ML, you might think you'll need to use some low-level programming language such as C++. But the folks over at NVIDIA have been hard at work building Python SDKs which provide nearly native level of performance when doing Pythonic GPU programming. Bryce Adelstein Lelbach is here to tell us about programming your GPU in pure Python. Episode sponsors Posit Agntcy Talk Python Courses Links from the show Bryce Adelstein Lelbach on Twitter: @blelbach Episode Deep Dive write up: talkpython.fm/blog NVIDIA CUDA Python API: github.com Numba (JIT Compiler for Python): numba.pydata.org Applied Data Science Podcast: adspthepodcast.com NVIDIA Accelerated Computing Hub: github.com NVIDIA CUDA Python Math API Documentation: docs.nvidia.com CUDA Cooperative Groups (CCCL): nvidia.github.io Numba CUDA User Guide: nvidia.github.io CUDA Python Core API: nvidia.github.io Numba (JIT Compiler for Python): numba.pydata.org NVIDIA's First Desktop AI PC ($3,000): arstechnica.com Google Colab: colab.research.google.com Compiler Explorer (“Godbolt”): godbolt.org CuPy: github.com RAPIDS User Guide: docs.rapids.ai Watch this episode on YouTube: youtube.com Episode #509 deep-dive: talkpython.fm/509 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

If you've heard the phrase "Automate the boring things" for Python, this episode starts with that idea and takes it to another level. We have Glyph back on the podcast to talk about "Programming YOUR computer with Python." We dive into a bunch of tools and frameworks and especially spend some time on integrating with existing platform APIs (e.g. macOS's BrowserKit and Window's COM APIs) to build desktop apps in Python that make you happier and more productive. Let's dive in! Episode sponsors Posit Agntcy Talk Python Courses Links from the show Glyph on Mastodon: @glyph@mastodon.social Glyph on GitHub: github.com/glyph Glyph's Conference Talk: LceLUPdIzRs: youtube.com Notify Py: ms7m.github.io Rumps: github.com QuickMacHotkey: pypi.org QuickMacApp: pypi.org LM Studio: lmstudio.ai Coolify: coolify.io PyWin32: pypi.org WinRT: pypi.org PyObjC: pypi.org PyObjC Documentation: pyobjc.readthedocs.io Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

If you want to leverage the power of LLMs in your Python apps, you would be wise to consider an agentic framework. Agentic empowers the LLMs to use tools and take further action based on what it has learned at that point. And frameworks provide all the necessary building blocks to weave these into your apps with features like long-term memory and durable resumability. I'm excited to have Sydney Runkle back on the podcast to dive into building Python apps with LangChain and LangGraph. Episode sponsors Posit Auth0 Talk Python Courses Links from the show Sydney Runkle: linkedin.com LangGraph: github.com LangChain: langchain.com LangGraph Studio: github.com LangGraph (Web): langchain.com LangGraph Tutorials Introduction: langchain-ai.github.io How to Think About Agent Frameworks: blog.langchain.dev Human in the Loop Concept: langchain-ai.github.io GPT-4 Prompting Guide: cookbook.openai.com Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

