Deleted articles cannot be recovered. Draft of this article would be also deleted. Are you sure you want to delete this article? Pythonコルーチンの開発プロセスと新旧コルーチンの深層分析 1. Pythonコルーチンの歴史的進化 Pythonの長い開発の歴史を通じて、コルーチンの実装はいくつかの大きな変更を経てきました。これらの変更を理解することは、Pythonの非同期プログラミングの本質をよりよく把握するのに役立ちます。 1.1 初期の探索と基本機能の導入 Python 2.5：このバージョンでは、ジェネレータに.send()、.throw()、.close()メソッドが導入されました。これらのメソッドの登場により、ジェネレータは単なるイテレータ以上のもの
GitHub - modelcontextprotocol/servers: Model Context Protocol Servers
Official integrations are maintained by companies building production ready MCP servers for their platforms. 21st.dev Magic - Create crafted UI components inspired by the best 21st.dev design engineers. 2slides - An MCP server that provides tools to convert content into slides/PPT/presentation or generate slides/PPT/presentation with user intention. ActionKit by Paragon - Connect to 130+ SaaS inte
Rust でも学べる関数型ドメイン駆動設計 - Domain Modeling Made Functional の読書感想文 - じゃあ、おうちで学べる
はじめに なぜ 2026 年に、2018 年出版の本を再読するのでしょうか。正直に言えば、『Architecture Modernization』の翻訳作業で DDD の概念が頻出し、「分かったつもり」の理解では訳せなくなったからです。初読から 7 年。関数型の視点で DDD を説明する本書を、今度こそ腹落ちさせたかった。 読む動機 『Domain Modeling Made Functional』は、DDD と関数型プログラミングを組み合わせたアプローチを解説する書籍です。 Domain Modeling Made Functional: Tackle Software Complexity with Domain-Driven Design and F# (English Edition) 作者:Wlaschin, ScottPragmatic BookshelfAmazon 著者の
Rustacean のための F# 入門
また、 F# の decimal 型は Rust には標準で存在しませんが、 5m という書き方をします。 数字の間に _ を入れて読みやすくすることができるのも同様です。 let num = 8_000_000; その他の型について ... F# の char は Rust の char に似ていますが、 前者が UTF-16 なのに対し、 Rust の char は UTF-32 で常に 4bytes です。これは、 Rust とは違い、 char の配列がほぼそのまま string として扱えることを示しています。 Rust の unit と F# の unit は両方とも () で表され、役割も同じです。 文字列型に関しては Rust には色々あるので、簡単な比較はできませんが、 string は immutable な char の配列で、 mutable に扱いたい場合は St
Tier 4 Support § Support for these targets is entirely experimental. If this target is provided by LLVM, LLVM may have the target as an experimental target, which means that you need to use Zig-provided binaries for the target to be available, or build LLVM from source with special configure flags. zig targets will display the target if it is available. This target may be considered deprecated by
We now live in a world where ML workflows (pre-training, post training, etc) are heterogeneous, must contend with hardware failures, are increasingly asynchronous and highly dynamic. Traditionally, PyTorch has relied on an HPC-style multi-controller model, where multiple copies of the same script are launched across different machines, each running its own instance of the application (often refer
Deconstructing prompt-based meta-tool architecture and context injection patterns for AI engineering - Claude’s Agent Skills system represents a sophisticated prompt-based meta-tool architecture that extends LLM capabilities through specialized instruction injection. Unlike traditional function calling or code execution, skills operate through prompt expansion and context modification to modify ho
Right now, asyncio is one of the trendier topics in Python, and rightfully so – It’s a great way to handle I/O-bound programs! When I was learning about asyncio, It took me a while to understand how it actually worked. But later, I came to find out that it’s basically just a really nice layer on top of Python Generators. In this article, I’m going to create a simplified version of asyncio using ju
An AI-native software engineer is one who deeply integrates AI into their daily workflow, treating it as a partner to amplify their abilities. This requires a fundamental mindset shift. Instead of thinking “AI might replace me” an AI-native engineer asks for every task: “Could AI help me do this faster, better, or differently?”. The mindset is optimistic and proactive - you see AI as a multiplier
