Python Bytes - #456 You’re so wrong

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Brian #1: The PSF has withdrawn a $1.5 million proposal to US government grant program

  • Related post from Simon Willison
  • ARS Technica: Python plan to boost software security foiled by Trump admin’s anti-DEI rules
  • The Register: Python Foundation goes ride or DEI, rejects government grant with strings attached
  • In Jan 2025, the PSF submitted a proposal for a US NSF grant under the Safety, Security, and Privacy of Open Source Ecosystems program. After months of work by the PSF, the proposal was recommended for funding.
  • If the PSF accepted it, however, they would need to agree to the some terms and conditions, including, affirming that the PSF doesn't support diversity. The restriction wouldn't just be around the security work, but around all activity of the PSF as a whole. And further, that any deemed violation would give the NSF the right to ask for the money back.
  • That just won't work, as the PSF would have already spent the money.
  • The PSF mission statement includes "The mission of the Python Software Foundation is to promote, protect, and advance the Python programming language, and to support and facilitate the growth of a diverse and international community of Python programmers." The money would have obviously been very valuable, but the restrictions are just too unacceptable.
  • The PSF withdrew the proposal. This couldn't have been an easy decision, that was a lot of money, but I think the PSF did the right thing.

Michael #2: A Binary Serializer for Pydantic Models

  • 7× Smaller Than JSON
  • A compact binary serializer for Pydantic models that dramatically reduces RAM usage compared to JSON.
  • The library is designed for high-load systems (e.g., Redis caching), where millions of models are stored in memory and every byte matters.
  • It serializes Pydantic models into a minimal binary format and deserializes them back with zero extra metadata overhead.
  • Target Audience: This project is intended for developers working with:
    • high-load APIs
    • in-memory caches (Redis, Memcached)
    • message queues
    • cost-sensitive environments where object size matters

Brian #3: T-strings: Python's Fifth String Formatting Technique?

  • Trey Hunner
  • Python 3.14 has t-strings. How do they fit in with the rest of the string story?
  • History
    • percent-style (%) strings - been around for a very long time
    • string.Template - and t.substitute() - from Python 2.4, but I don’t think I’ve ever used them
    • bracket variables and .format() - Since Python 2.6
    • f-strings - Python 3.6 - Now I feel old. These still seem new to me
    • t-strings - Python 3.14, but a totally different beast. These don’t return strings.
  • Trey then covers a problem with f-strings in that the substitution happens at definition time.
  • t-strings have substitution happen later. this is essentially “lazy string interpolation”
  • This still takes a bit to get your head around, but I appreciate Trey taking a whack at the explanation.

Michael #4: Cronboard

  • Cronboard is a terminal application that allows you to manage and schedule cronjobs on local and remote servers.
  • With Cronboard, you can easily add, edit, and delete cronjobs, as well as view their status.
  • ✨ Features
    • ✔️ Check cron jobs
    • ✔️ Create cron jobs with validation and human-readable feedback
    • ✔️ Pause and resume cron jobs
    • ✔️ Edit existing cron jobs
    • ✔️ Delete cron jobs
    • ✔️ View formatted last and next run times
    • ✔️ Accepts special expressions like @daily, @yearly, @monthly, etc.
    • ✔️ Connect to servers using SSH, using password or SSH keys
    • ✔️ Choose another user to manage cron jobs if you have the permissions to do so (sudo)

Extras

Brian:

Joke: You are so wrong!

Talk Python To Me - #526: Building Data Science with Foundation LLM Models

Today, we’re talking about building real AI products with foundation models. Not toy demos, not vibes. We’ll get into the boring dashboards that save launches, evals that change your mind, and the shift from analyst to AI app builder. Our guide is Hugo Bowne-Anderson, educator, podcaster, and data scientist, who’s been in the trenches from scalable Python to LLM apps. If you care about shipping LLM features without burning the house down, stick around.

