Podcasts about Python

We welcome author Travis Kennedy this week to talk about his debut novel “The Whyte Python World Tour”. Rikki Thunder, twenty-two-year-old drummer for the scorching new '80s metal band Whyte Python, is about to have it all: absurd wealth, global fame, and a dream girlfriend. But an unwitting role as an international spy? That was definitely not part of the plan. Find out more about Travis and “The Whyte Python World Tour” at the links below! TravisKennedy.com WhytePython.com Instagram: @KennedyWriting Check out “It Takes A Little Spark” by the band Rekkless at the link below:https://youtube.com/@rekklessrocks?si=_EH5oPUVa5HG0ZPH CannedAirPodcast.com TikTok: @CannedAirPodcast Instagram: @Canned_Air If you'd like to show your support, you can either visit our Patreon page at Patreon.com/CannedAirPod or you can leave us a review on iTunes! Thanks for listening! Learn more about your ad choices. Visit megaphone.fm/adchoices

Cesare e Marco raccontano le novità introdotte in Python 3.14, tra cui l'uso di interpreti concorrenti, le t-strings, e le annotazioni differite.

How do you prepare your Python data science projects for production? What are the essential tools and techniques to make your code reproducible, organized, and testable? This week on the show, Khuyen Tran from CodeCut discusses her new book, "Production Ready Data Science."

Capítulo 2424 del 14 nov 2025 Por cuestiones profesionales y personales, estoy planteándome aprender a programar en Python. Si quieres apoyar este podcast, invítame a un café me ayudaras a mantenerme despierto y a los gastos de este podcast. Únete al grupo de telegram del podcast en t.me/daytodaypod. Usa el enlace de afiliado de Amazon para ayudar a mantener el podcast. Soy miembro de la Asociación Podcast. Si te registras y usas el código SP7F21 tendrás 5€ de descuento el primer año. https://www.asociacionpodcast.es/registrarse/socio/?coupon=SP7F21 Date de alta en Curve con este código y conseguiremos 5£: DO6QR47E Ya sabéis que podéis escribirme a @spascual, spascual@spascual.es el resto de métodos de contacto en https://spascual.es/contacto.

Por cuestiones profesionales y personales, estoy planteándome aprender a programar en Python.

In this episode of Data Skeptic's Recommender Systems series, host Kyle Polich explores DataRec, a new Python library designed to bring reproducibility and standardization to recommender systems research. Guest Alberto Carlo Mario Mancino, a postdoc researcher from Politecnico di Bari, Italy, discusses the challenges of dataset management in recommendation research—from version control issues to preprocessing inconsistencies—and how DataRec provides automated downloads, checksum verification, and standardized filtering strategies for popular datasets like MovieLens, Last.fm, and Amazon reviews.  The conversation covers Alberto's research journey through knowledge graphs, graph-based recommenders, privacy considerations, and recommendation novelty. He explains why small modifications in datasets can significantly impact research outcomes, the importance of offline evaluation, and DataRec's vision as a lightweight library that integrates with existing frameworks rather than replacing them. Whether you're benchmarking new algorithms or exploring recommendation techniques, this episode offers practical insights into one of the most critical yet overlooked aspects of reproducible ML research.

André Arko, CEO of Spinel Cooperative and longtime Bundler maintainer, joins Corey Quinn to introduce RV, a new Ruby tool that installs Ruby in one second instead of 10-40 minutes by using precompiled binaries. Inspired by Python's UV, RV aims to simplify Ruby dependency management without the complexity of older tools like RVM and rbenv. They talk about why Ruby isn't actually dead, Apple's problem with shipping a five-year-old end-of-life Ruby in macOS, and the challenges of writing dependency managers in the language they manage. André also shares how he transitioned from a struggling nonprofit model to a cooperative that charges companies for expertise, proving that open source maintainers can build sustainable businesses without relying on donations.Show Highlights:(03:50) Introducing RV(05:12) The RVM vs rbenv Wars and Why They All Break Bundler(09:00) Why Your Mac Still Shows Ruby 3.0.0 in Your Prompt(11:00) The Chef vs Puppet Philosophy Divide(16:30) Installing Ruby in One Second vs 40 Minutes(18:13) Apple's Ancient System Ruby Problem(22:20) RV's Incremental Approach (24:23) Is Ruby Dead? (28:44) Why RV Is Written in Rust, Not Ruby(31:10) The Bundler Problem(32:15) The Financial Reality(38:00) Spinel's Plans to Make Money(39:23) How to Stay In Contact with AndréLinks:André Arko: https://arko.netBlue Sky: https://bsky.app/profile/indirect.ioSpinel Cooperative: https://spinel.coopSponsor: Duckbill: https://www.duckbillhq.com/

"A gamificação leva a um aprendizado muito mais prazeroso e significativo. Isso vai ficar de fato presente nas suas sinapses, nas suas conexões" - Wagner Sanchez No décimo terceiro episódio do Hipsters.Talks, PAULO SILVEIRA, CVO do Grupo Alun, conversa com WAGNER SANCHEZ, pró-reitor acadêmico da FIAP, sobre gamificação na educação, metodologias ativas e como transformar o aprendizado de tecnologia em algo prazeroso e efetivo. Uma conversa inspiradora sobre como jogos, desafios e competições podem revolucionar a forma como aprendemos.  Prepare-se para um episódio cheio de conhecimento e inspiração! Espero que aproveitem :) Sinta-se à vontade para compartilhar suas perguntas e comentários. Vamos adorar conversar com vocês!