The folks over at Astral have made some big-time impacts in the Python space with uv and ruff. They are back with another amazing project named ty. You may have known it as Red-Knot. But it's coming up on release time for the first version and with the release it comes with a new official name: ty. We have Charlie Marsh and Carl Meyer on the show to tell us all about this new project. Episode sponsors Posit Auth0 Talk Python Courses Links from the show Talk Python's Rock Solid Python: Type Hints & Modern Tools (Pydantic, FastAPI, and More) Course: training.talkpython.fm Charlie Marsh on Twitter: @charliermarsh Charlie Marsh on Mastodon: @charliermarsh Carl Meyer: @carljm ty on Github: github.com/astral-sh/ty A Very Early Play with Astral's Red Knot Static Type Checker: app.daily.dev Will Red Knot be a drop-in replacement for mypy or pyright?: github.com Hacker News Announcement: news.ycombinator.com Early Explorations of Astral's Red Knot Type Checker: pydevtools.com Astral's Blog: astral.sh Rust Analyzer Salsa Docs: docs.rs Ruff Open Issues (label: red-knot): github.com Ruff Types: types.ruff.rs Ruff Docs (Astral): docs.astral.sh uv Repository: github.com Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Python has many string formatting styles which have been added to the language over the years. Early Python used the % operator to injected formatted values into strings. And we have string.format() which offers several powerful styles. Both were verbose and indirect, so f-strings were added in Python 3.6. But these f-strings lacked security features (think little bobby tables) and they manifested as fully-formed strings to runtime code. Today we talk about the next evolution of Python string formatting for advanced use-cases (SQL, HTML, DSLs, etc): t-strings. We have Paul Everitt, David Peck, and Jim Baker on the show to introduce this upcoming new language feature. Episode sponsors Posit Auth0 Talk Python Courses Links from the show Guests: Paul on X: @paulweveritt Paul on Mastodon: @pauleveritt@fosstodon.org Dave Peck on Github: github.com Jim Baker: github.com PEP 750 – Template Strings: peps.python.org tdom - Placeholder for future library on PyPI using PEP 750 t-strings: github.com PEP 750: Tag Strings For Writing Domain-Specific Languages: discuss.python.org How To Teach This: peps.python.org PEP 501 – General purpose template literal strings: peps.python.org Python's new t-strings: davepeck.org PyFormat: Using % and .format() for great good!: pyformat.info flynt: A tool to automatically convert old string literal formatting to f-strings: github.com Examples of using t-strings as defined in PEP 750: github.com htm.py issue: github.com Exploits of a Mom: xkcd.com pyparsing: github.com Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

What trends and technologies should you be paying attention to today? Are there hot new database servers you should check out? Or will that just be a flash in the pan? I love these forward looking episodes and this one is super fun. I've put together an amazing panel: Gina Häußge, Ines Montani, Richard Campbell, and Calvin Hendryx-Parker. We dive into the recent Stack Overflow Developer survey results as a sounding board for our thoughts on rising and falling trends in the Python and broader developer space. Episode sponsors NordLayer Auth0 Talk Python Courses Links from the show The Stack Overflow Survey Results: survey.stackoverflow.co/2024 Panelists Gina Häußge: chaos.social/@foosel Ines Montani: ines.io Richard Campbell: about.me/richard.campbell Calvin Hendryx-Parker: github.com/calvinhp Explosion: explosion.ai spaCy: spacy.io OctoPrint: octoprint.org .NET Rocks: dotnetrocks.com Six Feet Up: sixfeetup.com Stack Overflow: stackoverflow.com Python.org: python.org GitHub Copilot: github.com OpenAI ChatGPT: chat.openai.com Claude: anthropic.com LM Studio: lmstudio.ai Hetzner: hetzner.com Docker: docker.com Aider Chat: github.com Goose AI: goose.ai IndyPy: indypy.org OctoPrint Community Forum: community.octoprint.org spaCy GitHub: github.com Hugging Face: huggingface.co Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Pandas is at a the core of virtually all data science done in Python, that is virtually all data science. Since it's beginning, Pandas has been based upon numpy. But changes are afoot to update those internals and you can now optionally use PyArrow. PyArrow comes with a ton of benefits including it's columnar format which makes answering analytical questions faster, support for a range of high performance file formats, inter-machine data streaming, faster file IO and more. Reuven Lerner is here to give us the low-down on the PyArrow revolution. Episode sponsors NordLayer Auth0 Talk Python Courses Links from the show Reuven: github.com/reuven Apache Arrow: github.com Parquet: parquet.apache.org Feather format: arrow.apache.org Python Workout Book: manning.com Pandas Workout Book: manning.com Pandas: pandas.pydata.org PyArrow CSV docs: arrow.apache.org Future string inference in Pandas: pandas.pydata.org Pandas NA/nullable dtypes: pandas.pydata.org Pandas `.iloc` indexing: pandas.pydata.org DuckDB: duckdb.org Pandas user guide: pandas.pydata.org Pandas GitHub issues: github.com Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Do you or your company need accounting software? Well, there are plenty of SaaS products out there that you can give your data to. but maybe you also really like Django and would rather have a foundation to build your own accounting system exactly as you need for your company or your product. On this episode, we're diving into Django Ledger, created by Miguel Sanda, which can do just that. Episode sponsors Auth0 Talk Python Courses Links from the show Miguel Sanda on Twitter: @elarroba Miguel on Mastodon: @elarroba@fosstodon.org Miguel on GitHub: github.com Django Ledger on Github: github.com Django Ledger Discord: discord.gg Get Started with Django MongoDB Backend: mongodb.com Wagtail CMS: wagtail.org Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Have you ever spent an afternoon wrestling with a Jupyter notebook, hoping that you ran the cells in just the right order, only to realize your outputs were completely out of sync? Today's guest has a fresh take on solving that exact problem. Akshay Agrawal is here to introduce Marimo, a reactive Python notebook that ensures your code and outputs always stay in lockstep. And that's just the start! We'll also dig into Akshay's background at Google Brain and Stanford, what it's like to work on the cutting edge of AI, and how Marimo is uniting the best of data science exploration and real software engineering. Episode sponsors Worth Search Talk Python Courses Links from the show Akshay Agrawal: akshayagrawal.com YouTube: youtube.com Source: github.com Docs: marimo.io Marimo: marimo.io Discord: marimo.io WASM playground: marimo.new Experimental generate notebooks with AI: marimo.app Pluto.jl: plutojl.org Observable JS: observablehq.com Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

