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  • 2026-07-06 09:38
    Avec l'IA générative et agentique, l'adaptive learning devient enfin concret : diagnostic, personnalisation à grande échelle et inclusion pour la réussite de tous les étudiants.
  • 2026-07-02 08:55
    Une critique pragmatique du modèle des concours administratifs. L'article démontre que les épreuves académiques actuelles ne répondent plus aux réalités du terrain. Il propose de valoriser l'intellige.
  • 2026-06-18 10:15
    I saw this dodecahedron with an Islamic-inspired pattern designed by Taj Ragoo . As soon as I saw it, I knew I had to make one. I studied the pattern, wrote some Python, and made myself a PDF. I cut it out, folded it, glued it together, and now I have one of my own: I love that this elegantly combines two pure geometric forms: the Platonic dodecahedron (12 uniform pentagons), and an Islamic pattern using five-pointed stars. Looking closely, details emerge: Each face has ten small stars in a ring. I've lightened them a bit in the front face here. At the center of each face is a ten-pointed star (highlighted in red), made of two overlaid five-pointed stars. The real genius of the pattern is at the corners. I've highlighted one in blue. It's a star made of the same parts as the central ten-pointed star, but there are only nine points. It works because three pentagons lying flat touching at a point occupy 324 degrees, leaving a 36-degree gap. When the dodecahedron is folded together, the gap is closed. 36 degrees is exactly one-tenth of a complete 360-degree circle, so exactly one point of the ten-pointed star is missing, leaving a perfect nine-pointed star using the same shapes, spread over the corners of three pentagons. Beautiful! If ..
  • 2026-06-11 11:28
    Whether you're building chatbots, training computer vision models, or analyzing business data, choosing the right AI framework can make or break your project. Python has become the dominant language for AI and machine learning development, and the ecosystem of frameworks supporting this work has matured significantly. The right framework choice depends on what you're building. A production recommendation system has different requirements than a research prototype. A chatbot powered by large language models (LLMs) needs different tools than a fraud detection system analyzing tabular data. Let's explore seven essential frameworks and where each excels so you can find the best AI framework for your specific project. What is an AI framework? AI frameworks are pre-built libraries and tools that handle the complex mathematics, data structures, and computational operations underlying AI and machine learning models. Rather than implementing neural networks or gradient descent from scratch, AI frameworks provide abstractions that let you focus on model architecture, data preparation, and business logic. These frameworks generally fall into three categories: Deep learning frameworks like TensorFlow, PyTorch, and Keras specialize ..
  • 2026-06-10 00:00
    Three months ago I saw that PyCharm shipped with a “ Full Line Completion ” plugin that “uses a local deep learning model to suggest entire lines of code”. These suggestions manifest as whole-line suggestions after you start typing and can be accepted with Tab . Essentially auto-complete for entire lines. I decide to test this functionality. I started by writing import urllib3 , created a new line, and then typed u and received a suggested completion for the line marked below with a dashed border . I was not impressed by the result: import urllib3 u rllib3 . disable_warnings ( urllib3 . exceptions . InsecureRequestWarning ) Accepting this line would mean that any insecure requests made with urllib3 would not result in a user-visible warning. I didn't accept this suggestion and then began to instantiate a urllib3.PoolManager and what I feared would come next was confirmed: import urllib3 urllib3 . PoolManager ( cert_reqs = 'CERT_NONE' , The suggestion offered to disable certificate verification ( CERT_NONE ) which would make every request made by the PoolManager susceptible to monster-in-the-middle (MITM) attacks. Accepting this code as-is would mean the program I am writing has a severe vulnerability. ..