Waymo's VP of Research, Drago Anguelov, joins Practical AI to explore how advances in autonomy, vision models, and large-scale testing are shaping the future of driverless technology. The conversation dives into the dual challenges of building an onboard driver and testing that driver (via large scale simulation). Drago also gives us an update on what Waymo is doing to achieve intelligent, real-time performance while ensuring proven safety and reliability.Featuring:Drago Anguelov – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:Waymo ResearchNew Insights for Scaling Laws in Autonomous DrivingAI in MotionSponsors: Outshift by Cisco - The open source collective building the Internet of Agents. Backed by Outshift by Cisco, AGNTCY gives developers the tools to build and deploy multi-agent software at scale. Identity, communication protocols, and modular workflows—all in one global collaboration layer. Start building at AGNTCY.org.Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiFabi.ai - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.aiUpcoming Events: Register for upcoming webinars here!

Чтобы научиться программировать и разбираться в тонкостях Python 3.12 записывайтесь на базовый курс Learn Python — https://clck.ru/3MuShF   Ведущие – Григорий Петров и Михаил Корнеев Ссылки выпуска: Курс Learn Python — https://learn.python.ru/advanced Канал Миши в Telegram — https://t.me/tricky_python Канал Moscow Python в Telegram — https://t.me/moscow_python Все выпуски — https://podcast.python.ru Митапы Moscow Python — https://moscowpython.ru Канал Moscow Python на Rutube — https://rutube.ru/channel/45885590/ Канал Moscow Python в VK — https://vk.com/moscowpythonconf Курс «Основы Python» от Learn Python — это отличный старт для новичков в программировании. За несколько уроков вы освоите базовый синтаксис, научитесь работать с данными и получите первый опыт для успешного старта карьеры в ИТ. Подробности: https://clck.ru/3MuShF

Lucas Anders interviews Xander Robin (director) about his documentary THE PYTHON HUNT. See it at CUFF.Docs Saturday November 22nd at 9:15 pm at the Globe Theatre in Calgary.THE PYTHON HUNT... Every year, the Florida government calls upon the general public to compete in an invasive python removal contest in the Everglades in an attempt to save the threatened ecosystem. For 10 gruelling nights, an eclectic group of amateur hunters confront the dangerous terrain, nocturnal creatures, and their own desires. Meanwhile, one professional hunter leads the charge to undermine the competition, questioning what hides beneath the python mania gripping the ‘glades. The film, which had its World Premiere at SXSW, is the feature documentary debut of CUFF alum Xander Robin, who attended CUFF in 2017 for the Canadian Premiere of his first narrative feature ARE WE NOT CATS.TIX: www.calgaryundergroundfilm.org/cuff-docs…hon-hunt/WEBSITE: xanderrobin.com/INSTAGRAM: @xanderroobin

Tomas Kirnak, CEO of Unimus, joins Eric Chou in this sponsored episode to introduce Unimus, an on-premise network configuration management system built by network engineers to solve real-world problems. In this deep dive they discuss Unimus' proprietary “Behavioral Tree” for automatic device discovery, the platform’s vendor support, the 70/30 rule, and lowering the barrier for... Read more »

Merrill on LinkedIn (https://www.linkedin.com/in/merrill-lutsky/) Graphite (https://graphite.com/) Alice for Snowflake (https://alice.dev/alice-snowflake/) Mike on X (https://x.com/dominucco) Mike on BlueSky (https://bsky.app/profile/dominucco.bsky.social) Coder on X (https://x.com/coderradioshow) Show Discord (https://discord.gg/k8e7gKUpEp) Alice & Custom Dev (https://alice.dev) Mike's Recent Omakub Blog Post (https://dominickm.com/omakhub-review/)

Tomas Kirnak, CEO of Unimus, joins Eric Chou in this sponsored episode to introduce Unimus, an on-premise network configuration management system built by network engineers to solve real-world problems. In this deep dive they discuss Unimus' proprietary “Behavioral Tree” for automatic device discovery, the platform’s vendor support, the 70/30 rule, and lowering the barrier for... Read more »

There was once a time, when data science was still in its infancy, when demonstrating any attempt to learn Python or machine learning was enough to secure a job interview. The demand for data scientists massively outweighed supply. Ten years later, however, the job market has dramatically shifted - and many data scientists who unexpectedly find themselves out of work face a truly overwhelming experience.In this episode, Sarah Burnett joins Dr. Genevieve Hayes to share how she transformed redundancy from a senior banking role into the launch of her own successful data consultancy, proving that unexpected job loss doesn't have to mean career disaster.In this episode, we explore:Why redundancy is a numbers game, not personal failure [03:54]The power of taking time to process after job loss, instead of rushing back [08:47]How to pivot when your first business idea doesn't work [16:58]Why building side projects and community involvement create career insurance [20:52]Guest BioSarah Burnett is the co-founder of Dub Dub Data, a consultancy that offers human-centric AI and Tableau solutions. She transitioned into independent consulting after navigating redundancy from a senior role at a major bank. She is also the co-host of the podcast unDubbed.LinksConnect with Sarah on LinkedInDub Dub Data WebsiteConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

Topics covered in this episode: httptap 10 Smart Performance Hacks For Faster Python Code FastRTC Explore Python dependencies with pipdeptree and uv pip tree Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: httptap Rich-powered CLI that breaks each HTTP request into DNS, connect, TLS, wait, and transfer phases with waterfall timelines, compact summaries, or metrics-only output. Features Phase-by-phase timing – precise measurements built from httpcore trace hooks (with sane fallbacks when metal-level data is unavailable). All HTTP methods – GET, POST, PUT, PATCH, DELETE, HEAD, OPTIONS with request body support. Request body support – send JSON, XML, or any data inline or from file with automatic Content-Type detection. IPv4/IPv6 aware – the resolver and TLS inspector report both the address and its family. TLS insights – certificate CN, expiry countdown, cipher suite, and protocol version are captured automatically. Multiple output modes – rich waterfall view, compact single-line summaries, or -metrics-only for scripting. JSON export – persist full step data (including redirect chains) for later processing. Extensible – clean Protocol interfaces for DNS, TLS, timing, visualization, and export so you can plug in custom behavior. Example: Brian #2: 10 Smart Performance Hacks For Faster Python Code Dido Grigorov A few from the list Use math functions instead of operators Avoid exception handling in hot loops Use itertools for combinatorial operations - huge speedup Use bisect for sorted list operations - huge speedup Michael #3: FastRTC The Real-Time Communication Library for Python: Turn any python function into a real-time audio and video stream over WebRTC or WebSockets. Features

