Building a Raw BitTorrent Client from Scratch in Python

Whether you’re a seasoned developer or just curious about scientific visualization, VTK’s ecosystem continues to evolve in exciting ways. In our latest blog, we take a look at how VTK supports development across a wide range of programming languages: from its C++ roots to modern bindings in Python, JavaScript, .NET languages, and beyond. 🌐 No matter your background, Python scripter, web developer, JVM enthusiast, or .NET builder, you’ll find ways to tap into VTK’s powerful visualization pipeline. 👉 Dive into the full story and see examples in multiple languages: https://ow.ly/j1SK50Yq7EY #VTKVisualization #PythonVisualization #TechInnovation #DataVisualization #ScientificVisualization

Ever wondered how Rust lets you write multithreaded code without the classic nightmares of race conditions and deadlocks? I just published a deep-dive article covering everything you need to know about concurrency and parallelism in Rust. Here’s what the article walks through: → The real difference between concurrency and parallelism → Spawning and managing threads with std::thread::spawn → Sharing data safely using Arc, Mutex, and RwLock → Message passing with mpsc channels for clean, lock-free communication → Coordinating threads with multi-channel patterns → async/await basics and how executors work → How Rust’s Send and Sync traits catch threading bugs at compile time, not at 3 AM in production Rust doesn’t just make concurrency possible. It makes it safe by default. The compiler is your co-pilot, and the ownership model eliminates entire categories of bugs before your code ever runs. Whether you’re coming from C++, Go, Python, or just getting started with systems programming, this guide breaks it all down with clear explanations and practical code examples. Link in the comments 👇 #Rust #RustLang #Concurrency #Parallelism #Multithreading #SystemsProgramming #SoftwareEngineering #Programming #CodingTips #ThreadSafety #AsyncAwait #RustProgramming #LearnRust #WebDev #BackendDevelopment #DevCommunity #TechArticle #CodeNewbie #SoftwareDevelopment #OpenSource

We’re proud to be a sponsor at PyTexas Foundation 2026. If you're building modern Python apps, this hands-on lab is worth your time: Building a Full-Stack FastAPI App with open source DocumentDB via Docker You’ll build a full-stack app using FastAPI and open source DocumentDB, all running in Docker—focused on rapid prototyping, scalable APIs, and clean dev workflows. This one is very practical: containerized development, CI/CD patterns, and real-world debugging in reproducible environments. https://msft.it/6045Q7RZL #DocumentDB #Python #AzureDocumentDB

A while back, a post was making the rounds about Claude writing a C compiler. Writing a C compiler is a well-researched problem. What happens if you wander off the beaten track a bit? Some initial observations from developing the Splic compiler below. Some obvious, some perhaps less so. (1) Encapsulate domain knowledge in skills. Splic is based on two-level types, a somewhat niche concept, and its application to compilers is a relatively recent research. The very first commit in the repo was a two-level types skill. It took some effort to get the papers into a format easily digestible by the agent but it paid off handsomely. I even had Claude push back on a suggestion of mine that did not follow one of the typing rules. It is also useful to include links to the original sources so the agent can look up further detail when needed. (2) Create design documents. An example would be the syntax reference in splic. These get referenced a lot and it's handy to be able to explicitly feed them into context at any point. (3) Plan mode with a detailed initial prompt is your friend. I have to admit I only glance at the generated plan. Instead, I directly drill into known-to-be-tricky parts with some pointed interrogation. Manipulation of de Bruijn indices/levels is the prime example. Having domain knowledge is still very useful in this stage, to catch errors early or when the agent asks for clarification. (4) Agents do not take advantage of strong types as much as they could. When refactoring code, the agent often looks up all the use sites by reading a bunch of source files and grepping a lot. This might be a sensible approach when working with Python or JavaScript. However, in a Rust-based project, asking it to "just make the change and chase up the bloody compiler errors" is faster, more reliable, and easier on token consumption. All this applies to Claude Code using mostly the Sonnet 4.6 model. Splic repo: https://lnkd.in/eyj6m72z

The low code/ no code ecosystem that thrived for the last 20 years is dying as architecture. The idea of building a custom proprietary runtime that only works for specific vendor is no longer a solution. Now you can generate apps of javascript, C#, Python,….. using new generation of platforms that are not proprietary. It helps you generate the code not own your app through monthly subscription forever. Even if the old platforms added AI generators, why sticking to proprietary if I can be free? That’s the challenge for platforms like Power Apps. Either to start new from scratch or lose the market. #nocode #lowcode #powerapps

