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...
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
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1:05:01
#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
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
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1:04:21
#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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1:02:03
#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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1:04:32
#489: Anaconda Toolbox for Excel and more with Peter Wang
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 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
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.