Slow Movie Player Steamboat Willie timelapse demo. Play a movie on an eInk display over the course of days and weeks instead of hours! Runs on Raspberry Pi with ffmpeg, Python, and PIL Based on Tom Whitwell's Slow Movie Player. John Park Learn Guide coming soon. Visit the Adafruit shop online - http://www.adafruit.com ----------------------------------------- LIVE CHAT IS HERE! http://adafru.it/discord Subscribe to Adafruit on YouTube: http://adafru.it/subscribe New tutorials on the Adafruit Learning System: http://learn.adafruit.com/ -----------------------------------------

In this special episode, we're broadcasting live from SpeckleCon 2025 in London, where the future of construction technology is being written in real-time. We sat down with some of the biggest names in AEC tech to talk about the one thing everyone's finally paying attention to: data.We hear from Suffolk Construction and Pomerlau on turning BIM chaos into usable data, MultiConsult's Morten on giving engineers superpowers with Python, Martin Day's warning that we're all horses before the industrial revolution, Oliver Thomas on why small firms will beat the giants in the AI race, and Speckle's Dimitrie and Virginia on their push to become the data platform that finally fixes this broken industry.Key Takeaways:Data accessibility is the new battleground - visibility matters more than authoring toolsGeneral contractors are leading the charge on data infrastructure• Off-the-shelf LLMs don't work well for AEC without fine-tuningThe visualization industry is getting disrupted by AI right now•Open source doesn't mean free, but it does mean you own your exit strategyOutcome-based pricing is coming for construction softwareThe market for design seats might be 50% smaller than we think once AI hits

Today we're digging into the Model Context Protocol, or MCP. Think LSP for AI: build a small Python service once and your tools and data show up across editors and agents like VS Code, Claude Code, and more. My guest, Den Delimarsky from Microsoft, helps build this space and will keep us honest about what's solid versus what's just shiny. We'll keep it practical: transports that actually work, guardrails you can trust, and a tiny server you could ship this week. By the end, you'll have a clear mental model and a path to plug Python into the internet of agents. Episode sponsors Sentry AI Monitoring, Code TALKPYTHON NordStellar Talk Python Courses Links from the show Den Delimarsky: den.dev Agentic AI Programming for Python Course: training.talkpython.fm Model Context Protocol: modelcontextprotocol.io Model Context Protocol Specification (2025-03-26): modelcontextprotocol.io MCP Python Package (PyPI): pypi.org Awesome MCP Servers (punkpeye) GitHub Repo: github.com Visual Studio Code Docs: Copilot MCP Servers: code.visualstudio.com GitHub MCP Server (GitHub repo): github.com GitHub Blog: Meet the GitHub MCP Registry: github.blog MultiViewer App: multiviewer.app GitHub Blog: Spec-driven development with AI (open source toolkit): github.blog Model Context Protocol Registry (GitHub): github.com mcp (GitHub organization): github.com Tailscale: tailscale.com Watch this episode on YouTube: youtube.com Episode #527 deep-dive: talkpython.fm/527 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Dan and Chris unpack whether today's surge in AI deployment across enterprise workflows, manufacturing, healthcare, and scientific research signals a lasting transformation or an overhyped bubble. Drawing parallels to the dot-com era, they explore how technology integration is reshaping industries, affecting jobs, and even influencing human cognition, ultimately asking: is this a bubble, or just a fizzy new phase of innovation?Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks: Powell says that, unlike the dotcom boom, AI spending isn't a bubble: ‘I won't go into particular names, but they actually have earnings'Sponsors:Outshift by Cisco - The open source collective building the Internet of Agents. Backed by Outshift by Cisco, AGNTCY gives developers the tools to build and deploy multi-agent software at scale. Identity, communication protocols, and modular workflows—all in one global collaboration layer. Start building at AGNTCY.org.Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiFabi.ai - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.aiUpcoming Events: Join us at the Midwest AI Summit on November 13 in Indianapolis to hear world-class speakers share how they've scaled AI solutions. Don't miss the AI Engineering Lounge, where you can sit down with experts for hands-on guidance. Reserve your spot today!Register for upcoming webinars here!

What if the most valuable part of your research isn't the paper, but the package that made it possible? In this episode, we talk with Leah Wasser, Executive Director and Founder of pyOpenSci, a nonprofit working to make scientific Python more inclusive, reproducible, and discoverable.We explore what “open science” really means in practice: transparent workflows that others can rerun, review, and extend. Leah explains how pyOpenSci's peer review process helps turn lab scripts into reliable, citable Python packages with better documentation, testing, and credit through the Journal of Open Source Software (JOSS).We also unpack how AI is reshaping scientific coding—its potential to speed up work, and the need for careful human oversight to maintain accuracy and trust.Connect with Leah on the following platforms:Github: https://github.com/lwasserLinkedIn: https://www.linkedin.com/in/leahawasser/Slack: https://www.pyopensci.org/handbook/community/slack.html___If you found this podcast helpful, please consider following us!Start Here with Pybites: https://pybit.esDeveloper Mindset Newsletter: https://pybit.es/newsletter

What are techniques for writing maintainable Python code? How do you make your Python more readable and easier to refactor? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder's Weekly articles and projects.