We're sitting down with Eric Matthes, the educator, author, and developer behind Django Simple Deploy. If you've ever struggled with taking that final step of getting your Django app onto a live server (without spending days wrestling with DevOps complexities), then give Django Simple Deploy a look. Eric shares how Django Simple Deploy automates away the boilerplate parts of deployment, so you can focus on building features instead of deciphering endless configs. We'll talk about this new project's journey to 1.0, the range of hosting platforms it supports, and why it's not just for beginners. Episode sponsors Worth Search Talk Python Courses Links from the show django-simple-deploy documentation: readthedocs.io django-simple-deploy repository: github.com Python Crash Course book: ehmatthes.github.io Code Red: codered.cloud Docker: docker.com Caddy: caddyserver.com Bunny.net CDN: bunny.net Platform.sh: platform.sh fly.io: fly.io Heroku: heroku.com Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

This episode is all about Beeware, the project that working towards true native apps built on Python, especially for iOS and Android. Russell's been at this for more than a decade, and the progress is now hitting critical mass. We'll talk about the Toga GUI toolkit, building and shipping your apps with Briefcase, the newly official support for iOS and Android in CPython, and so much more. I can't wait to explore how BeeWare opens up the entire mobile ecosystem for Python developers, let's jump right in. Episode sponsors Posit Python in Production Talk Python Courses Links from the show Anaconda open source team: anaconda.com PEP 730 – Adding iOS: peps.python.org PEP 738 – Adding Android: peps.python.org Toga: beeware.org Briefcase: beeware.org emscripten: emscripten.org Russell Keith-Magee - Keynote - PyCon 2019: youtube.com Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

