Posit PBC

10/28/2026

10/28/2026

Manage your Python and R packages using the Packages pane directly in Positron!

10/19/2026

5 Best Python Polars Data Validation Libraries ⚡📊

Looking for data validation, schema enforcement, and data quality tools built for Python Polars DataFrames? Here are 5 essential Python libraries for Polars pipelines:

1️⃣ Pandera – Schema-first validation with statistical checks, type safety, and mypy integration.
2️⃣ Patito – Pydantic-style data models and schema validation designed natively for Polars DataFrames.
3️⃣ Pointblank – Comprehensive validation workflows that generate interactive reports for stakeholders.
4️⃣ Validoopsie – Lightweight, composable validation checks with smart error handling and built-in logging.
5️⃣ Dataframely – Type-safe collection schema validation with advanced failure analysis.

💡 Polars Data Engineering Topics:


Learn how to enforce DataFrame schemas, audit data quality, and prevent errors in high-performance Polars workflows!

10/15/2026

So you've got a cool CSV file to work with, but how do you actually load it into your Python project? In this 60-second tutorial, we explore 3 simple methods using Polars, Positron's built-in GUI, and AI.

📌 What you'll learn:

- Load CSV with Polars pl.read_csv()
- Parse CSV using Positron's built-in Import Dataset UI
- Import data automatically using Posit Assistant

💡 Best for: Beginner Python programmers, Polars users, and Positron IDE workflows.

09/22/2026

The clearest framing of AI I have heard this year comes down to middle school arithmetic.

"There was somebody who said something like, hey, like LLMs, you know, sort of an exponent on on who you are and what you are. So if you're if you're already a greater than one, then you will that num that ex you know that exponential is going to grow you dramatically. But if you're just a little bit under one for whatever reason. then that you know the greater power is gonna make you a much smaller impact."

That's Posit CEO Tareef Kawaf on The Test Set, and the math holds up. Raise 1.2 to the tenth power and you land somewhere near 6. Raise 0.9 to the same power and you end up around 0.35. The exponent is identical in both cases, and the two people come out of it in completely different places.

That puts the variable on your side of the equation rather than the tool's. Full episode out now.

Listen now on Spotify (https://open.spotify.com/episode/7AbutF3Xvsf7ScaglRfiFo?si=23aea660fef34a04) and Apple Podcasts (https://podcasts.apple.com/us/podcast/the-test-set-by-posit/id1823736938?i=1000790947311).

09/08/2026

Leland McInnes’s gripe about data science is that we have amazing tools for tabular data, and basically nothing good for the rest of it. On The Test Set, the mathematician behind UMAP explains the problem that's driven his entire body of work. If you've got a giant pile of documents, images, videos, or some mixture of all three, how do you even figure out what's in there, let alone explore it in a way that makes sense? His answer isn't "let an AI summarize it for you." It's that humans still need to be the ones looking, because understanding a dataset takes taste, and taste is something AI doesn't have … yet. Every tool he's built, UMAP, HDBSCAN, EVōC, exists to condense a messy pile of unstructured data down to something a person can actually look at and learn from.

Listen now on Spotify (https://open.spotify.com/episode/5KhfqQxJCgPeDoYyndj0Oz?si=15d68ee7a5744b2f) and Apple Podcasts (https://podcasts.apple.com/us/podcast/the-test-set-by-posit/id1823736938?i=1000788474295).

08/25/2026

"You guys always have way too much to say in the time allotted. It's just the nature of your business."

Ruth Milligan said this to Michael, Wes and Hadley on this week's The Test Set, and nobody argued. Because she's right.

Her question, the one she's put to hundreds of conference speakers, is brutal and useful. How much information do I have to share for you to believe something is true? Do I have to show you 20 charts, or can I show you two?

The uncomfortable part is that you spent six weeks on the analysis and your audience is going to walk out remembering one thing. So pick the thing.

Ruth curates TEDx Columbus, wrote The Motivated Speaker, and has coached hundreds of data folks through exactly this problem.

Listen now on Spotify https://open.spotify.com/episode/1AxvHyeKsPPU3E5PfW8gGT?si=3aa9bf9006144332 and Apple Podcasts https://podcasts.apple.com/us/podcast/the-test-set-by-posit/id1823736938?i=1000785578039.

08/11/2026

Hot take from someone who actually shipped it —> most MCP integrations have too many tools. marimo pair had a whole drawer of them. List my variables. List my data frames. Tell me what's in cell three. Trevor Manz and the marimo team deleted all of it, and what’s left is one tool to run Python code, in the kernel, where the notebook actually lives. Feedback comes in the same turn as the action. Redefine a variable, break marimo's rules, hallucinate a value that isn't there — the error comes straight back, without a follow-up query. This means no more agent babysitting (agentsitting?). One sharp tool beats a pile of dull ones, and the model already speaks Python. Trevor's on latest episode of The Test Set with Michael Chow and Hadley Wickham.

Listen now on Spotify (https://open.spotify.com/episode/2gmO1zQFv5PRQ0HandRj2N?si=9da3245c0a3d4c05) and Apple Podcasts (https://podcasts.apple.com/us/podcast/let-the-agent-cook-with-trevor-manz/id1823736938?i=1000782024767).

07/28/2026

Being reasonable and being ethical are not the same thing, and Leilani Battle thinks data science low-key mixes the two up all the time. On the new episode of The Test Set, the UW professor hits on why so much harm in this field doesn't come from bad actors cutting corners, it comes from people acting completely rationally inside a definition of rational that was never built to account for ethics. "It's not that people aren't rational or people aren't reasonable," she says. "It's that they're rational and reasonable. Rational behavior is not necessarily, in the current context, the definition of rationality might not be ethical. So if you define rational as responsible, you end up in a different frame." A useful reframe for anyone who assumes good outcomes just follow from good intentions.

Listen now on Spotify (https://open.spotify.com/episode/6fn22DYxSoKX9OFBx61N41?si=06a884a1103a44a0) and Apple Podcasts (https://podcasts.apple.com/us/podcast/the-test-set-by-posit/id1823736938?i=1000778566461).

07/14/2026

Joe Cheng, CTO of Posit, was genuinely unsure about whether he should keep building AI tools at all. On this episode of The Test Set, he explains how he landed on an answer. His logic: The train keeps moving with or without him. If he personally stepped away from AI, or even got his whole company to abstain, it wouldn't slow the technology's development anywhere else. Joe points to Posit’s decades of perspectives about reproducible, correct data science and the leverage to help people avoid getting confidently wrong answers from these tools. He argues that's exactly why the company has an obligation to stay in the room.

Listen on Spotify (https://open.spotify.com/episode/5pD6aH5Y2vPuecLpEeJEMW?si=6b645cc9a77c4d74) and Apple Podcasts (https://podcasts.apple.com/us/podcast/the-test-set-by-posit/id1823736938?i=1000776617646).