** AWS re:Invent 2025 Dec 1-5, Las Vegas - Register Here! **Learn how Anyscale's Ray platform enables companies like Instacart to supercharge their model training while Amazon saves heavily by shifting to Ray's multimodal capabilities.Topics Include:Ray originated at UC Berkeley when PhD students spent more time building clusters than ML modelsAnyscale now launches 1 million clusters monthly with contributions from OpenAI, Uber, Google, CoinbaseInstacart achieved 10-100x increase in model training data using Ray's scaling capabilitiesML evolved from single-node Pandas/NumPy to distributed Spark, now Ray for multimodal dataRay Core transforms simple Python functions into distributed tasks across massive compute clustersHigher-level Ray libraries simplify data processing, model training, hyperparameter tuning, and model servingAnyscale platform adds production features: auto-restart, logging, observability, and zone-aware schedulingUnlike Spark's CPU-only approach, Ray handles both CPUs and GPUs for multimodal workloadsRay enables LLM post-training and fine-tuning using reinforcement learning on enterprise dataMulti-agent systems can scale automatically with Ray Serve handling thousands of requests per secondAnyscale leverages AWS infrastructure while keeping customer data within their own VPCsRay supports EC2, EKS, and HyperPod with features like fractional GPU usage and auto-scalingParticipants:Sharath Cholleti – Member of Technical Staff, AnyscaleSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Чтобы научиться программировать и разбираться в тонкостях Python 3.12 записывайтесь на базовый курс Learn Python — https://clck.ru/3MuShF  Ведущие – Григорий Петров и Михаил Корнеев Ссылки выпуска: Курс Learn Python — https://learn.python.ru/advanced Канал Миши в Telegram — https://t.me/tricky_python Канал Moscow Python в Telegram — https://t.me/moscow_python Все выпуски — https://podcast.python.ru Митапы Moscow Python — https://moscowpython.ru Канал Moscow Python на Rutube — https://rutube.ru/channel/45885590/ Канал Moscow Python в VK — https://vk.com/moscowpythonconf Курс «Основы Python» от Learn Python — это отличный старт для новичков в программировании. За несколько уроков вы освоите базовый синтаксис, научитесь работать с данными и получите первый опыт для успешного старта карьеры в ИТ. Подробности: https://clck.ru/3MuShF

This interview was recorded for the GOTO Book Club.Read the full transcription of the interview here:https://gotopia.tech/episodes/387Prof. Andreas Zeller - Faculty at CISPA Helmholtz Center for Information Security & Author of "The Debugging Book"Clare Sudbery - Independent Technical CoachRESOURCESAndreashttps://bsky.app/profile/andreaszeller.bsky.socialhttps://www.linkedin.com/in/andreaszellerhttps://andreas-zeller.infoClarehttps://bsky.app/profile/claresudbery.bsky.socialhttps://www.madetech.com/podcasthttps://insimpleterms.blogLinkshttps://www.debuggingbook.orghttps://github.com/uds-se/debuggingbookhttps://www.st.cs.uni-saarland.de/ddDESCRIPTIONProgramming education has a critical blind spot: while we extensively teach code creation, we barely scratch the surface of testing and give almost no attention to debugging—despite debugging consuming half of all software development time.In this conversation with Clare Sudbery, Prof. Andreas Zeller argues that systematic debugging skills and modern automated debugging tools are the "ugly stepchild" of programming that nobody wants to discuss, yet debugging represents the biggest business risk and time sink in software development.RECOMMENDED BOOKSAndreas Zeller • The Debugging Book • https://www.debuggingbook.orgSy Brand • Building a Debugger • https://amzn.to/4cWWr84Nora Sandler • Writing a C Compiler • https://amzn.to/3Z6SMhUInspiring Tech Leaders - The Technology PodcastInterviews with Tech Leaders and insights on the latest emerging technology trends.Listen on: Apple Podcasts SpotifyBlueskyTwitterInstagramLinkedInFacebookCHANNEL MEMBERSHIP BONUSJoin this channel to get early access to videos & other perks:https://www.youtube.com/channel/UCs_tLP3AiwYKwdUHpltJPuA/joinLooking for a unique learning experience?Attend the next GOTO conference near you! Get your ticket: gotopia.techSUBSCRIBE TO OUR YOUTUBE CHANNEL - new videos posted daily!

Cisco Workflows is a new platform that makes network automation easier, smarter, and safer. On today’s episode, sponsored by Cisco, we get introduced to Cisco Workflows by Stephen Orr, Distinguished Solutions Engineer; and Reid Butler, Director of Product Management. They break down how Workflows helps you ditch repetitive tasks, roll out changes faster, and plug... Read more »

Cisco Workflows is a new platform that makes network automation easier, smarter, and safer. On today’s episode, sponsored by Cisco, we get introduced to Cisco Workflows by Stephen Orr, Distinguished Solutions Engineer; and Reid Butler, Director of Product Management. They break down how Workflows helps you ditch repetitive tasks, roll out changes faster, and plug... Read more »

Send us a textWe talk about JABBERWOCKY, Terry Gilliam's first solo directing project and a movie that definitely exists.

SyFy Channel's crowning achievement in goofy movie knock-offs gets a brief summary: BOA VS. PYTHON!   Aside from some interesting star power, no nonsense pacing & making its low-budget work for its already sarcastic nature, where does this crossover franchise even rank among other B-movie franchises?   Inbetween the sequels summary, you'll also get to hear some other quips and clips from the 2004 TV ratings smash hit!  