In this episode, we welcome back Will McGugan, the creator of the wildly popular Rich library and founder of Textualize. We'll dive into Will's latest article on "Algorithms for High Performance Terminal Apps" and explore how he's quietly revolutionizing what's possible in the terminal, from smooth animations and dynamic widgets to full-on TUI (or should we say GUI?) frameworks. Whether you're looking to supercharge your command-line tools or just curious how Python can push the limits of text-based UIs, you'll love hearing how Will's taking a modern, web-inspired approach to old-school terminals. Episode sponsors Posit Python in Production Talk Python Courses Links from the show Algorithms for high performance terminal apps post: textual.textualize.io Textual Demo: github.com Textual: textualize.io Zero ver: 0ver.org memray: github.com Posting app: posting.sh Bulma CSS framewokr: bulma.io JP Term: davidbrochart.github.io Rich: github.com btop: github.com starship: starship.rs Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Have you ever wondered why certain data points stand out so dramatically? They might hold the key to everything from fraud detection to groundbreaking discoveries. This week on Talk Python to Me, we dive into the world of outlier detection with Python with Brett Kennedy. You'll learn how outliers can signal errors, highlight novel insights, or even reveal hidden patterns lurking in the data you thought you understood. We'll explore fresh research developments, practical use cases, and how outlier detection compares to other core data science tasks like prediction and clustering. If you're ready to spot those game-changing anomalies in your own projects, stay tuned. Episode sponsors Posit Python in Production Talk Python Courses Links from the show Data-morph: github.com PyOD: github.com Prophet: github.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Today we explore the wild world of Python deployment with my friend, Calvin Hendricks-Parker from Six Feet Up. We'll tackle some of the biggest challenges in taking a Python app from “it works on my machine” to production, covering inconsistent environments, conflicting dependencies, and sneaky security pitfalls. Along the way, Calvin shares how containerization with Docker and Kubernetes can both simplify and complicate deployments, especially for smaller teams. Finally, we'll introduce Scaf, a powerful project blueprint designed to give developers a rock-solid start on Python web projects of all sizes. Get notified when the Talk Python in Production book goes live and read the first third online right now. Episode sponsors Posit Python in Production Talk Python Courses Links from the show Calvin Hendryx-Parker: github.com Scaf on GitHub: github.com Scaf on GitHub (duplicate): github.com "Deploy the Dream" song: deploy-the-dream-talk-python.mp3 CloudDevEngineering YouTube Channel: youtube.com TechWorld with Nana YouTube Channel: youtube.com Tilt (Kubernetes Dev Tool): tilt.dev Talos (Minimal OS for Kubernetes): talos.dev Traefik Reverse Proxy: traefik.io Sealed Secrets on GitHub: github.com Argo CD Documentation: readthedocs.io MailHog on GitHub: github.com Next.js: nextjs.org Cloud Custodian: cloudcustodian.io Valky (Redis Replacement): valkey.io “The ‘Works on My Machine' Certification Program” (Coding Horror): blog.codinghorror.com NVIDIA's First Desktop AI PC (Ars Technica): arstechnica.com Kind (Kubernetes in Docker): kind.sigs.k8s.io Updated Effective PyCharm Course: training.talkpython.fm Talk Python in Production book: talkpython.fm/books/python-in-production Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

On this episode, I'm joined by Dr. Jeff Boeing, an assistant professor at the University of Southern California whose research spans urban planning, spatial analysis, and data science. We explore why OpenStreetMap is such a powerful source of global map data—and how Jeff's Python library, OSMnx, makes that data easier to download, model, and visualize. Along the way, we talk about what shapes city streets around the world, how urban design influences everything from daily commutes to disaster resilience, and why turning open data into accessible tools can open up completely new ways of understanding our cities. If you've ever wondered how to build or analyze your own digital maps in Python, or what it takes to manage a project that transforms raw geographic data into meaningful research, you won't want to miss this conversation. Episode sponsors Posit Podcast Later Talk Python Courses Links from the show City Street Orientations World: geoffboeing.com OSMnx Documentation: readthedocs.io OSMnx GitHub: github.com OpenStreetMap: openstreetmap.org Open Database License: opendatacommons.org ID Editor (Web Editor): wiki.openstreetmap.org Planet OSM: planet.openstreetmap.org Overpass API: wiki.openstreetmap.org GeoPandas: geopandas.org NetworkX: networkx.org Shapely: shapely.readthedocs.io Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

As Python developers, we're incredibly lucky to have over half a million packages that we can use to build our applications with over at PyPI. However, when it comes to choosing a UI framework, the options get narrowed down very quickly. Intersect those choices with the ones that work on mobile, and you have a very short list. Flutter is a UI framework for building desktop and mobile applications, and is in fact the one that we used to build the Talk Python courses app, you'd find at talkpython.fm/apps. That's why I'm so excited about Flet. Flet is a Python UI framework that is distributed and executed on the Flutter framework, making it possible to build mobile apps and desktop apps with Python. We have Feodor Fitsner back on the show after he launched his project a couple years ago to give us an update on how close they are to a full featured mobile app framework in Python. Episode sponsors Posit Podcast Later Talk Python Courses Links from the show Flet: flet.dev Flet on Github: github.com Packaging apps with Flet: flet.dev/docs/publish Flutter: flutter.dev React vs. Flutter: trends.stackoverflow.co Kivy: kivy.org Beeware: beeware.org Mobile forge from Beeware: github.com The list of built-in binary wheels: flet.dev/docs/publish/android#binary-python-packages Difference between dynamic and static Flet web apps: flet.dev/docs/publish/web Integrating Flutter packages: flet.dev/docs/extend/integrating-existing-flutter-packages serious_python: pub.dev/packages/serious_python Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