🧠 I built my own programming language — GreyMatter! Inspired by Grey Matter from Ben 10 (yes, the alien genius 😄), I created a fully functional interpreted programming language built in Python using SLY. GreyMatter supports: ✅ Variables, loops, and conditionals ✅ User-defined functions with FEEDBACK (return values) ✅ String utilities like WAYBIG() (uppercase) and NANOMECH() (lowercase) ✅ Time utilities via PARADOX.SLEEP() and PARADOX.UNIDATE() ✅ A memory system called BRAINSTORM ✅ Even experimental @WEB_SEARCH and @AI query features! The whole interpreter works through Lexical Analysis → Parsing → AST Generation → Runtime Execution. This project taught me how real-world languages like Python and JavaScript actually work under the hood. If you're a CS student or a curious developer, building your own language is one of the most valuable things you can do. 🔗 GitHub: github.com/Abineshabee #Programming #Python #ComputerScience #OpenSource #LanguageDesign #StudentProject #Interpreter #Ben10 #GreyMatter #BuildInPublic

𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝗞𝗮𝗶𝗿𝗼! About a year and a half ago, my friends and I started building a programming language. We'd been writing systems-level code across C++, Rust, and lower-level tooling for long enough to have strong opinions about what was missing. C++ gives you performance and the richest library ecosystem in systems programming, but the language fights you at every turn undefined behavior, header hell, decades of accumulated complexity. Rust solves the safety problem but introduces real cognitive overhead and a syntax that trades readability for compiler appeasement. We wanted something that didn't force that tradeoff. So we built Kairo a statically typed systems programming language with bidirectional C++ interoperability, readability-first syntax, and a memory safety model that gives you both manual and automatic memory tracking without fighting a borrow checker. 𝗪𝗵𝗲𝗿𝗲 𝘄𝗲 𝗮𝗿𝗲 𝗻𝗼𝘄 The project has come a long way. We shipped a Stage 0 bootstrap compiler, then used it to build a Stage 1 self-hosted compiler; Kairo is being written in Kairo itself! The language, toolchain, and ecosystem are actively under development and roughly halfway to a production release. 𝗪𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗞𝗮𝗶𝗿𝗼 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 - Bidirectional C++ FFI call C++ from Kairo and Kairo from C++, no bindings layer required. - Readability-first design. Code should be readable by default, not after three months of pattern memorization. - BCIR/AMT memory safety model manual and automatic memory tracking with safety guarantees, without Rust's borrow checker annoyance. - Planned interop expansion to Python and Rust. - Full access to the existing C++ library ecosystem from day one. 𝗖𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗼𝗿𝘀 :Arnav Goyal , Dhruvan Kartik and Me 𝗟𝗶𝗻𝗸𝘀 - Website: https://www.kairolang.org - Github: https://lnkd.in/gZEdW2Gi We're a three-person team and the project has 360+ GitHub stars. If this interests you, a star, an issue report, or a contribution all help. #CompilerDev #Compiler #tech #buildinpublic #SystemsEngineering

Tired of switching windows or using online compilers to test your Python code? 🐍 I love the blazing-fast Helix editor but couldn't find a good live-runner. So, I built a fully local solution: HelixPythonLiveRunner. How it makes coding faster: ⚡ Instant Feedback: Auto-runs your script the second you hit save (Ctrl+S). 💻 Side-by-Side View: Code in Helix on the left, live output on the right. 🛠️ Zero Bloat: Uses 100% standard Python and Windows Terminal no heavy plugins. 🚀 Fully Local: Ditch the online tools and code efficiently on your own machine. Why I built this: I wanted a fast, distraction-free way to learn and practice Python all inside Helix editor. Perfect for Python learners and rapid prototyping. Just clone the repo, run the setup, and start coding. 🔗 Check it out here: https://lnkd.in/g_fxvXYc #Python #HelixEditor #WindowsTerminal #DeveloperTools #OpenSource

My new favorite free tool 😎 This new tool is the best. It’s essentially VS code and RStudio wrapped into one, giving you an easy and interactive way to write your Python code and keep track of any variables or objects you’ve already created. For anyone that’s familiar with RStudio and wished Python had an equivalent IDE, this is the best thing ever. It makes you feel WAY more in control of your data. I can realistically say that this IDE is what I’ll use for most of my data driven coding projects in the future. Not a sponsored post, I just love this thing (and it’s free) Follow for more free coding resources ✅ #code #coding #tech #learntocode #datascience

📌 You can streamline your research workflow by mastering modern coding tools and sharing them effectively. Together these practices boost reproducibility, cut development time, and enhance your publication record, delivering up to a year of research efficiency over the next few projects. ✓ 🖥️ Install Visual Studio Code, follow the free Python in VS Code tutorial, and write a simple data script. ✓ 🐙 Create a GitHub repository, push scripts weekly, use issues to track analysis steps. ✓ 📦 Package your workflow with Cookiecutter, publish template on GitHub, and host documentation on ReadTheDocs for community use. 🟢 Which tool has most improved your research reproducibility? #ResearchTools #Reproducibility #OpenScience #Python #GitHub