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  • Pythonの非同期処理: これだけは知っておきたい! - Qiita

    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

      Pythonの非同期処理: これだけは知っておきたい! - Qiita
    • ChatGPT deep researchに見る⁨⁩AIが自律的に考える未来 - LayerX エンジニアブログ

      こんにちは、LayerXプロダクトマネージャーの野畑(@isseinohata)です。 LayerXで生成AIプラットフォーム Ai Workforceの開発に従事しています。 getaiworkforce.com 2月3日にOpenAIが発表したAIエージェント「deep research」が大きな話題を呼んでいます。 openai.com 生成AIの領域では日々さまざまなプロダクトや新しい技術が登場していますが、その中でもdeep researchは単なるサービス自体の性能の高さに加え、それを実現する技術(人間のリサーチプロセスに近い思考を実現する技術)に対して、未来への大きなインパクトを感じさせる体験でした。 実際、deep researchの調査ログを眺めていると、あたかも人間が試行錯誤するように、自律的に計画→検索→読み込み→発見→方針変更を進めているような姿が見て取れます。 左

        ChatGPT deep researchに見る⁨⁩AIが自律的に考える未来 - LayerX エンジニアブログ
      • Don't write clean code, write CRISP code — Bitfield Consulting

        I’m sure we’re all in favour of “clean code”, but it’s one of those motherhood-and-apple-pie things that no one can reasonably disagree with. Who wants to write dirty code, unless maybe it’s for a porn site? The problem, of course, is that few of us can agree on what “clean code” means, and how to get there. A rule like “methods should only do one thing”, looks great on a T-shirt, but it’s not so

          Don't write clean code, write CRISP code — Bitfield Consulting
        • The Prompt Engineering Playbook for Programmers

          Developers are increasingly relying on AI coding assistants to accelerate our daily workflows. These tools can autocomplete functions, suggest bug fixes, and even generate entire modules or MVPs. Yet, as many of us have learned, the quality of the AI’s output depends largely on the quality of the prompt you provide. In other words, prompt engineering has become an essential skill. A poorly phrased

            The Prompt Engineering Playbook for Programmers
          • 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

              GitHub - modelcontextprotocol/servers: Model Context Protocol Servers
            • AWS Documentation MCP Server でAWSのFAQアシスタントを作成する - Taste of Tech Topics

              はじめに データ分析エンジニアの木介です。 AWSの公式ドキュメントで欲しい情報を探そうとしても、なかなか目的のページが見つからなかったりすることってありませんか? AWSから「AWS Documentation MCP Server」が公開されたため、本記事では、それを利用して、最新のAWSドキュメントに基づき、質問に回答してくれるFAQアシスタントの作成方法について紹介したいと思います。 MCP Serverの呼び出しには、Claude Desktop および dolphin-mcp を利用します。 github.com はじめに 概要 1. MCPとは MCPのしくみ 2. AWS Documentation MCP Serverとは Claude Desktop経由でAWS ドキュメントのFAQアシスタントを作成する dolphin-mcpでAWS ドキュメントのFAQアシスタント

                AWS Documentation MCP Server でAWSのFAQアシスタントを作成する - Taste of Tech Topics
              • research!rsc: Coroutines for Go

                This post is about why we need a coroutine package for Go, and what it would look like. But first, what are coroutines? Every programmer today is familiar with function calls (subroutines): F calls G, which stops F and runs G. G does its work, potentially calling and waiting for other functions, and eventually returns. When G returns, G is gone and F continues running. In this pattern, only one fu

                • Writing a C compiler in 500 lines of Python

                  A few months ago, I set myself the challenge of writing a C compiler in 500 lines of Python1, after writing my SDF donut post. How hard could it be? The answer was, pretty hard, even when dropping quite a few features. But it was also pretty interesting, and the result is surprisingly functional and not too hard to understand! There's too much code for me to comprehensively cover in a single blog

                  • 巨人の肩に乗る

                    本記事は 仮想通貨 Advent Calendar 2025 の24日目の記事です。 はじめに はじめまして、ymdと申します。普段は、株や暗号資産の分析をし、マーケットが盛り上がったときに落ちているお金を拾っています。 今年のAdvent Calendarを眺めていると、DEXの分析やLLMを活用した自動トレード戦略作成など、非常に有益な記事が目白押しです。 これらを見て思い出したのが、ニュートンの「巨人の肩に乗る」という言葉。本記事では、この精神に倣い、AIの力と先人の知見という2つの「肩」を借りながら、お金拾いの方法を探っていきます。 AIの肩に乗る AI駆動開発の3つのアプローチ AIを活用した開発には、大きく3つの方向性があります: 情報収集の自動化:論文や API ドキュメントの要約 戦略生成の自動化:複数のアプローチを並行生成 コーディングの自動化:コードそのものを AI に