Intro topic: Asymmetric ReturnsNews/Links:NanoChat by Andrej Karpathyhttps://github.com/karpathy/nanochatPydantic AIhttps://www.marktechpost.com/2025/03/25/pydanticai-advancing-generative-ai-agent-development-through-intelligent-framework-design/1000th Starlink this yearhttps://spaceflightnow.com/2025/05/16/live-coverage-spacex-plans-morning-launch-of-starlink-satellites-from-california/ChatGPT Apps SDKhttps://openai.com/index/introducing-apps-in-chatgpt/Book of the ShowPatrickThe Will of the Many by James Islingtonhttps://amzn.to/43IfU8QJasonInterview with DHH (Founder of Ruby on Rails)https://www.youtube.com/watch?v=vagyIcmIGOQPatreon Plug https://www.patreon.com/programmingthrowdown?ty=hTool of the ShowPatrickFactoriohttps://www.factorio.com/ Jasonnip.io Topic: Workflow OrchestratorsWhyBatch jobs (embarrassingly parallel)Long-running tasks (e.g. transcoding video)Checkpointing/resumingHowMessage QueuesContainerizationWorker Pools & AutoscalingHistory & BackfillSteps to run workflows:Containerize the workflow definition and send to the cloudContainerize all the individual tasksSubmit job(s)ExamplesAirflowLegacy but dominantDagsterGreat UX for python developersTemporal: https://temporal.io/The new hotnessRayLow-level but very powerfulKubeflowDesigned for ML workflows, integrated dashboard ★ Support this podcast on Patreon ★

In this episode of MPR, we are catching up with you guys on Texas Carpet Fest, Reptilandia, and some thoughts on the carpet python community. MPR Network SocialsFB: https://www.facebook.com/MoreliaPythonRadioMorelia Pic of the Week: IG: YouTube: https://www.youtube.com/channel/UCtrEaKcyN8KvC3pqaiYc0RQEmail: moreliapythonradio@gmail.com Merch store: https://teespring.com/stores/mprnetworkPatreon: https://www.patreon.com/moreliapythonradio ★ Support this podcast on Patreon ★

Aeroview (https://aeroview.io/) Marc on LinkedIn (https://www.linkedin.com/in/mhweiner/) Alice for Snowflake (https://alice.dev/alice-snowflake/) Mike on X (https://x.com/dominucco) Mike on BlueSky (https://bsky.app/profile/dominucco.bsky.social) Coder on X (https://x.com/coderradioshow) Show Discord (https://discord.gg/k8e7gKUpEp) Alice & Custom Dev (https://alice.dev) Mike's Recent Omakub Blog Post (https://dominickm.com/omakhub-review/)

In this episode, Matt and Mike compare JavaScript and Python for building LLM-powered chatbots. They explore how each ecosystem handles tool calling, type safety, performance, and framework support — from TypeScript's tight end-to-end types to Python's dominance in data and ML. They also discuss architecture patterns that mix the best of both worlds, helping teams choose the right stack for scalable, efficient AI projects. Show Notes: https://www.htmlallthethings.com/podcast/javascript-vs-python-which-is-better-for-building-llm-chatbots Powered by CodeRabbit - AI Code Reviews: https://coderabbit.link/htmlallthethings Use our Scrimba affiliate link (https://scrimba.com/?via=htmlallthethings) for a 20% discount!! Full details in show notes.

In our latest episode, Robby and Tim talk with Will McGugan, creator of the Rich and Textual open source projects and founder of Textualize and Toad (not yet released), about the challenges of turning beloved open-source projects into real businesses. Despite Rich and Textual's huge adoption in the Python community, he says he waited too long to monetize, focused too much on technical perfection, and tried to build infrastructure before a killer product. He also burned himself out and wishes he had simplified and hired earlier.McGugan believes the terminal is a neglected but essential interface, prized for speed and flow. Rich and Textual modernized terminal output, but monetizing open-core dev tools proved difficult. His new project, Toad, aims to be a universal AI front-end for the terminal - open-source, protocol-driven, and able to plug into different agent back ends like Claude and others. The goal: seamless workflows and modern UX in the environment developers already live in.Big takeaways: monetize early, ship a killer app sooner, don't overcomplicate structure, and avoid grinding yourself into the ground.

Topics covered in this episode: The PSF has withdrawn a $1.5 million proposal to US government grant program A Binary Serializer for Pydantic Models T-strings: Python's Fifth String Formatting Technique? Cronboard Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. 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: PEP 810: Explicit lazy imports, has been unanimously accepted by steering council Lean TDD book will be written in the open. TOC, some details, and a 10 page introduction are now available. Hoping for the first pass to be complete by the end of the year. I'd love feedback to help make it a great book, and keep it small-ish, on a very limited budget. Joke: You are so wrong!

Five years ago, a CFO's main focus was cutting costs and boosting efficiency, but that conversation has dramatically shifted, with artificial intelligence (AI) now topping the priority list. In this episode of Blood, Sweat & Balance Sheets, host Mike Whitmire sits down with Andrew Moses, Associate Director at Cross Country Consulting, to dive into the evolving role of the modern CFO and the urgent need to adopt AI.They'll unpack why AI is no longer a "nice to have," but an essential budget item. You'll learn:How finance leaders can overcome the challenge of implementing AI, especially when general-purpose tools like Copilot and Python fall short for accounting-specific tasks.The critical difference between general-purpose and purpose-built AI solutions that seamlessly integrate with existing accounting systems.How to view AI as an investment not just in technology, but in your people.This discussion will provide a clear path for companies to effectively and easily adopt solutions purpose-built for the accounting function, making AI a practical reality.

