Podcasts about Python

RHLSTP Book Club #161 - Seriously Silly - The Life of Terry Jones - Richard chats to renowned comedy historian Robert Ross about his fabulous new biography of actor, writer, director and Python, Terry Jones. The topics includes what it's like to befriend a Python and how that friendship affects the writing of a biography, how comedy history can be a map for future comedians, how Jones' influence in the sketch group is perhaps underestimated, how the Python members could never have imagined that the sketch show they were embarking on would bind them for the rest of their lives, what a fine movie director he was, how he helped Rich get an A in his A level English, how his dementia affected his later years and how the new naked statue of Terry will be viewed by the people of the future.Buy the book here https://uk.bookshop.org/p/books/seriously-silly-the-life-of-terry-jones-the-authorised-biography-robert-ross/4553b8f600a0191aSUPPORT THE SHOW!See details of the RHLSTP LIVE DATES Watch our TWITCH CHANNELBecome a badger and see extra content at our WEBSITE Buy DVDs and books from GO FASTER STRIPE Hosted on Acast. See acast.com/privacy for more information.

В гостях выпуска Алексей Толстиков - кандидат физико-математических наук, руководитель Школы анализа данных Яндекса, эксперт в олимпиадах по программированию. Разговаривать мы, разумеется, будем про ШАД. Зачем когда-то (аж 18 лет назад) появилась Школа Анализа Данных? Как руководить большим направлением в компании, когда хочется писать образовательные программы и код? Зачем ШАДу взаимодействие с ВУЗами? Куда уходят выпускники ШАД? Как работает комьюнити выпускников? Сломаны ли процессы в современном образовании из-за бурного развития LLM? Стоит ли учиться в ШАД только ради "ачивки"? А чему вообще можно научиться в Школе Анализа Данных? Кто такие исследователи-разработчики? Не снижается ли радикально роль живого преподавателя с учётом того, что теперь легко можно взаимодействовать с ChatGPT-like моделями в интерактивном режиме? Можно ли реально "расти" без "боли"? Как поступить в ШАД, если математика была давно? Из каких этапов состоит поступление? Как готовиться к экзаменам? Обо всём этом в выпуске!Ссылки выпуска:ШАД (https://shad.yandex.ru)Все в ШАД - телеграм-канал с полезными материалами для подготовки к поступлению (https://t.me/vse_v_shad)Буду благодарен за обратную связь!Подписывайтесь на телеграм-канал "Стать специалистом по машинному обучению" (https://t.me/toBeAnMLspecialist)Обо мне (https://t.me/toBeAnMLspecialist/935)Мой телеграм для связи (https://t.me/kmsint)Ещё со мной можно связаться по электронной почте: kms101@yandex.ruЯ сделал бесплатный курс по созданию телеграм-ботов на Python и aiogram на Степике (https://stepik.org/120924). Присоединяйтесь, если хотите научиться разрабатывать телеграм-ботов и вообще вести проекты на Python!Также в соавторстве с крутыми разработчиками я пишу курс по продвинутой разработке телеграм-ботов с элементами микросервисной архитектуры (https://stepik.org/a/153850?utm_source=mlpodcast&utm_campaign=ep_76).Выразить благодарность можно добрым словом и/или донатом (https://www.tinkoff.ru/rm/kryzhanovskiy.mikhail11/NkwE718878/)

Episode #128 Of Daffy's Round Table!On this episode of Daffy's Round Table, I'm joined by Dominic Carbonneau from Dom's Reptiles, a highly respected breeder in the Morelia world. We talk all things Carpet Pythons, from species and locales to morphs and breeding strategies.Dom gives us a behind-the-scenes look at how he manages his animals, including his quarantine setup, nidovirus protocols, and how he handles common issues like mites without compromising the health of his snakes.Big thanks to Dom for coming on and sharing so much valuable knowledge!Huge thank you to Exo Terra for sponsoring this episode and supporting the podcast. Exo Terra makes top-quality products that help our reptiles feel at home!Follow Dominic on IG: https://www.instagram.com/domsreptiles/Follow The Reptile Rejects On IG: https://www.instagram.com/reptilerejects/Check out the Reptile Rejects Podcast: https://www.youtube.com/ ⁨@reptilerejects⁩ Check out my other channel: https://www.youtube.com/ ⁨@daffysreptiles⁩ If you enjoyed this episode please subscribe to Daffy's Round Table on whatever streaming platform you use! Follow Daffy: Instagram: @DaffysreptilesTwitter: @DaffysreptilesFacebook: Facebook.com/DaffysreptilesTiktok: @DaffysreptilesBusiness: daffysreptiles@gmail.com