                      巨人の肩に乗る
                    • LogLog Games

                      The article is also available in Chinese. Disclaimer: This post is a very long collection of thoughts and problems I've had over the years, and also addresses some of the arguments I've been repeatedly told. This post expresses my opinion the has been formed over using Rust for gamedev for many thousands of hours over many years, and multiple finished games. This isn't meant to brag or indicate su

                      • Announcing .NET 10 - .NET Blog

                        Today, we are excited to announce the launch of .NET 10, the most productive, modern, secure, intelligent, and performant release of .NET yet. It’s the result of another year of effort from thousands of developers around the world. This release includes thousands of performance, security, and functional improvements across the entire .NET stack-from languages and developer tools to workloads-enabl

                          Announcing .NET 10 - .NET Blog
                        • Changing std::sort at Google’s Scale and Beyond

                          TL;DR; We are changing std::sort in LLVM’s libcxx. That’s a long story of what it took us to get there and all possible consequences, bugs you might encounter with examples from open source. We provide some benchmarks, perspective, why we did this in the first place and what it cost us with exciting ideas from Hyrum’s Law to reinforcement learning. All changes went into open source and thus I can

                            Changing std::sort at Google’s Scale and Beyond
                          • 4 Pandas Anti-Patterns to Avoid and How to Fix Them

                            pandas is a powerful data analysis library with a rich API that offers multiple ways to perform any given data manipulation task. Some of these approaches are better than others, and pandas users often learn suboptimal coding practices that become their default workflows. This post highlights four common pandas anti-patterns and outlines a complementary set of techniques that you should use instea

                              4 Pandas Anti-Patterns to Avoid and How to Fix Them
                            • RFC 9562: Universally Unique IDentifiers (UUIDs)

                               Internet Engineering Task Force (IETF) K. Davis Request for Comments: 9562 Cisco Systems Obsoletes: 4122 B. Peabody Category: Standards Track Uncloud ISSN: 2070-1721 P. Leach University of Washington May 2024 Universally Unique IDentifiers (UUIDs) Abstract This specification defines UUIDs (Universally Unique IDentifiers) -- also known as GUIDs (Globally Unique IDentifiers) -- and a Uniform Resou

                                RFC 9562: Universally Unique IDentifiers (UUIDs)
                              • June 2022 (version 1.69)

                                Update 1.69.1: The update addresses these issues. Update 1.69.2: The update addresses these issues. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the June 2022 release of Visual Studio Code. There are many updates in this version that we hope you'll like, some of the key highlights include: 3-way merge editor - Resolve merge conflicts wit

                                  June 2022 (version 1.69)
                                • Golang Mini Reference 2022: A Quick Guide to the Modern Go Programming Language (REVIEW COPY)

                                  Golang Mini Reference 2022 A Quick Guide to the Modern Go Programming Language (REVIEW COPY) Harry Yoon Version 0.9.0, 2022-08-24 REVIEW COPY This is review copy, not to be shared or distributed to others. Please forward any feedback or comments to the author. • feedback@codingbookspress.com The book is tentatively scheduled to be published on September 14th, 2022. We hope that when the release da

                                  • Agents

                                    Intelligent agents are considered by many to be the ultimate goal of AI. The classic book by Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Prentice Hall, 1995), defines the field of AI research as “the study and design of rational agents.” The unprecedented capabilities of foundation models have opened the door to agentic applications that were previously unimaginabl

                                      Agents
                                    • Parsing SQL - Strumenta

                                      The code for this tutorial is on GitHub: parsing-sql SQL is a language to handle data in a relational database. If you worked with data you have probably worked with SQL. In this article we will talk about parsing SQL. It is in the same league of HTML: maybe you never learned it formally but you kind of know how to use it. That is great because if you know SQL, you know how to handle data. However

                                        Parsing SQL - Strumenta
                                      • How I developed a faster Ruby interpreter | Red Hat Developer

                                        In this article, I will describe my efforts to implement a faster interpreter for CRuby, the Ruby language interpreter, using a dynamically specialized internal representation (IR). I believe this article will interest developers trying to improve the interpreter performance of dynamic programming languages (e.g., CPython developers). I will cover the following topics: Existing CRuby interpreter a

                                          How I developed a faster Ruby interpreter | Red Hat Developer
                                        • Building a Toy Programming Language in Python

                                          I thought it would be fun to go outside of my comfort zone of web development topics and write about something completely different and new, something I have never written about before. So today, I'm going to show you how to implement a programming language! The project will parse and execute programs written in a simple language I called my (I know it's a lame name, but hey, it is "my" language).