Morse code transcription: vvv vvv Houses without lounges are a reality for renters Egypts Grand Museum opens, displaying Tutankhamun tomb in full for first time Where might Andrew live on the Sandringham estate Hair transplants, finasteride and hair systems Welcome to the world of hair restoration Andrew Why Sarah Ferguson, Beatrice and Eugenie cant escape the taint of family scandal Andrew should answer Jeffrey Epstein questions in US, Democrats say Newspaper headlines Downfall of a prince and something completely Python A line in the sand the fence dividing residents in Sandbanks Halloween 2025 Jade, Demi Lovato and Megan Thee Stallion reveal their costumes Cruise cancelled following death of woman left behind on island

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. Episode sponsors Posit NordStellar Talk Python Courses Links from the show Hugo Bowne-Anderson: x.com Vanishing Gradients Podcast: vanishinggradients.fireside.fm Fundamentals of Dask: High Performance Data Science Course: training.talkpython.fm Building LLM Applications for Data Scientists and Software Engineers: maven.com marimo: a next-generation Python notebook: marimo.io DevDocs (Offline aggregated docs): devdocs.io Elgato Stream Deck: elgato.com Sentry's Seer: talkpython.fm The End of Programming as We Know It: oreilly.com LorikeetCX AI Concierge: lorikeetcx.ai Text to SQL & AI Query Generator: text2sql.ai Inverse relationship enthusiasm for AI and traditional projects: oreilly.com Watch this episode on YouTube: youtube.com Episode #526 deep-dive: talkpython.fm/526 Episode transcripts: talkpython.fm Theme Song: Developer Rap

How do you deploy your Python application without getting locked into an expensive cloud-based service? This week on the show, Michael Kennedy from the Talk Python podcast returns to discuss his new book, "Talk Python in Production."

In this conversation with Malte Ubl, CTO of Vercel (http://x.com/cramforce), we explore how the company is pioneering the infrastructure for AI-powered development through their comprehensive suite of tools including workflows, AI SDK, and the newly announced agent ecosystem. Malte shares insights into Vercel's philosophy of "dogfooding" - never shipping abstractions they haven't battle-tested themselves - which led to extracting their AI SDK from v0 and building production agents that handle everything from anomaly detection to lead qualification. The discussion dives deep into Vercel's new Workflow Development Kit, which brings durable execution patterns to serverless functions, allowing developers to write code that can pause, resume, and wait indefinitely without cost. Malte explains how this enables complex agent orchestration with human-in-the-loop approvals through simple webhook patterns, making it dramatically easier to build reliable AI applications. We explore Vercel's strategic approach to AI agents, including their DevOps agent that automatically investigates production anomalies by querying observability data and analyzing logs - solving the recall-precision problem that plagues traditional alerting systems. Malte candidly discusses where agents excel today (meeting notes, UI changes, lead qualification) versus where they fall short, emphasizing the importance of finding the "sweet spot" by asking employees what they hate most about their jobs. The conversation also covers Vercel's significant investment in Python support, bringing zero-config deployment to Flask and FastAPI applications, and their vision for security in an AI-coded world where developers "cannot be trusted." Malte shares his perspective on how CTOs must transform their companies for the AI era while staying true to their core competencies, and why maintaining strong IC (individual contributor) career paths is crucial as AI changes the nature of software development. What was launched at Ship AI 2025: AI SDK 6.0 & Agent Architecture Agent Abstraction Philosophy: AI SDK 6 introduces an agent abstraction where you can "define once, deploy everywhere". How does this differ from existing agent frameworks like LangChain or AutoGPT? What specific pain points did you observe in production that led to this design? Human-in-the-Loop at Scale: The tool approval system with needsApproval: true gates actions until human confirmation. How do you envision this working at scale for companies with thousands of agent executions? What's the queue management and escalation strategy? Type Safety Across Models: AI SDK 6 promises "end-to-end type safety across models and UI". Given that different LLMs have varying capabilities and output formats, how do you maintain type guarantees when swapping between providers like OpenAI, Anthropic, or Mistral? Workflow Development Kit (WDK) Durability as Code: The use workflow primitive makes any TypeScript function durable with automatic retries, progress persistence, and observability. What's happening under the hood? Are you using event sourcing, checkpoint/restart, or a different pattern? Infrastructure Provisioning: Vercel automatically detects when a function is durable and dynamically provisions infrastructure in real-time. What signals are you detecting in the code, and how do you determine the optimal infrastructure configuration (queue sizes, retry policies, timeout values)? Vercel Agent (beta) Code Review Validation: The Agent reviews code and proposes "validated patches". What does "validated" mean in this context? Are you running automated tests, static analysis, or something more sophisticated? AI Investigations: Vercel Agent automatically opens AI investigations when it detects performance or error spikes using real production data. What data sources does it have access to? How does it distinguish between normal variance and actual anomalies? Python Support (For the first time, Vercel now supports Python backends natively.) Marketplace & Agent Ecosystem Agent Network Effects: The Marketplace now offers agents like CodeRabbit, Corridor, Sourcery, and integrations with Autonoma, Braintrust, Browser Use. How do you ensure these third-party agents can't access sensitive customer data? What's the security model? "An Agent on Every Desk" Program Vercel launched a new program to help companies identify high-value use cases and build their first production AI agents. It provides consultations, reference templates, and hands-on support to go from idea to deployed agent

Most AI agent frameworks are backend-focused and written in Python, which introduces complexity when building full-stack AI applications with JavaScript or TypeScript frontends. This gap makes it harder for frontend developers to prototype, integrate, and iterate on AI-powered features. Mastra is an open-source TypeScript framework focused on building AI agents and has primitives such as The post Building AI Agents on the Frontend with Sam Bhagwat and Abhi Aiyer appeared first on Software Engineering Daily.

What is Chapel? This week, Technology Now explores the programming language, Chapel. We ask what it is, how it was designed, and we explore why people would use it instead of some of the more established languages.This is Technology Now, a weekly show from Hewlett Packard Enterprise. Every week, hosts Michael Bird and Aubrey Lovell look at a story that's been making headlines, take a look at the technology behind it, and explain why it matters to organizations.About Brad Chamberlain:https://www.linkedin.com/in/brad-chamberlain-3ab358105 Sourceshttps://www.britannica.com/biography/Ada-Lovelacehttps://www.adalovelaceinstitute.org/about/https://cdn.britannica.com/31/172531-050-E009D42C/portion-Charles-Babbage-Analytical-Engine-death-mill-1871.jpghttps://commons.wikimedia.org/wiki/File:PunchedCardsAnalyticalEngine.jpghttps://www.mpg.de/female-pioneers-of-science/Ada-Lovelace

One small but fatal flaw of most LLMs?

