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Изходен канал @clockstackwheels · Post #1131 · 2.08

Тут незаметно подъехала свежая статистика по разработчикам от Stackoverflow. Каждый год я думаю о том, что надо бы принять участие в опросе, и каждый год пропускаю его. Судя по всему, его не рекламируют по почте, не присылают никаких уведомлений, не продвигают. В итоге мы получаем абсурдную картину, когда в статистике по странам разработчики из России представлены на одном уровне с Нигерией. Хотя понятно, что айти сектор в России очень развит и влияет на глобальные процессы (взять тот же Kotlin). Так что, на эту статистику стоит смотреть, как на данные по США и чуть-чуть Германии. Ещё довольно высоко стоит Индия, но мы-то знаем :) Ладно. Принципиально нового по сравнению с предыдущими годами почти нет. Три года назад я делал анализ графиков, чтобы дать ответ на вопрос: «Какой язык программирования учить?». С тех пор общие тренды остались плюс-минус такими же: вся [американская] разработка до сих пор сидит на Винде и пишет на JavaScript, потому что нет выхода, много использует проприетарщины и коммерческих облаков от монополистов. В статистике Web-фреймворков React вдвое популярнее у разработчиков, чем jQuery, хотя, вроде как, 73% сайтов до сих пор на jQuery. Вывод понятен: значительная часть этих сайтов в сети не поддерживается, никакой активной разработки по ним нет. Это, кстати, важная причина, по которой не стоит использовать аргументы вроде: «На PHP до сих пор весь интернет, поэтому язык востребован». Стоит отметить, что среди профессионалов наконец C# стал самым популярным языком с нормальной системой типов, если не считать TypeScript. Позиции Java уверенно падают который год. А ASPNET Core самый популярный Web-фреймворк с нормальной системой типов (но так было и раньше, даже три года назад). Остальное ожидаемо: PostgreSQL, Docker, VS Code в топах по использованию. Ну, и большая секция про ИИ. Почти все используют LLM, но почти все просто общаются в чатах, а не применяют какой-нибудь агентный режим. 66% опрошенных сказали, что в ИИ их фрустрирует приближенность ответа к правильному, но всё-таки не до конца («AI solutions that are almost right, but not quite»). И почти половина отмечает, что дебаг нейросетевого кода отнимает больше времени. Хотя тут, мне кажется, эффект в том, что дольше дебажить код, который писал не ты, и не важно, ИИ там или другой разработчик. Я кстати и сам после первых восторгов от Cursor немного поубавил свой пыл: реально большой проект на C# он не умеет правильно читать и понимает происходящее там довольно посредственно. DeepSeek, ChatGPT, Claude Sonnet — за всеми нужно внимательно следить и править их ошибки, ловить галлюцинации, не позволять творить дичь. Я бы сказал, что в моей рабочей практике ИИ это просто очень быстрый поиск и агрегация материала по тому, как что-то сделать. Но делать нужно самому. #dev

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@githubtrending · Post #15603 · 05.04.2026 г., 12:30

#cplusplus LiteRT-LM is Google's free, high-speed tool for running large language models like Gemma 4 on phones, computers, Raspberry Pi, and more, with GPU boosts, vision/audio support, and tool use for smart apps. It powers AI in Chrome, Pixel Watch, and Chromebook—try it fast via CLI command on Linux, macOS, Windows, or Pi without coding. You benefit by easily deploying fast, private on-device AI for apps, prototyping, or edge projects, saving time and cloud costs. https://github.com/google-ai-edge/LiteRT-LM

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@githubtrending · Post #15554 · 12.03.2026 г., 11:30

#cplusplus LiteRT is Google's free framework for running fast machine learning and generative AI on phones, computers, and web without cloud help. It uses GPU and NPU for up to 2x speed boosts, zero-copy data handling, and async execution on Android, iOS, Linux, and more, plus easy PyTorch model conversion. You benefit by building quick, private apps like real-time image editing or chatbots that work offline on everyday devices, saving battery and boosting performance. https://github.com/google-ai-edge/LiteRT

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@githubtrending · Post #15550 · 09.03.2026 г., 11:30

#cplusplus Godot RE Tools let you fully recover Godot projects from APK, PCK, or EXE files by extracting resources, decompiling GDScripts, recreating the project.godot file, and converting resources to original formats. It supports Godot 4.x, 3.x, and 2.x via easy GUI drag-and-drop or command line. This helps you restore lost projects quickly, edit games for modding, or regain work from exports/backups without starting over. https://github.com/GDRETools/gdsdecomp

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@githubtrending · Post #15508 · 20.02.2026 г., 12:00

#cplusplus Electrobun lets you build ultra-fast, tiny desktop apps in TypeScript for macOS, Windows, and Linux. Start with `npx electrobun init` for quick templates, get ~12-14MB bundles using system webviews and Bun runtime, and send tiny 14KB updates via bsdiff patches. It offers typed RPC for main-webview communication, fast startup under 50ms, and full tools for building, signing, and shipping. You benefit by coding once in familiar TypeScript, skipping Electron's bloat or Tauri's Rust, to ship performant apps in minutes with easy distribution and low user downloads. https://github.com/blackboardsh/electrobun