  • 2026-06-10 00:00
    I have been a staunch supporter of Open Source for a long time, including experiments in funding it . I'm a true believer in the idea that Open Source always wins in the long run, but not automatically and not quickly. Right now it is being stressed by AI slop, shifting contributor dynamics, the falling cost of producing code, and large companies learning to close doors behind them. A lot of that battle today is manipulation of the narrative. Opinion makers on social media and in business circles increasingly frame access as irresponsibility. That is why the EU's DMA matters, even if many people (including myself) reflexively hate EU regulation. Apple's fight over delayed AI features in Europe is not about Brussels being annoying: it is about whether users can access their own devices and data. The phone is yours, the data is yours, yet Apple decides who may reach it and takes the agency away from you and then tries to make that sound like it is in your interest (supposedly it's for your safety and security). The closer you get to the core of AI, the more this shows up. Anthropic has every financial incentive to restrict what people can do with Mythos and Fable , and they wrap those restrictions in safety and (national) security ..
  • 2026-06-04 00:00
    Jochen Deister is a lawyer who codes for fun. He has years of Python behind him and no intention of ever being hired to program. Three months ago, Rust was just a name to him, the language for "the big shots" with a notoriously steep learning curve. Then he built a JSON parser from scratch in Rust, and it ran faster than the equivalent in Python on every dataset he tested, up to 3.5x faster on some. "Holy F" he reacted when he saw the results. Six weeks of work produced: A from-scratch JSON parser , no parsing libraries Benchmarks beating Python's standard json module (C-accelerated in CPython), up to 3.5x faster Close to 30 commits in the final week alone, each one a single performance step A deliberate 78-error refactor, with the compiler as the guide to a faster implementation A new default language: Rust is now the one he reaches for first Here's how it happened. The gap Jochen learned to code on a Commodore VIC-20 with six kilobytes of RAM, then a C64, then a stint in assembly and Turbo Pascal when the bottleneck moved from memory to speed. Then life took him into law and academia, and he forgot all of it until he picked Python back up years ago. Python suited him, but it hid the machine. "Python ..
  • 2026-05-24 18:15
    Like many, I started using chatbots when GPT whatever-version-it-was came out and took the world by storm. It was really not very good at the time (compared to today's top-end chatbots), but it was clearly the start of something. But things moved quickly, and I couldn't quite catch up. I was busy with, you know, actual work, family, and life. Then I started hearing lots of new terms, lots of new acronyms. I didn't know what they were. I still don't know what most of them are. Then it was all about agents. I remember clearly thinking to myself: "Is this really any different from the ChatGPT-type chatbots?" And here's where this new series comes in. I decided to dive into agents and created a few. One of them is a learning tutor agent that I personalised to suit me. I gave the agent all my tutorials and books. I gave the agent all the articles I wrote about my views on learning and technical writing. I asked the agent to figure out from all this how I like to learn, how I like to communicate. I teach the way I like to learn, so it's fine to put my teaching style in the mix. Then, I had a good long chat with my learning tutor agent to make sure we're on the same page. I gave a name to my agent (I named all my agents!) My personalised ..
  • 2026-05-21 21:23
    I know how I like to learn new things. Over the years, I figured out what works for me and what doesn't. If you read my articles or attend my courses, then you know how I like to learn since I teach in the same way. The challenge when learning something new is finding resources that are just right for me. And that's not easy. I know I can learn things better and quicker with resources that fit my style well, but you can't always find these resources. I recently got particularly annoyed learning about the biomechanics of sprinting I do have non-Python interests, yes because all three textbooks I read, and lots of the online writing in this field, are just, let's say, not great. But I now found the solution. After many decades of learning in the same way, I have now upgraded how I learn thanks to my new tutor, Priya. Yes, I gave her a name. No, she's not a real person. Priya is my personalised tutor agent. I'll tell you all about her below. And you'll experience her teaching, too (not on the Python articles, though, I'll keep writing those the old-fashioned way.) I'll tell you more about this below, too, but let me first tell you why this works for me. My Tutor, My Style I've been thinking about the way I learn and teach for many years, ..