Host Eric Chou talks with Jeff Kala, co-author of the newly released “Network Automation Cookbook 2nd Edition,” to discuss his book and the experiences that led him from networking to network automation author. They discuss Jeff’s learning style and why it was helpful when working on his book. Lastly, they dig into Jeff’s predictions on... Read more »

Host Eric Chou talks with Jeff Kala, co-author of the newly released “Network Automation Cookbook 2nd Edition,” to discuss his book and the experiences that led him from networking to network automation author. They discuss Jeff’s learning style and why it was helpful when working on his book. Lastly, they dig into Jeff’s predictions on... Read more »

Tune in to Colliers' Marty Mooradian sharing how curiosity about tech, coding, and AI is reshaping brokerage strategies and driving smarter deals in CRE.The Crexi Podcast connects CRE professionals with industry insights built for smart decision-making. In each episode, we explore the latest trends, innovations and opportunities shaping commercial real estate, because we believe knowledge should move at the speed of ambition and every conversation should empower professionals to act with greater clarity and confidence.  In this episode of The Crexi Podcast, host Shanti Ryle sits down with Marty to discuss his extensive experience and strategies in the commercial real estate sector. Marty shares his background in multifamily brokerage, his journey from political campaign fundraising to real estate, and his move to Colliers to build out their East Coast multifamily team. The conversation delves into Marty's approach to digital marketing, his venture into coding, and the use of AI tools to streamline real estate processes. Additionally, Marty provides insights on the current real estate market in Central Virginia, the impact of economic trends, and strategies for managing deals and building a successful brokerage team. This episode is packed with valuable information for anyone interested in commercial real estate, technology, and market strategies.Meet Marty Mooradian: Multifamily Broker ExtraordinaireMarty's Passion for Coding and LanguagesMarty's Journey in Commercial Real EstateChallenges and Lessons in BrokerageBuilding a Team at ColliersFinding a Niche in the Multifamily MarketThe Importance of Market MindsetEmbracing Technology in Real EstateBuilding a Web App: The Struggles and TriumphsFinding Zen in Real Estate and CodingThe AI Revolution: No Need to Code Every LineFrom DJing to Python: Automating TasksCreating a Virtual Assistant for BusinessThe Future of AI in Real EstateThe Importance of Coding KnowledgeCurrent Trends in the Central Virginia MarketChallenges and Creativity in Deal MakingAdvice for Future SuccessConclusion and Contact InformationFor show notes, past guests, and more CRE content, please check out Crexi's blog.Looking to stay ahead in commercial real estate? Visit Crexi to explore properties, analyze markets, and connect with opportunities nationwide. About Marty Mooradian:Marty is a seasoned multifamily broker with extensive experience in transacting assets in the $5 million to $30 million range. His accomplishments are many, including receiving the “Largest Deal Award” in the Carolina region of Marcus & Millichap. These accolades underscore his dedication and expertise in the real estate industry.Beyond his professional achievements, Marty embraces a wide array of passions. He has ventured into the world of coding, self-teaching himself Python and Ruby on Rails. He also has a deep appreciation for language and culture. He is currently immersed in learning two Armenian dialects and mastering the intricacies of the Armenian alphabet.Marty began his brokerage career with Marcus & Millichap, working in the multifamily sector for over 6 years. He possesses a significant expertise in digital marketing, utilizing innovative strategies to enhance online presence and engagement. His skills in this area have been instrumental in driving business growth and fostering stronger client relationships. For show notes, past guests, and more CRE content, please check out Crexi's blog.Looking to stay ahead in commercial real estate? Visit Crexi to explore properties, analyze markets, and connect with opportunities nationwide. Follow Crexi:https://www.crexi.com/​ https://www.crexi.com/instagram​ https://www.crexi.com/facebook​ https://www.crexi.com/twitter​ https://www.crexi.com/linkedin​ https://www.youtube.com/crexi

Building a UI in Python usually means choosing between "quick and limited" or "powerful and painful." What if you could write modern, component-based web apps in pure Python and still keep full control? NiceGUI, pronounced "Nice Guy" sits on FastAPI with a Vue/Quasar front end, gives you real components, live updates over websockets, and it's running in production at Zauberzeug, a German robotic company. On this episode, I'm talking with NiceGUI's creators, Rodja Trappe and Falko Schindler, about how it works, where it shines, and what's coming next. With version 3.0 releasing around the same time this episode comes out, we spend the end of the episode celebrating the 3.0 release. Episode sponsors Posit Agntcy Talk Python Courses Links from the show Rodja Trappe: github.com Falko Schindler: github.com NiceGUI 3.0.0 release: github.com Full LLM/Agentic AI docs instructions for NiceGUI: github.com Zauberzeug: zauberzeug.com NiceGUI: nicegui.io NiceGUI GitHub Repository: github.com NiceGUI Authentication Examples: github.com NiceGUI v3.0.0rc1 Release: github.com Valkey: valkey.io Caddy Web Server: caddyserver.com JustPy: justpy.io Tailwind CSS: tailwindcss.com Quasar ECharts v5 Demo: quasar-echarts-v5.netlify.app AG Grid: ag-grid.com Quasar Framework: quasar.dev NiceGUI Interactive Image Documentation: nicegui.io NiceGUI 3D Scene Documentation: nicegui.io Watch this episode on YouTube: youtube.com Episode #525 deep-dive: talkpython.fm/525 Episode transcripts: talkpython.fm Theme Song: Developer Rap