Server-Sent Events: the alternative to WebSockets you should be using
When developing real-time web applications, WebSockets might be the first thing that come to your mind. However, Server Sent Events (SSE) are a simpler alternative that is often superior. Contents Prologue WebSockets? What is wrong with WebSockets Compression Multiplexing Issues with proxies Cross-Site WebSocket Hijacking Server-Sent Events Let’s write some code The Reverse-Proxy The Frontend The
Generators are an odd part of the JavaScript language. And some people find them a bit of a puzzle. You might be a successful developer for decades and never feel the need to reach for them. Which raises the question, if you can go so long without ever needing them, what are they good for? Generators have a funny syntax, too. They have these strange starred function definitions; you can’t define t
GitHub - taishi-i/awesome-ChatGPT-repositories: A curated list of resources dedicated to open source GitHub repositories related to ChatGPT and OpenAI API
awesome-chatgpt-api - Curated list of apps and tools that not only use the new ChatGPT API, but also allow users to configure their own API keys, enabling free and on-demand usage of their own quota. awesome-chatgpt-prompts - This repo includes ChatGPT prompt curation to use ChatGPT better. awesome-chatgpt - Curated list of awesome tools, demos, docs for ChatGPT and GPT-3 awesome-totally-open-chat
GitHub - langroid/langroid: Harness LLMs with Multi-Agent Programming
This is just a teaser; there's much more, like function-calling/tools, Multi-Agent Collaboration, Structured Information Extraction, DocChatAgent (RAG), SQLChatAgent, non-OpenAI local/remote LLMs, etc. Scroll down or see docs for more. See the Langroid Quick-Start Colab that builds up to a 2-agent information-extraction example using the OpenAI ChatCompletion API. See also this version that uses t
Update 1.90.2: The update addresses these issues. Update 1.90.1: The update addresses these issues. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the May 2024 release of Visual Studio Code. There are many updates in this version that we hope you'll like, some of the key highlights include: Editor tabs multi-select - Select and perform act
スマホでAIイラスト制作：DiscordからローカルStable Diffusionを操作する方法｜花笠
全国のにじジャーニーで元絵をつくりSDモデルでimg2imgしてAIイラストを制作している皆さんこんばんは。花笠です。 本日はDiscord上で、その「にじジャーニーで元絵をつくりSDモデルでimg2imgしてAIイラストを制作する」工程を完結させる方法を編み出したので紹介しますね。img2imgだけじゃなくてtxt2img機能も含めてるから、にじ使いじゃない人でも使えると思いますよ！ 作ってるうちに機能が変わってきたので結論として ・Discordでテキストを入力するとテキスト画像生成（txt2img） ・Discordで画像とテキストを入力すると画像から画像生成（img2img） ができるようになるよって記事です。 こういうのがスマホのDiscord内で作れる※にじジャーニーの使い方は全世界民がすでに知ってると思うから省略するよ。 ※コマンドプロンプトの基本的な使い方は先に理解すると良
Python behind the scenes #12: how async/await works in Python
Mark functions as async. Call them with await. All of a sudden, your program becomes asynchronous – it can do useful things while it waits for other things, such as I/O operations, to complete. Code written in the async/await style looks like regular synchronous code but works very differently. To understand how it works, one should be familiar with many non-trivial concepts including concurrency,
[Simon Tatham, initial version 2023-09-01, last updated 2025-03-25] [Coroutines trilogy: C preprocessor | C++20 native | general philosophy ] Introduction Why I’m so enthusiastic about coroutines The objective view: what makes them useful? Versus explicit state machines Versus conventional threads The subjective view: why do I like them so much? “Teach the student when the student is ready” They s
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Pythonの非同期処理: これだけは知っておきたい！ - Qiita
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