                                            Building a Toy Programming Language in Python
                                          • Argilla を使って生成 AI の出力クオリティ向上を目指す! - Techtouch Developers Blog

                                            はじめに 導入背景 Argilla とは なぜ Argilla を選んだか 実現したいこと 設計 実装方針 その他実装における工夫点 今後の課題 まとめ はじめに こんにちは。データエンジニアの acchan です。 現在 DAP Lab とよばれるチームに配属しており、生成 AI 技術を使ったプロダクト開発に従事しています。生成 AI の新たな可能性と課題に挑む私たちの取り組みについて、今回は AI 出力改善のワークフロー構築に Argilla と呼ばれるツールを組み込んだ背景や、具体的な機能などについて紹介します。 導入背景 弊社はノーコードWebシステム改善プラットフォーム「テックタッチ」を展開しています。 この「テックタッチ」に対して、DAP Labでは生成 AI を使った機能(以下、AI 機能)のリリースを控えています。 この機能は「テックタッチ」の利用効率化を目的としたものです

                                              Argilla を使って生成 AI の出力クオリティ向上を目指す! - Techtouch Developers Blog
                                            • Kalyn: a self-hosting compiler for x86-64

                                              Over the course of my Spring 2020 semester at Harvey Mudd College, I developed a self-hosting compiler entirely from scratch. This article walks through many interesting parts of the project. It’s laid out so you can just read from beginning to end, but if you’re more interested in a particular topic, feel free to jump there. Or, take a look at the project on GitHub. Table of contents What the pro

                                              • Patterns for Building LLM-based Systems & Products

                                                Patterns for Building LLM-based Systems & Products [ llm engineering production 🔥 ] · 66 min read Discussions on HackerNews, Twitter, and LinkedIn “There is a large class of problems that are easy to imagine and build demos for, but extremely hard to make products out of. For example, self-driving: It’s easy to demo a car self-driving around a block, but making it into a product takes a decade.”

                                                  Patterns for Building LLM-based Systems & Products
                                                • July 2022 (version 1.70)

                                                  Join a VS Code Dev Days event near you to learn about AI-assisted development in VS Code. Update 1.70.1: The update addresses these issues. Update 1.70.2: The update addresses these issues. Update 1.70.3: This update is only available for Windows 7 users and is the last release supporting Windows 7. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welc

                                                    July 2022 (version 1.70)
                                                  • Coroutines and effects

                                                    For the past few months I’ve been mulling over some things that Russell Johnston made me realize about the relationship between effect systems and coroutines. You can read more of his thoughts on this subject here, but he made me realize that effect systems (like that found in Koka) and coroutines (like Rust’s async functions or generators) are in some ways isomorphic to one another. I’ve been pon

                                                    • Building the fastest Lua interpreter.. automatically!

                                                      This is Part 1 of a series of posts. Part 2 is available here: Building a baseline JIT for Lua automatically It is well-known that writing a good VM for a dynamic language is never an easy job. High-performance interpreters, such as the JavaScript interpreter in Safari, or the Lua interpreter in LuaJIT, are often hand-coded in assembly. If you want a JIT compiler for better performance, well, you’

                                                        Building the fastest Lua interpreter.. automatically!
                                                      • Beyond the 70%: Maximizing the human 30% of AI-assisted coding

                                                        Beyond the 70%: Maximizing the human 30% of AI-assisted codingWhy durable human skills matter in the age of AI-assisted coding This is a follow-up to my article “The 70% problem: Hard truths about AI-assisted coding” AI coding assistants like Cursor, Cline, Copilot and WindSurf have transformed how software is built, shouldering much of the grunt work and boilerplate. Yet, as experienced developer

                                                          Beyond the 70%: Maximizing the human 30% of AI-assisted coding
                                                        • Why People are Angry over Go 1.23 Iterators - gingerBill

                                                          NOTE: This is based on, but completely rewritten, from a Twitter post: https://x.com/TheGingerBill/status/1802645945642799423 TL;DR It makes Go feel too “functional” rather than being an unabashed imperative language. I recently saw a post on Twitter showing the upcoming Go iterator design for Go 1.23 (August 2024). From what I can gather, many people seem to dislike the design. I wanted to give m

                                                          • Real-world gen AI use cases from the world's leading organizations | Google Cloud Blog

                                                            AI is here, AI is everywhere: Top companies, governments, researchers, and startups are already enhancing their work with Google's AI solutions. Published April 12, 2024; last updated October 9, 2025. Automotive & Logistics Business & Professional Services Financial Services Healthcare & Life Sciences Hospitality & Travel Manufacturing, Industrial & Electronics Media, Marketing & Gaming Public Sec

                                                              Real-world gen AI use cases from the world's leading organizations | Google Cloud Blog
                                                            • How I Use AI: Meet My Promptly Hired Model Intern