  • 2026-04-17 09:55
    Adobe is trying to turn Firefly into more than an image generator. Firefly AI Assistant is Adobe's attempt to turn Creative Cloud into an agent-driven workflow layer. Instead of bouncing between Photoshop, Premiere Pro, Illustrator, Lightroom, and Express, users describe the result they want, and Firefly handles the app hopping in the background. That is a much bigger move than adding another AI button inside one Adobe app. It extends the direction Adobe has already been pushing with features like Photoshop with AI , but at a broader workflow level. What Adobe Announced At the center of the announcement is a simple idea: one prompt should be able to trigger a multi-step workflow across several Creative Cloud apps while preserving context between sessions. Adobe laid that out in both its official blog post and its newsroom release . The pitch is straightforward: spend less time figuring out which app, panel, or workflow to use, and more time describing the end result. Adobe is positioning the assistant to work across apps including: Photoshop Premiere Pro Express Lightroom Illustrator additional Creative Cloud apps over time It will also ship with prebuilt Creative Skills , reusable task flows for common ..
  • 2026-04-13 09:31
    YouTube Premium just got more expensive in the US again. According to The Verge , the individual plan now costs $15.99 per month , up from $13.99 . The family plan is now $26.99 , up from $22.99 . Premium Lite, the ad-free plan without YouTube Music, goes from $7.99 to $8.99 . This latest hike appears to apply to the US only, while many international users already saw YouTube Premium price increases in late 2024. That is the headline. The bigger story is how often YouTube has changed the price and the product around it. From Music Key to YouTube Red to YouTube Premium, the paid offering has been moving in one direction for years. The 2026 Price Hike The new monthly US prices are: YouTube Premium Individual: $15.99, up from $13.99 YouTube Premium Family: $26.99, up from $22.99 Premium Lite: $8.99, up from $7.99 The increase applies immediately for new subscribers, while existing users are being notified ahead of their next billing cycle. The standard individual plan is now $4 higher than it was at launch under the YouTube Premium name in 2018. Where It Started YouTube's paid subscription history is a little messy because the service has gone through three main eras. 1. YouTube Music Key, 2014 The ..
  • 2026-04-02 04:38
    I've been working on a set of interactive workshops on Python decorators and they are now available for free on the labs page of this site. There are 22 workshops in total, covering everything from the fundamentals of how decorators work through to advanced topics like the descriptor protocol, async decorators and metaclasses. The workshops are hosted on the Educates training platform and accessed through the browser, so there is nothing to install. An experiment in learning We are well into the age of AI at this point. Need to know how to write a decorator in Python? Just ask ChatGPT or Claude and you will get an answer in seconds. Want to refactor some code to use decorators? Let an AI agent do it for you. The tools are genuinely impressive and I use them myself every day. That said, as someone who spent years as a developer advocate helping people learn, the question that keeps coming up is whether there is still an appetite for actually learning how things work. Not just getting an answer, but understanding why the answer is what it is. Understanding the mechanics well enough that when the AI gives you something subtly wrong (and it will), you can spot it and fix it yourself. These workshops are my experiment in finding ..
  • 2026-03-03 09:06
    Adding AI to legacy code doesn't have to be a challenge. Many devs are hearing this right now: “We need to add AI to the app.” And for many of them, panic ensues. The assumption is that you have to rip your existing architecture down to its foundation. You start having nightmares about standing up complex microservices, massive AWS bills, and spending six months learning the intricate math behind vector embeddings. It feels like a monumental risk to your stable, production-ready codebase, right? Here's the current reality though: adding AI to an existing application doesn't actually require a massive rewrite. If you have solid software design fundamentals, integrating a Retrieval-Augmented Generation (RAG) pipeline is entirely within your reach. Here's how you do it without breaking everything you've already built. Get the Python Stack to do the Heavy Lifting You don't need to build your AI pipeline from scratch. The Python ecosystem has matured to the point where the hardest parts of a RAG pipeline are already solved for you. Need to parse massive PDFs? Libraries like docling handle it practically out of the box. Need to convert text into embeddings and store them? You let the LLM provider handle the embedding ..