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Watch this episode on YouTube: youtube.com
Episode #526 deep-dive: talkpython.fm/526
Episode transcripts: talkpython.fm

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Lex Fridman Podcast - #484 – Dan Houser: GTA, Red Dead Redemption, Rockstar, Absurd & Future of Gaming

Dan Houser is co-founder of Rockstar Games and is a legendary creative mind behind Grand Theft Auto (GTA) and Red Dead Redemption series of video games.
Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep484-sc
See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc.

Transcript:
https://lexfridman.com/dan-houser-transcript

CONTACT LEX:
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EPISODE LINKS:
Absurd Adventures: https://absurdventures.com
A Better Paradise: https://www.amazon.com/exec/obidos/ASIN/B0FCYSK8VD
American Caper: https://absurdventures.com/americancaper

SPONSORS:
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OUTLINE:
(00:00) – Introduction
(01:29) – Sponsors, Comments, and Reflections
(11:32) – Greatest films of all time
(23:45) – Making video games
(26:36) – GTA 3
(29:55) – Open world video games
(32:42) – Character creation
(36:09) – Superintelligent AI in A Better Paradise
(45:21) – Can LLMs write video games?
(49:41) – Creating GTA 4 and GTA 5
(1:01:16) – Hard work and Rockstar’s culture of excellence
(1:04:56) – GTA 6
(1:21:46) – Red Dead Redemption 2
(2:01:39) – DLCs for GTA and Red Dead Redemption
(2:07:58) – Leaving Rockstar Games
(2:17:22) – Greatest game of all time
(2:22:10) – Life lessons from father
(2:24:29) – Mortality
(2:41:47) – Advice for young people
(2:47:49) – Future of video games

PODCAST LINKS:
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Big Technology Podcast - OpenAI and Microsoft’s Grand Bargain, Sam Altman’s Next Three Years, A New Humanoid Robot

Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We cover: 1) OpenAI converts to a public benefit corporation 2) Why this is big news 3) Satya Nadela's wise OpenAI maneuver 4) Microsoft wants every AI model on Azure 5) Is AGI dead? 6) Inside Microsoft and OpenAI's negotiations 7) Sam Altman charts out OpenAI's next three years 8) Is building automated AI researchers a worthwhile and ambitious goal? 9) OpenAI also wants to be its own Ai cloud 10) OpenAI has become Facebook, kinda 11) OpenAI employees say they don't want to be engagement farmers 12) Meta's threat from OpenAI 13) Instead of the AI bubble, how about the AI wobble? 14) Do we want the 1X Technologies Neo humanoid robot?


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The Stack Overflow Podcast - Vibe coding needs a spec, too

Ryan talks with Deepak Singh, VP of Developer Agents and Experiences at AWS and lead at Kiro, about spec-driven development in a vibe coding world. They explore how AI tools have evolved from autocomplete to sophisticated agents that can write code based off of just specs, and how AWS has pioneered spec-driven development through their Kiro agent. 

Episode notes:

Kiro is AWS’ AI IDE that brings structure to AI coding with spec-driven development. 

Connect with Deepak on the Kiro Discord server and read more about spec-driven development on The New Stack

We last spoke to Deepak Singh in March about how enterprise-ready agents are.

Congratulations to user Whymarrh for winning a Populist badge on their answer to Git commits are duplicated in the same branch after doing a rebase

Learn more about the future of software engineering in the AI age on November 3rd, when our CEO, Prashanth Chandrasekar, speaks at a virtual OpenAI Forum.

TRANSCRIPT

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Code Story: Insights from Startup Tech Leaders - S11 Bonus: Shamba Chowdhury, DeForge

Shamba Chowdhury got his first computer at an early age. He was the kid that explored every button and every setting, trying to figure out how it all worked. His curiosity exploded when he was 15 and the internet came around. Post that, his first foray into programming came from his love of playing video games. Outside of tech, he loves to read, in particular crime thrillers. He noted that his favorite is A Minute to Midnight by David Baldacci.