                                                              written on January 30, 2025 After Musk’s acquisition of Twitter, many people I respect and follow moved to Bluesky. I created an account there and made an honest attempt of making it my primary platform. Sadly, I found Bluesky to be surprisingly hostile towards AI content. There is an almost religious resistance to AI on there, at least in whatever corner of the platform I ended up in. Despite the

                                                                How I Use AI: Meet My Promptly Hired Model Intern
                                                              • 0.10.0 Release Notes ⚡ The Zig Programming Language

                                                                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

                                                                • Reflections on 2 years of CPython’s JIT Compiler—The good, the bad, the ugly

                                                                  Ken Jin's Blog Reflections on 2 years of CPython’s JIT Compiler: The good, the bad, the ugly 5 July 2025 This blog post includes my honest opinions on the CPython JIT. What I think we did well, what I think we could have done better. I’ll also do some brief qualititative analysis. I’ve been working on CPython’s JIT compiler since before the very start. I don’t know how long that is at this point …

                                                                  • LLMが苦手な麻雀点数計算問題生成タスクの精度を33%から90%に上げたMulti Agentの力 - LayerX エンジニアブログ

                                                                    こんにちは、Hiromu Nakamura (pon) です。 LayerXの機械学習チームでMLOpsをやっています。LayerXではAI エージェント事業を進めており、その一環として身近なタスクで日々AIエージェントを触りまくっています。今回はLLMが苦手な麻雀点数計算問題生成タスクの精度を33%から90%に上げた話をします。 この話から次のことが学べます。 「無数の選択肢の組み合わせを考えるタスクだが、正解は検証できる」という特性を持つタスクの精度を上げるノウハウ。 実際のMulti Agentの実装方法 目次 目次 成果物 導入 LLMは麻雀点数計算が苦手 実験1: 麻雀のルール、考え方を叩き込む 実験設定 比較手法 データセット 評価方法 評価指標 結果 定性確認による考察 精度を上げる方針 改めて考えるタスクの特性 特性を考慮した精度向上アイデア 実験2: Multi Agen

                                                                      LLMが苦手な麻雀点数計算問題生成タスクの精度を33%から90%に上げたMulti Agentの力 - LayerX エンジニアブログ
                                                                    • Ordering Movie Credits With Graph Theory

                                                                      At Endcrawl we're always thinking about the hard work that goes into making film and TV, and how that work translates to on-screen credits. A feature film may involve thousands of people, hundreds of distinct job titles or "roles," and dozens of departments. So there's plenty for a producer to worry about, like: Did we forget or misspell a name? Is this the correct way to credit that role? Do all

                                                                        Ordering Movie Credits With Graph Theory
                                                                      • j3s.sh

                                                                        my website is one binary 2022-04-06 ---------------------------- a.k.a. this one weird trick that inspires me to program creatively i have struggled for years to figure out a website framework that feels good to me. i tried all of the classics, including but limited to: - ghost - hugo - jekyll - sr.ht + tarball - manual html editing i have very high and unusual standards, and none of the above fel

                                                                        • Introducing PyTorch Monarch – PyTorch

                                                                          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

                                                                          • August 2021 (version 1.60)

                                                                            Update 1.60.1: The update addresses these issues. Update 1.60.2: The update addresses these issues. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the August 2021 release of Visual Studio Code. There are many updates in this version that we hope you will like, some of the key highlights include: Automatic language detection - Programming l

                                                                              August 2021 (version 1.60)
                                                                            • 90%

                                                                              written on September 29, 2025 “I think we will be there in three to six months, where AI is writing 90% of the code. And then, in 12 months, we may be in a world where AI is writing essentially all of the code” — Dario Amodei Three months ago I said that AI changes everything. I came to that after plenty of skepticism. There are still good reasons to doubt that AI will write all code, but my curre

                                                                                90%
                                                                              • Implementing RSA in Python from Scratch

                                                                                Implementing RSA in Python from Scratch Build RSA encryption in Python from first principles — key generation, Extended Euclidean Algorithm, and modular exponentiation explained with working code. This is the math that actually runs behind every HTTPS connection you make. I've seen a lot of articles explaining the general principles of asymmetric cryptography, but not many that give easy-to-unders

                                                                                  Implementing RSA in Python from Scratch
                                                                                • Zensical - A modern static site generator - Material for MkDocs

                                                                                  Zensical – A modern static site generator built by the Material for MkDocs team¶ We are thrilled to announce Zensical, our next-gen static site generator designed to simplify the process of building documentation sites. Distilled from a decade of experience, Zensical is our effort to overcome the technical limitations of MkDocs, reaching far beyond its capabilities. Zensical is the result of thous

                                                                                    Zensical - A modern static site generator - Material for MkDocs