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@githubtrending · Post #15501 · 18.02.2026 г., 12:00

#cplusplus Pyrite64 is an open-source visual editor and engine for creating 3D games that run on real Nintendo 64 consoles or accurate emulators. It uses community libraries like Libdragon and tiny3d instead of proprietary Nintendo SDKs, avoiding legal complications. The tool features automatic toolchain installation, Blender model importing, HDR and bloom rendering, and a node-graph editor for scripting. You benefit by building authentic N64 games without wrestling with outdated 1990s development tools—the integrated environment handles compilers, dependencies, and asset management automatically, letting you focus on game creation rather than technical setup. https://github.com/HailToDodongo/pyrite64

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@githubtrending · Post #15428 · 22.01.2026 г., 12:00

#cplusplus FlashMLA is DeepSeek's optimized attention library that makes AI models run faster and use less memory. It works with advanced NVIDIA GPUs to speed up how language models process information, achieving up to 660 trillion floating-point operations per second. The library supports both dense and sparse attention modes, meaning it can focus on important tokens while skipping less relevant ones, reducing computational waste. For you, this means faster AI responses, lower costs for running large language models, and better performance on tasks like chatbots and code generation. The technology is open-source and integrates with popular AI frameworks like PyTorch and Hugging Face, making it accessible for developers building next-generation AI applications. https://github.com/deepseek-ai/FlashMLA

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@githubtrending · Post #15186 · 02.10.2025 г., 08:30

#cplusplus Tile Language (tile-lang) is a simple, Python-like programming language that helps you write fast GPU and CPU code for tasks like matrix multiplication and attention mechanisms. It uses a smart compiler based on TVM to optimize your code automatically, so you get high performance without dealing with complex low-level details. Tile-lang supports many devices including NVIDIA and AMD GPUs and offers examples and tools to help you write, test, and profile your kernels easily. Installing it is straightforward via pip or from source. This lets you develop efficient AI and math kernels faster and with less effort, improving productivity and performance on modern hardware. https://github.com/tile-ai/tilelang

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@githubtrending · Post #15179 · 29.09.2025 г., 11:30

#cplusplus Media Downloader is a user-friendly program that helps you download videos and playlists from many websites using a simple graphical interface. It supports multiple tools like yt-dlp and others through extensions, allowing you to download media in different formats and do many downloads at once or batch downloads from files. You can also manage playlist subscriptions and use it in many languages. It works on Windows, macOS, and Linux, with portable and installer versions available. This tool saves you time and effort by making media downloads easy, organized, and flexible, letting you watch offline without interruptions or internet issues. https://github.com/mhogomchungu/media-downloader

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@githubtrending · Post #15148 · 17.09.2025 г., 11:30

#cplusplus Monad is a fast, scalable Layer 1 blockchain fully compatible with Ethereum's EVM, allowing you to run Ethereum smart contracts without changes. It improves speed by separating consensus (agreement on transaction order) from execution (processing transactions), enabling parallel transaction execution and reaching 10,000 transactions per second with 1-second finality. Monad uses a custom EVM and a special database (MonadDb) optimized for parallel state access, reducing delays. This means you get much faster, cheaper transactions while keeping Ethereum compatibility, making it easier for developers and users to adopt and benefit from high performance and scalability. https://github.com/category-labs/monad

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@githubtrending · Post #15146 · 15.09.2025 г., 11:30

#cplusplus This project helps you fix batteries that get locked by their Battery Management System (BMS) when it detects a fault, which sometimes happens by mistake or after the problem is fixed. Instead of throwing away a good battery, you can use open-source tools to reset the lock and save money. You set up an Arduino device and software on your computer (either a simple Windows program or Python-based) to communicate with the battery and unlock it. This way, you can repair and reuse batteries that would otherwise be wasted, reducing costs and environmental impact. https://github.com/mnh-jansson/open-battery-information

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@githubtrending · Post #14974 · 19.07.2025 г., 12:00

#cplusplus ik_llama.cpp is an improved version of llama.cpp that runs faster on CPUs and hybrid GPU/CPU setups. It supports many new advanced quantization methods, which help models use less memory and run more efficiently. It also offers better performance for special models like DeepSeek and MoE, with faster prompt processing and token generation. You can run it on various hardware, including Android, and it has features to control where model data is stored (CPU or GPU). This means you get quicker AI responses and can handle bigger or more complex models smoothly on your computer or device[2][1][4]. https://github.com/ikawrakow/ik_llama.cpp

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@githubtrending · Post #14857 · 23.06.2025 г., 13:00

#cplusplus The LEGO Island portable project recreates the original LEGO Island game (version 1.1, English) so it can run on many platforms like Windows, Linux, macOS, and even the web, without changing the gameplay or adding new features. It replaces Windows-only parts with cross-platform libraries like SDL3 to make the game work smoothly on different systems. You need an original copy of LEGO Island to use it, and while developer builds exist, user-friendly versions are still being made. This means you can enjoy the classic LEGO Island game on modern devices and operating systems that it wasn’t originally designed for, preserving the nostalgic experience across platforms[2]. https://github.com/isledecomp/isle-portable

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