Shamba and his co-founder have participated in many hackathons, and they noticed how difficult it was to stitch together ideas, utilizing AI technology. It was at that point they decided to build a no code builder to wire up AI agents together.

This is the creation story of DeForge.

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Big Technology Podcast - How AI Is Changing Writing — With Tony Stubblebine

Tony Stubblebine is the CEO of Medium. He joins Big Technology to discuss the future of writing in the age of AI and how platforms should handle AI-generated content. Tune in to hear fresh data on ChatGPT vs. Google referral quality, Gemini’s impact on click-throughs, and Medium’s anti-spam approach. We also cover Cloudflare AI blocking, creator payouts, and Medium’s writing app. Hit play for a candid operator’s view of what survives—and thrives—as AI floods the web.

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Code Story: Insights from Startup Tech Leaders - The Railsware Way – Vibe Coding vs. Traditional SDLC, with Sergiy Korolov

Today, we are kicking off a new series, sponsored by our good friends at Railsware. Railsware is a leading product studio with two main focuses - services and products. They have created amazing products like Mailtrap, Coupler and TitanApps, while also partnering with teams like Calendly and Bright Bytes. They deliver amazing products, and have happy customers to prove it.

In this series, we are digging into the company's methods around product engineering and development. In particular, we will cover relevant topics to not only highlight their expertise, but to educate you on industry trends alongside their experience.

In today's episode, we are talking with Sergiy Korolov, Co-CEO of Railsware and Co-founder of Mailtrap. In this conversation, we are bringing up a popular - but somewhat controversial topic - vibe-coding vs. traditional software development approaches.

Questions:

  • You’ve been in tech for over two decades, and have definitely seen many trends come and go. How would you define "vibe-coding" and how does it differ from traditional software development approaches?
  • What drove the emergence of vibe-coding? Could it be a response to overly rigid development processes that many companies have? Or it’s a fundamental shift in engineering?
  • What do engineers on your team think about vibe-coding? Have you practiced this approach on some of your products?
  • What types of products or development contexts are best suited for vibe-coding?
  • Is it possible to create successful and scalable products through vibe-coding? For instance, can people balance vibe-coding with business requirements, deadlines, and stakeholder expectations?
  • To wrap up, is vibe-coding actually sustainable long-term, or is it just a trendy reaction to over-engineering?

Links




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Code Story: Insights from Startup Tech Leaders - S11 E23: Dr. Zohar Bronfman, Pecan AI

Zohar Bronfman spends most of his time in Tel Aviv, Israel these days. He has a focused academic background, specifically in philosophy and neuroscience. He was always intrigued by the question - how do we know what we know? - which led him to get a PhD in Philosophy. While doing that, he also became fascinated with he human mind and empirical decision making, which took him down the road of obtaining another PhD in AI & Neuroscience, essentially emulating brain processes. Outside of tech, he has 3 kids and a startup. He loves a good book in the philosophy or neuroscience space, and is a big fan of sports. Specifically, he loves the NBA and claims to be a Knicks fan.

Zohar and his now co-founder were digging into predictive models, as an extension of their academic studies. They were curious as to why companies, though they were running predictive models, were not making accurate predictions. They soon realized that this was because the AI modeling expertise was centralized at couple of well known companies.

This is the creation story of Pecan AI.

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The Stack Overflow Podcast - Craft and quality beat speed and scale, with or without agents

Ryan welcomes Tom Moor, head of engineering at Linear, to discuss AI agents’ mixed results for productivity in the development lifecycle, the importance of context for maximizing agents’ effectiveness, and the role that junior developers need to take in a world increasingly driven by AI.

Episode notes:

Linear is a tool for planning and building products that streamline issues, projects, and product roadmaps.

Connect with Tom on Twitter

This episode’s shoutout goes to user ozz, who won a Populist badge for their answer to Column width not working in DataTables bootstrap.

TRANSCRIPT

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.