Claire chatted to Kevin McAleer from kevsrobots about how to get started building robots at home. Kevin McAleer is a hobbyist robotics fanatic who likes to build robots, share videos about them on YouTube and teach people how to do the same. Kev has been building robots since 2019, when he got his first 3d printer and wanted to make more interesting builds. Kev has a degree in Computer Science, and because his day job is relatively hands-off, this hobby allows his creativity to have an outlet. Kev is a huge fan of Python and Micropython for embedded devices, and has a website - kevsrobots.com where you can learn more about how to get started in robotics. Join the Robot Talk community on Patreon: https://www.patreon.com/ClaireAsher  

Cesare e Marco esplorano il concetto di 'Duct Tape Programmer', una figura pragmatica nella programmazione che si concentra sulla consegna di software funzionante piuttosto che sulla perfezione. Discutono l'importanza del pragmatismo rispetto al perfezionismo, l'over-engineering nelle architetture moderne e forniscono esempi di come semplificare il codice possa portare a risultati migliori.

In a world of Rust, Go, and Python, why does C++ still matter? Dr. Gabriel Dos Reis joins Scott to explain how C++ continues to shape everything from GPUs and browsers to AI infrastructure. They talk about performance, predictability, and the art of balancing power with safety...and how the language's constant evolution keeps it relevant four decades in.

Gatekeeping. Discrimination. Whatever you call it, the Leftist Activists within Tech have a message for anyone who disagrees with them: “You are not welcome here!”More from The Lunduke Journal:https://lunduke.com/ This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit lunduke.substack.com/subscribe

Hey everyone, Alex here

In this Blind Abilities episode, Jeff Thompson talks with Jeff Bishop, president of BITS—Blind Information Technology Specialists—an all-volunteer organization empowering blind and low-vision individuals through accessible technology, community, and hands-on learning. Bishop outlines BITS' rapid growth, affordable memberships, and expanding reach across platforms like WhatsApp, Facebook, email lists, and mentoring channels. BITS offers high-impact training, including Python programming, Microsoft Office, Google Workspace, NVDA, and AI immersion courses—all with fully accessible materials and strong completion rates. Their partnerships with APH, Bookshare, NLS, Microsoft, and others ensure free resources and meaningful industry feedback opportunities, including paid participation in Microsoft's Project Empower. With free Remote Incident Manager (RIM) support, active mentoring, and a welcoming culture, BITS serves beginners and experts alike. As the group considers rebranding the "S" in BITS to Solutions, the mission remains clear: meeting people where they are and helping them thrive in their digital lives. Link to BITS