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: quartopub.com Deno: deno.com Real World Data Science site: realworlddatascience.net Typst: typst.app Github Actions for Quarto: github.com Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

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 Tabular Presentation: census.gov Table Contest: posit.co Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Debuting on January 16, 2014, GOT7 is a 7-member self-producing multinational boy group.Initially known for their "martial arts tricking" concept, they started with hip-hop music but later expanded their musical spectrum to include a wide range of genres, from hip-hop to R&B, with strong vocals, energetic performances, and original choreography.As one of the representative global boy groups of the third generation, GOT7 has proven its power with domestic and international music charts and successful world tours.They are especially hugely popular in Thailand, almost regarded as a national boy group.In 2021, the members began individual activities after leaving their original agency but, out of affection for the group and as a gift for the fans, they reunited as a full group yesterday to release an album after almost three years.This year marks the 11th anniversary of their debut!Let's now check out the music from the perfect group, GOT7, back together.Today's playlist1. PYTHON2. 딱 좋아(Just right)3. 하드캐리(Hard Carry)4. Never Ever5. Miracle - Nive's Pick6. 하지하지마(Stop stop it) - AIVAN's Pick7. 니가 하면(If You Do)

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.python.org/pep-0249 Flask: flask.palletsprojects.com Gunicorn: gunicorn.org MinIO: min.io Amazon S3: aws.amazon.com/s3 Azure Blob Storage: azure.microsoft.com/products/storage Google Cloud Storage: cloud.google.com/storage DigitalOcean: www.digitalocean.com Linode: www.linode.com Hetzner: www.hetzner.com BigQuery: cloud.google.com/bigquery DBT (Data Build Tool): docs.getdbt.com Mode: mode.com Hex: hex.tech Python: www.python.org Node.js: nodejs.org Rust: www.rust-lang.org Go: go.dev .NET: dotnet.microsoft.com Watch this episode on YouTube: youtube.com 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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

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: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

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 --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

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 Pydantic: pydantic.dev PEP 0759: peps.python.org TypeShed: github.com Maturin: maturin.rs rloop: github.com 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 Snakes, David Seddon, Pycon Italia: youtube.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

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: docs.python.org Avalonia UI: avaloniaui.net 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

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 song: youtube.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

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 Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

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 Datasaurus Dozen: stefaniemolin.com Data Morph on GitHub: 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

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.stackoverflow.co 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

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 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

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.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

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: Scratch Jr.: scratchjr.org Scratch: scratch.org Blocky: google.com Microbit's Make Code: microbit.org Code Club: codeclubworld.org Textual programming Code Combat: codecombat.com Hedy: hedycode.com Anvil: anvil.works Coding classes / summer camps (US) Portland Community College Summer Teen Program: pcc.edu 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

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 YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

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 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: py-free-threading.github.io caniuse.com: caniuse.com SPy, presented at PyCon 2024: us.pycon.org 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

Do you feel like ADHD is holding you back? Maybe you don't personally have ADHD but you work with folks who do and you'd like to support them better. Either way, how ADHD interplays with programming and programmers is pretty fascinating. On this episode we have Chris Ferdinandi who himself has ADHD and has written a lot about it to share his journey and his advice for thriving with ADHD as a programmer or data scientist. Episode sponsors Posit Talk Python Courses Links from the show Chris on Mastodon: @cferdinandi ADHD FTW Talk Python Page: adhdftw.com Building a Second Brain: buildingasecondbrain.com Building a Second Brain Book: buildingasecondbrain.com White Collar Jobs are Just Meetings: theatlantic.com Article with Fighting Duck-Sized Horses Agile: mensurdurakovic.com Nothing Phone: nothing.tech Apple Watch: apple.com Todoist: todoist.com Anytype (open source Notion): anytype.io Obsidian: obsidian.md 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