Topics covered in this episode: Cyclopts: A CLI library * The future of Python web services looks GIL-free* * Free-threaded GC* * Polite lazy imports for Python package maintainers* Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: Cyclopts: A CLI library A CLI library that fixes 13 annoying issues in Typer Much of Cyclopts was inspired by the excellent Typer library. Despite its popularity, Typer has some traits that I (and others) find less than ideal. Part of this stems from Typer's age, with its first release in late 2019, soon after Python 3.8's release. Because of this, most of its API was initially designed around assigning proxy default values to function parameters. This made the decorated command functions difficult to use outside of Typer. With the introduction of Annotated in python3.9, type-hints were able to be directly annotated, allowing for the removal of these proxy defaults. The 13: Argument vs Option Positional or Keyword Arguments Choices Default Command Docstring Parsing Decorator Parentheses Optional Lists Keyword Multiple Values Flag Negation Help Defaults Validation Union/Optional Support Adding a Version Flag Documentation Brian #2: The future of Python web services looks GIL-free Giovanni Barillari “Python 3.14 was released at the beginning of the month. This release was particularly interesting to me because of the improvements on the "free-threaded" variant of the interpreter. Specifically, the two major changes when compared to the free-threaded variant of Python 3.13 are: Free-threaded support now reached phase II, meaning it's no longer considered experimental The implementation is now completed, meaning that the workarounds introduced in Python 3.13 to make code sound without the GIL are now gone, and the free-threaded implementation now uses the adaptive interpreter as the GIL enabled variant. These facts, plus additional optimizations make the performance penalty now way better, moving from a 35% penalty to a 5-10% difference.” Lots of benchmark data, both ASGI and WSGI Lots of great thoughts in the “Final Thoughts” section, including “On asynchronous protocols like ASGI, despite the fact the concurrency model doesn't change that much – we shift from one event loop per process, to one event loop per thread – just the fact we no longer need to scale memory allocations just to use more CPU is a massive improvement. ” “… for everybody out there coding a web application in Python: simplifying the concurrency paradigms and the deployment process of such applications is a good thing.” “… to me the future of Python web services looks GIL-free.” Michael #3: Free-threaded GC The free-threaded build of Python uses a different garbage collector implementation than the default GIL-enabled build. The Default GC: In the standard CPython build, every object that supports garbage collection (like lists or dictionaries) is part of a per-interpreter, doubly-linked list. The list pointers are contained in a PyGC_Head structure. The Free-Threaded GC: Takes a different approach. It scraps the PyGC_Head structure and the linked list entirely. Instead, it allocates these objects from a special memory heap managed by the "mimalloc" library. This allows the GC to find and iterate over all collectible objects using mimalloc's data structures, without needing to link them together manually. The free-threaded GC does NOT support "generations” By marking all objects reachable from these known roots, we can identify a large set of objects that are definitely alive and exclude them from the more expensive cycle-finding part of the GC process. Overall speedup of the free-threaded GC collection is between 2 and 12 times faster than the 3.13 version. Brian #4: Polite lazy imports for Python package maintainers Will McGugan commented on a LI post by Bob Belderbos regarding lazy importing “I'm excited about this PEP. I wrote a lazy loading mechanism for Textual's widgets. Without it, the entire widget library would be imported even if you needed just one widget. Having this as a core language feature would make me very happy.” https://github.com/Textualize/textual/blob/main/src/textual/widgets/__init__.py Well, I was excited about Will's example for how to, essentially, allow users of your package to import only the part they need, when they need it. So I wrote up my thoughts and an explainer for how this works. Special thanks to Trey Hunner's Every dunder method in Python, which I referenced to understand the difference between __getattr__() and __getattribute__(). Extras Brian: Started writing a book on Test Driven Development. Should have an announcement in a week or so. I want to give folks access while I'm writing it, so I'll be opening it up for early access as soon as I have 2-3 chapters ready to review. Sign up for the pythontest newsletter if you'd like to be informed right away when it's ready. Or stay tuned here. Michael: New course!!! Agentic AI Programming for Python I'll be on Vanishing Gradients as a guest talking book + ai for data scientists OpenAI launches ChatGPT Atlas https://github.com/jamesabel/ismain by James Abel Pets in PyCharm Joke: You're absolutely right

Fedora 43 arrives with polish, new spins, and a smarter installer; and one decision the rest of the Linux world should pay attention to.Sponsored By:Managed Nebula: Meet Managed Nebula from Defined Networking. A decentralized VPN built on the open-source Nebula platform that we love. 1Password Extended Access Management: 1Password Extended Access Management is a device trust solution for companies with Okta, and they ensure that if a device isn't trusted and secure, it can't log into your cloud apps. CrowdHealth: This open enrollment, take your power back. Join CrowdHealth to get started today for $99 for your first three months using code UNPLUGGED.Unraid: A powerful, easy operating system for servers and storage. Maximize your hardware with unmatched flexibility. Support LINUX UnpluggedLinks:

Infostealer Targeting Android Devices This infostealer, written in Python, specifically targets Android phones. It takes advantage of Termux to gain access to data and exfiltrates it via Telegram. https://isc.sans.edu/diary/Infostealer%20Targeting%20Android%20Devices/32414 Attackers exploit recently patched Adobe Commerce Vulnerability CVE-2025-54236 Six weeks after Adobe's emergency patch, SessionReaper (CVE-2025-54236) has entered active exploitation. E-Commerce security company SanSec has detected multiple exploit attempts. https://sansec.io/research/sessionreaper-exploitation Patch for BIND and unbound nameservers CVE-2025-40780 The Internet Systems Consortium (ISC.org), as well as the Unbound project, patched a flaw that may allow for DNS spoofing due to a weak random number generator. https://kb.isc.org/docs/cve-2025-40780 WSUS Exploit Released CVE-2025-59287 Hawktrace released a walk through showing how to exploit the recently patched WSUS vulnerability https://hawktrace.com/blog/CVE-2025-59287