Episode SummaryIn this conversation, Robby sits down with software engineer and author Chris Zetter to explore what building a relational database from scratch can teach us about maintainability, architectural thinking, and team culture. Chris shares why documentation often matters more than perfectly shaped code, why pairing accelerates learning and quality, and why “boring technology” is sometimes the most responsible choice. Together they examine how teams get stuck in local maxima, how junior engineers build confidence, and how coding agents perform when asked to implement a database.Episode Highlights[00:01:00] What Makes Software MaintainableChris explains that well-maintained software is defined by how effectively it helps teams deliver value and respond to change. In some domains—like payroll systems—the maintainability burden shifts toward documentation rather than code organization.[00:03:50] Documentation vs. Code CommentsHe describes visual docs, system diagrams, and commit–ticket links as more durable sources of truth than inline comments, which tend to rot and discourage refactoring.[00:05:15] Rethinking Technical DebtChris argues that teams overuse the metaphor. He prefers naming the specific reason something is slow or brittle—like outdated libraries or rushed decisions—because that builds trust and clarity with product partners.[00:07:45] Where Core Debt Really LivesEarlier in his career he obsessed over long files; now he focuses on structural issues. Architecture, boundaries, and naming affect changeability far more than messy internals.[00:08:15] Pairing as the Default ToolChris loves pairing for its speed, clarity, and shared context. Remote pairing has removed obstacles like mismatched keyboard setups or cramped office seating. Tools like Tuple and Pop keep it smooth.[00:10:20] The Mob Tool and Fast Driver SwitchingHe explains how the Mob CLI tool makes switching drivers nearly instant, which keeps energy high and lets everyone work in their own editor environment, reducing friction and fatigue.[00:13:45] Pairing with Junior EngineersPairing helps newer developers avoid painful pull-request rework and builds confidence. But teams must balance pairing with opportunities for engineers to build autonomy.[00:20:50] Getting Feedback SoonerChris emphasizes speed of feedback: showing progress early to stakeholders prevents wasted days—and sometimes weeks—of heading in the wrong direction.[00:21:10] Boring Technology as a FeatureAfter being burned by abandoned frameworks, Chris champions predictable, well-supported tools for the big layers: language, framework, database. Novelty is great—but only in places where rollback is cheap.[00:23:20] Balancing Professional Development with Organizational NeedsDevelopers want experience with new technology; organizations want stability. Chris describes how leaders can channel curiosity safely and productively.[00:27:20] Build a Database ServerChris's book, Build a Database Server, is a practical, language-agnostic guide to building a relational database from scratch. It uses a test suite as a feedback loop so developers can experiment, refactor, and learn architectural trade-offs along the way.[00:31:45] What Writing the Book Taught HimCreating a database deepened his appreciation for Postgres maintainers. He highlights the number of moving parts—storage engine, type system, query planner, wire protocol—and how academic papers often skip hands-on guidance.[00:33:00] Experimenting with Coding AgentsChris tested coding agents by giving them the book's test suite. They passed many tests but produced brittle, incoherent architecture. Without a feedback loop for quality, the agents aimed only to satisfy test conditions—not build maintainable systems.[00:36:55] Escaping a Local Maxima Through a Design SprintChris shares a story of a team stuck maintaining a system that no longer fit business needs. A design sprint gave them space to reimagine the system, clarify naming, validate concepts, and identify which pieces were worth reusing.[00:40:40] Rewrite vs. RefactorHe leans toward refactor for large systems but supports small, isolated rewrites when boundaries are clear.[00:41:40] Building Trust in Legacy CodeWhen inheriting an old codebase, Chris advises starting with a small bug fix or UI tweak to understand deployment pipelines, test coverage, and failure modes before tackling bigger improvements.[00:43:20] Recommended ReadingChris recommends _Turn the Ship Around! for its lessons on empowering teams to act with intent instead of waiting for permission.Resources MentionedBuild a Database ServerChris Zetter's blogThe Mob Programming CLI ToolTuplePopTurn the Ship Around!Thanks to Our Sponsor!Turn hours of debugging into just minutes! AppSignal is a performance monitoring and error-tracking tool designed for Ruby, Elixir, Python, Node.js, Javascript, and other frameworks.It offers six powerful features with one simple interface, providing developers with real-time insights into the performance and health of web applications.Keep your coding cool and error-free, one line at a time! Use the code maintainable to get a 10% discount for your first year. Check them out! Subscribe to Maintainable on:Apple PodcastsSpotifyOr search "Maintainable" wherever you stream your podcasts.Keep up to date with the Maintainable Podcast by joining the newsletter.

Topics covered in this episode: Possibility of a new website for Django aiosqlitepool deptry browsr 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: Possibility of a new website for Django Current Django site: djangoproject.com Adam Hill's in progress redesign idea: django-homepage.adamghill.com Commentary in the Want to work on a homepage site redesign? discussion Michael #2: aiosqlitepool

Marimo is redefining what a Python notebook can do—bringing structure, version control, and interactivity together. In this episode, we chat with Akshay Agrawal, co-founder and CEO of Marimo, about how their reactive Python notebook fixes hidden state, keeps outputs in sync, and makes reproducible, reviewable code the norm.Akshay shares Marimo's origin story, how its reactive DAG turns notebooks into clean, Git-friendly tools, and why teams are ditching Jupyter-to-Streamlit pipelines for simpler, reactive workflows. We also dive into performance, data handling with pandas/Polars via Narwhals, and SQL reactivity with DuckDB.Join us in this insightful episode as we talk with Akshay about reproducibility, data workflows, and turning prototypes into shareable apps.For more info on Marimo, reach out to Akshay:Website: https://www.akshayagrawal.com/Github: https://github.com/akshaykaLinkedIn: https://www.linkedin.com/in/akshayka/X: https://x.com/akshaykagrawal______If you found this podcast helpful, please consider following us!Start Here with Pybites: https://pybit.esDeveloper Mindset Newsletter: https://pybit.es/newsletter

First Python refused to stop discriminatory policies & turned down $1.5 Million from the US Government. Now they have launched the “Python is for EVERYONE” campaign... but they don't actually mean “everyone”.More from The Lunduke Journal:https://lunduke.com/ This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit lunduke.substack.com/subscribe

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

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.

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

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

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.

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."

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.

One small but fatal flaw of most LLMs?

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