Talk Python To Me

• #494: Update on Flet: Python + Flutter UIs

  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

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• #493: Quarto: Open-source technical publishing

  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 Podcast Later 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

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• #492: Great Tables

  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 Posit Podcast Later Talk Python Courses 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

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

  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

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• #490: Django Ninja

  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

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