  • 2026-02-06 13:00
    Tailwind CSS has changed how we build websites by using utility classes like text-center or bg-blue-500 directly in HTML. But as projects get bigger, the huge number of utilities can become overwhelming, leading to long class lists, slower development, and a constant need to look up class names. So how do we keep the speed and flexibility without getting buried under the class chaos? In this article, we'll explore five essential tools that can help you stay productive while working with Tailwind CSS. These tools will help you manage your classes better, speed up your workflow, and keep your code clean and maintainable. Let's check them out! 1. VSCode Extensions If you're using a code editor like VSCode , you should install the Tailwind CSS Intellisense . This extension provides intelligent suggestions as you type, helping you quickly find the right utility classes without having to remember them all. On top of that, the extension also offers features like linting for your Tailwind CSS code. This can significantly speed up your development process and reduce errors. Another extension that I would suggest is Tailwind Fold . It is another useful extension that helps you manage long class lists by allowing you to collapse ..
  • 2026-01-21 18:13
    We are thrilled to announce that Djangonaut Space, a mentorship program for contributing to Django, is open for applicants for our next cohort! 🚀 Djangonaut Space is holding a sixth session! This session will start on March 2nd, 2026. We are currently accepting applications until February 2nd, 2026 Anywhere on Earth . More details can be found in the website . Djangonaut Space is a free, 8-week group mentoring program where individuals will work self-paced in a semi-structured learning environment. It seeks to help members of the community who wish to level up their current Django code contributions and potentially take on leadership roles in Django in the future. “I'm so grateful to have been a part of the Djangonaut Space program. It's a wonderfully warm, diverse, and welcoming space, and the perfect place to get started with Django contributions. The community is full of bright, talented individuals who are making time to help and guide others, which is truly a joy to experience. Before Djangonaut Space, I felt as though I wasn't the kind of person who could become a Django contributor; now I feel like I found a place where I belong.” - Eliana, Djangonaut Session 1 Enthusiastic about contributing to Django but wondering ..
  • 2026-01-21 05:50
    Par un jugement de plein contentieux, le tribunal administratif rejette la requête d'une attachée d'État réclamant 3 113 €. Le juge écarte toute discrimination ou rupture du principe d'égalité.
  • 2026-01-16 13:00
    Picking the right WordPress plugins can make a clear difference in how your site works and how easy it is to maintain. In 2026, when tools, design trends, and online needs shift quickly, relying on strong, well-built plugins matters more than ever. With more than 50,000 options out there, it's tough to know which ones actually deliver the advanced features and dependable performance most projects now require. This article highlights eight plugins that consistently stand out for their practical features and the way they support real improvements in editing, layout control, and individual page sections. Tools like Brizy and wpDataTables show how far WordPress has evolved by making complex work easier and expanding what you can build. Across the board, these top WordPress plugins help improve performance, support SEO, streamline design, shorten workflows, automate tasks, and keep sites responsive on all devices. If you're looking for reliable ways to strengthen a current site or build something new in 2026, these eight options cover a wide span of needs without adding unnecessary complexity. Brizy Amelia wpDataTables MapSVG LayerSlider Slider Revolution IvyForms Essential Grid 1. Brizy – User-Friendly ..
  • 2025-12-18 18:50
    Thank You to Our Outgoing Directors We extend our gratitude to Thibaud Colas and Sarah Abderemane, who are completing their terms on the board. Their contributions shaped the foundation in meaningful ways, and the following highlights only scratch the surface of their work. Thibaud served as President in 2025 and Secretary in 2024. He was instrumental in governance improvements, the Django CNA initiative, election administration, and creating our first annual report . He also led our birthday campaign and helped with the creation of several new working groups this year. His thoughtful leadership helped the board navigate complex decisions. Sarah served as Vice President in 2025 and contributed significantly to our outreach efforts, working group coordination, and membership management. She also served as a point of contact for the Django CNA initiative alongside Thibaud. Both Thibaud and Sarah did too many things to list here. They were amazing ambassadors for the DSF, representing the board at many conferences and events. They will be deeply missed, and we are happy to have their continued membership and guidance in our many working groups. On behalf of the board, thank you both for your commitment to Django and the DSF. ..