Flask is one of the most important Python web frameworks and powers a bunch of the internet. David Lord, Flask's lead maintainer is here to give us an update on the state of Flask and Pallets in 2024. If you care about where Flask is and where it's going, you'll definitely want to listen in. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Talk Python Courses Links from the show David on Mastodon: @davidism David on X: @davidism State of Pallets 2024 FlaskCon Talk: youtube.com FlaskCon: flaskcon.com FlaskCon 2024 Talks: youtube.com Pallets Discord: discord.com Pallets Eco: github.com JazzBand: jazzband.co Pallets Github Org: github.com Jinja: github.com Click: github.com Werkzeug: github.com MarkupSafe: github.com ItsDangerous: github.com Quart: github.com pypistats: pypistats.org 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

If you want to get better at something, often times the path is pretty clear. If you get better at swimming, you go to the pool and practice your strokes and put in time doing the laps. If you want to get better at mountain biking, hit the trails and work on drills focusing on different aspects of riding. You can do the same for programming. Reuven Lerner is back on the podcast to talk about his book Pandas Workout. We dive into strategies for learning Pandas and Python as well as some of his workout exercises. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Scalable Path Talk Python Courses Links from the show Reuven Lerner on Twitter: @reuvenmlerner Pandas Workout Book: manning.com Bamboo Weekly: Solar eclipse: bambooweekly.com Bamboo Weekly: Avocado hand: bambooweekly.com Scaling data science across Python and R: 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 Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Python is special. It's used by the big tech companies but also by those you would rarely classify as developers. On this episode, we get a look inside how Python is being used at a Children's Hospital to speed and improve patient care. We have Dr. Somak Roy here to share how he's using Python in his day to day job to help kids get well a little bit faster. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Posit Talk Python Courses Links from the show Somak Roy: linkedin.com Cincinnati Children's Hospital: cincinnatichildrens.org CNVkit: Genome-wide copy number: readthedocs.io cnaplotr: github.com hgvs: readthedocs.io openpyxl: readthedocs.io Hera is an Argo Python SDK: github.com insiM: in silico Mutator software for bioinformatics: github.com Bamsurgeon: github.com pysam - An interface for reading and writing SAM files: readthedocs.io Scientists rename human genes to stop Microsoft Excel from misreading them as dates: theverge.com BioPython: biopython.org 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 is one of the most popular languages of the current era. It dominates data science, it an incredible choice for web development, and its many people's first language. But it's not super great on front-end programing, is it? Frameworks like React, Vue and other JavaScript frameworks rule the browser and few other languages even get a chance to play there. But with pyscript, which I've covered several times on this show, we have the possibility of Python on the front end. Yet it's not really a front end framework, just a runtime in the browser. That's why I'm excited to have Ken Kinder on the podcast to talk about his project PuePy, a reactive frontend framework in Python. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Code Comments Talk Python Courses Links from the show Michael's Code in a Castle Course: talkpython.fm/castle Ken Kinder: @bouncing@twit.social PuePy: puepy.dev PuePy Docs: docs.puepy.dev PuePy on Github: github.com pyscript: pyscript.net VueJS: vuejs.org Hello World example: docs.puepy.dev Tutorial: docs.puepy.dev Tutorial running at pyscript.com: pyscript.com Micropython: micropython.org Pyodide: pyodide.org PgQueuer: github.com Writerside: jetbrains.com Michael's PWA pyscript app: github.com Michael's demo of a PWA pyscript app: youtube.com Python iOS Web App with pyscript and offline PWAs video: youtube.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

I've gathered a group of Python experts who have been thinking deeply about where Python is going and who have lived through where it has been. This episode is all about near-term Python trends and things we each believe will be important to focus on as Python continues to grow. Our panelists are Jodie Burchell, Carol Willing, and Paul Everett. Episode sponsors Code Comments Posit Talk Python Courses Links from the show Shiny course at Talk Python: talkpython.fm/shiny Jodie Burchell: @t_redactyl Carol on Mastodon: @willingc@hachyderm.io Paul Everitt: @paulweveritt 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

