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  • Command Line Interface Guidelines

    Contents Command Line Interface Guidelines An open-source guide to help you write better command-line programs, taking traditional UNIX principles and updating them for the modern day. Authors Aanand Prasad Engineer at Squarespace, co-creator of Docker Compose. @aanandprasad Ben Firshman Co-creator Replicate, co-creator of Docker Compose. @bfirsh Carl Tashian Offroad Engineer at Smallstep, first e

      Command Line Interface Guidelines
    • 【2020年】CTF Web問題の攻撃手法まとめ - こんとろーるしーこんとろーるぶい

      はじめに 対象イベント 読み方、使い方 Remote Code Execution(RCE) 親ディレクトリ指定によるopen_basedirのバイパス PHP-FPMのTCPソケット接続によるopen_basedirとdisable_functionsのバイパス JavaのRuntime.execでシェルを実行 Cross-Site Scripting(XSS) nginx環境でHTTPステータスコードが操作できる場合にCSPヘッダーを無効化 GoogleのClosureLibraryサニタイザーのXSS脆弱性 WebのProxy機能を介したService Workerの登録 括弧を使わないXSS /記号を使用せずに遷移先URLを指定 SOME(Same Origin Method Execution)を利用してdocument.writeを順次実行 SQL Injection MySQ

        【2020年】CTF Web問題の攻撃手法まとめ - こんとろーるしーこんとろーるぶい
      • 結婚式のエンドロールを当日作った話

        結婚のお礼と報告 でちょこっと書いた結婚式エンドロールをその場で作ってみたのお話 注意事項# 結婚式のエンドロールを自作したりするには結婚式場の協力が必須です。 作り出す前に式場に必ず確認を取りましょう。 PCからそのままプロジェクトにだせばいいじゃん!と思い込むのだめです(自戒) 動機# エンドロールを式場にお願いしようと思ったら高かったので、最近のイケてるサービスとか適当にガッチャンコすれば作れると思った。 今は反省している。 全体の構成# LINE Botに参加者から画像投稿を投げてもらう S3に保存すると同時に投稿者情報をDynamoDBに保存 投稿された画像にDynamoDBの投稿者情報から名前を追記 画像を全部結合して動画化し、事前に生成したエンドロールで必要な部分を結合 式の最後に流してもらう 全体の構成はこんな感じです。 サーバーレスアーキテクチャのお勉強がてら作ろうとした

          結婚式のエンドロールを当日作った話
        • プロと読み解く Ruby 3.1 NEWS - クックパッド開発者ブログ

          技術部の笹田(ko1)と遠藤(mame)です。クックパッドで Ruby (MRI: Matz Ruby Implementation、いわゆる ruby コマンド) の開発をしています。お金をもらって Ruby を開発しているのでプロの Ruby コミッタです。 本日 12/25 に、ついに Ruby 3.1.0 がリリースされました(Ruby 3.1.0 リリース )。今年も Ruby 3.1 の NEWS.md ファイルの解説をします。NEWS ファイルとは何か、は以前の記事を見てください。 プロと読み解く Ruby 2.6 NEWS ファイル - クックパッド開発者ブログ プロと読み解くRuby 2.7 NEWS - クックパッド開発者ブログ プロと読み解くRuby 3.0 NEWS - クックパッド開発者ブログ 本記事は新機能を解説することもさることながら、変更が入った背景や苦労な

            プロと読み解く Ruby 3.1 NEWS - クックパッド開発者ブログ
          • GPT in 60 Lines of NumPy | Jay Mody

            January 30, 2023 In this post, we'll implement a GPT from scratch in just 60 lines of numpy. We'll then load the trained GPT-2 model weights released by OpenAI into our implementation and generate some text. Note: This post assumes familiarity with Python, NumPy, and some basic experience with neural networks. This implementation is for educational purposes, so it's missing lots of features/improv

            • LangGraph を用いた LLM エージェント、Plan-and-Execute Agents の実装解説 - Algomatic Tech Blog

              はじめに こんにちは。Algomatic LLM STUDIO 機械学習エンジニアの宮脇(@catshun_)です。 Wang+’23 - A Survey on Large Language Model Based Autonomous Agents ChatGPT が発表されてからおよそ 1 年が経ち、AutoGPT, BabyAGI, HuggingGPT, Generative Agents, ChatDev, Mind2Web, Voyager, MetaGPT, Self-Recovery Prompting, OpenCodeInterpreter, AutoAgents などなど、大規模言語モデル (LLM) の抱負な知識および高度な推論能力を活用した LLM エージェント (AIエージェント) が発表されています。 直近ではコード生成からデバッグ、デプロイまで自律的に行う

                LangGraph を用いた LLM エージェント、Plan-and-Execute Agents の実装解説 - Algomatic Tech Blog
              • 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
                • Onyx, a new programming language powered by WebAssembly · Blog · Wasmer

                  Onyx, a new programming language powered by WebAssemblyLearn about Onyx, a new imperative programming language that leverages WebAssembly and Wasmer for seamless cross-platform support What is Onyx? Onyx is a new programming language featuring a modern, expressive syntax, strict type safety, blazingly-fast build times, and out-of-the-box cross platform support thanks to WebAssembly. Over the past