I have a special episode for you this time around. We're coming to you live from PyCon 2024. I had the chance to sit down with some amazing people from the data science side of things: Jodie Burchell, Maria Jose Molina-Contreras, and Jessica Greene. We cover a whole set of recent topics from a data science perspective. Though we did have to cut the conversation a bit short as they were coming from and go to talks they were all giving but it was still a pretty deep conversation. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Code Comments Talk Python Courses Links from the show Jodie Burchell: @t_redactyl Jessica Greene: linkedin.com Maria Jose Molina-Contreras: linkedin.com Talk Python's free Shiny course: talkpython.fm/shiny 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

You're using Pydantic and it seems pretty straightforward, right? But could you adopt some simple changes to your code that would make it a lot faster and more efficient? Chances are, you'll find a couple of the tips from Sydney Runkle that will do just that. Join us to talk about Pydantic performance tips here on Talk Python. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Code Comments Talk Python Courses Links from the show Sydney Runkle: linkedin.com Pydantic: pydantic.dev Performance docs: docs.pydantic.dev Union tips: docs.pydantic.dev Sydney's presentation slides: docs.google.com JSON to Pydantic: jsontopydantic.com Samuel talking FastUI: talkpython.fm CodeFlash: codeflash.ai Codspeed: codspeed.io 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 hasn't been a boom like the AI boom since the .com days. And it may look like a space destined to be controlled by a couple of tech giants. But Ines Montani thinks open source will play an important role in the future of AI. I hope you join us for this excellent conversation about the future of AI and open source. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Porkbun Talk Python Courses Links from the show Ines Montani on Twitter: @_inesmontani spaCy: spacy.io Prodigy App: prodi.gy Ines' presentation at PyCon Lithuania: youtube.com LM Studio: lmstudio.ai Little Bobby Tables: xkcd.com spaCy and NLP course: 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 Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

Do you want to look inside your Django request? How about all of your requests in development and see where they overlap? If that sounds useful, you should check out Kolo. It's a pretty incredible extension for your editor (VS Code at the moment, more editors to come most likely). We have Wilhelm Klopp on to tell us all about it. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Talk Python Courses Links from the show Wil on Twitter: @wilhelmklopp Kolo: kolo.app Kolo's info repo: github.com Kolo Playground: play.kolo.app Generating tests with Kolo: kolo.app 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

So you've created a web app with Python using Flask, Django, FastAPI, or even Emmett. It works great on your machine. How do you get it out to the world? You'll need a production-ready web server. On this episode, we have Giovanni Barillari to tell us about his relatively-new server named Granian. It promises better performance and much better consistency than many of the more well known ones today. Episode sponsors Neo4j Talk Python Courses Links from the show New spaCy course: talkpython.fm Giovanni: @gi0baro Granian: github.com Emmett: emmett.sh Renoir: 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

This episode dives into some of the most important data science libraries from the Python space with one of its pioneers: Wes McKinney. He's the creator or co-creator of pandas, Apache Arrow, and Ibis projects and an entrepreneur in this space. Episode sponsors Neo4j Mailtrap Talk Python Courses Links from the show Wes' Website: wesmckinney.com Pandas: pandas.pydata.org Apache Arrow: arrow.apache.org Ibis: ibis-project.org Python for Data Analysis - Groupby Summary: wesmckinney.com/book Polars: pola.rs Dask: dask.org Sqlglot: sqlglot.com Pandoc: pandoc.org Quarto: quarto.org Evidence framework: evidence.dev pyscript: pyscript.net duckdb: duckdb.org Jupyterlite: jupyter.org Djangonauts: djangonaut.space 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

Do you use Python in an academic setting? Maybe you run a research lab or teach courses using Python. Maybe you're even a student using Python. Whichever it is, you'll find a ton of great advice in this episode. I talk with Keiland Cooper about how he is using Python at his neuroscience lab at the University of California, Irvine. Episode sponsors Neo4j Posit Talk Python Courses Links from the show Keiland's website: kwcooper.xyz Keiland on Twitter: @kw_cooper Keiland on Mastodon: @kwcooper@fediscience.org Journal of Open Source Software: joss.readthedocs.io Avalanche project: avalanche.continualai.org ContinualAI: continualai.org Executable Books Project: executablebooks.org eLife Journal: elifesciences.org 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