                    Onyx, a new programming language powered by WebAssembly · Blog · Wasmer
                  • 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

                    • Harden-Runner detection: tj-actions/changed-files action is compromised - StepSecurity

                      IntroductionWe have concluded our investigation into the critical security incident involving the `tj-actions/changed-files` GitHub Action. The issue has been reported to GitHub, and an official CVE — CVE-2025-30066 — has been published to track the incident. You can find more details in GitHub Issue #2463. Based on our findings, the Action was compromised and posed a significant risk by exposing

                        Harden-Runner detection: tj-actions/changed-files action is compromised - StepSecurity
                      • 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
                        • 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

                          • Why I use attrs instead of pydantic

                            This post is an account of why I prefer using the attrs library over Pydantic. I'm writing it since I am often asked this question and I want to have something concrete to link to. This is not meant to be an objective comparison of attrs and Pydantic; I'm not interested in comparing bullet points of features, nor can I be unbiased since I'm a major contributor to attrs (at time of writing, second

                            • The OpenSSL punycode vulnerability (CVE-2022-3602): Overview, detection, exploitation, and remediation | Datadog Security Labs

                              emerging threats and vulnerabilities The OpenSSL punycode vulnerability (CVE-2022-3602): Overview, detection, exploitation, and remediation November 1, 2022 emerging vulnerability On November 1, 2022, the OpenSSL Project released a security advisory detailing a high-severity vulnerability in the OpenSSL library. Deployments of OpenSSL from 3.0.0 to 3.0.6 (included) are vulnerable and are fixed in

                                The OpenSSL punycode vulnerability (CVE-2022-3602): Overview, detection, exploitation, and remediation | Datadog Security Labs
                              • python_modules.pdf

                                Python3 OpenCV / Pillow / pygame / Eel / PyDub / NumPy / matplotlib / SciPy / SymPy / gmpy2 / hashlib, passlib / Cython / Numba / ctypes / PyInstaller / curses / tqdm / JupyterLab / json / psutil / urllib / zenhan / jaconv Copyright © 2017-2025, Katsunori Nakamura 2025 8 19 Python ‘ .py’ Python Python Windows PSF Python py .py Enter macOS Linux PSF Python python3 .py Enter Anaconda Prompt Python p

                                • What's new in Python 3.11?

                                  What's new in Python 3.11?Built-in TOML support, better exceptions, and typing improvements. By Tushar·InsightsPython The first beta release of Python 3.11 is out, bringing some fascinating features for us to tinker with. This is what you can expect to see in 2022's release of Python later this year. Even better error messagesPython 3.10 gave us better error messages in various regards, but Python

                                    What's new in Python 3.11?
                                  • Kubeflow PipelinesからVertex Pipelinesへの移行による運用コスト削減 - ZOZO TECH BLOG

                                    こんにちは、技術本部 データシステム部 MLOpsブロックの平田(@TrsNium)です。約2年半ぶりの執筆となる今回の記事では、MLOps向け基盤を「Kubeflow Pipelines」から「Vertex Pieplines」へ移行して運用コストを削減した取り組みを紹介します。 目次 目次 はじめに Vertex Pipelinesとは Vertex Pipelinesへの移行 Vertex Pipelinesへ移行するワークフロー 1. ワークフローのKubeflow Pipelines SDK V2への移行 コンパイラのデータ型の制約が厳しくなった ContainerOp APIが非推奨になった Kubeflow PipelinesのPlaceholderを使用できなくなった 2. スケジュール実行されているワークフローへ前回実行分が終わるまでの待機処理を追加 3. Vertex

                                      Kubeflow PipelinesからVertex Pipelinesへの移行による運用コスト削減 - ZOZO TECH BLOG
                                    • はじめての自然言語処理 Fusion-In-Decoder でクイズに答えるモデルを作る | オブジェクトの広場

                                      今回は Fusion-In-Decoder を使ってクイズに答えるモデルを作ります。以前から Wikipedia 等の外部情報を参照できるテキスト生成モデルを試してみたいと思っていました。Fusion-In-Decoder の発表は 2020 年なので少し前のモデルですが、T5 ベースで手軽に試せるサイズ感ですので、日本語で試してみましょう。 1. はじめに 今回紹介する Fusion-In-Decoder(以下、FiD )1 は Meta AI (当時は Facebook AI Research) が発表した Open Domain question Answering タスクを解くテキスト生成モデルです。 じつは、以前から外部情報を参照できるテキスト生成モデルを試してみたくて2、 Google の RETRO3 の論文を読んでたんです。 なのですが、外部情報のサイズ感が 1000 B

                                        はじめての自然言語処理 Fusion-In-Decoder でクイズに答えるモデルを作る | オブジェクトの広場
                                      • OpenAI API の Structured Outputs の使い方|npaka

                                        以下の記事が面白かったので、簡単にまとめました。 ・Introducing Structured Outputs in the API 1. Structured Outputs昨年のDevDayで、「JSONモード」を導入しました。これは、OpenAIのモデルを使用して信頼性の高いアプリを構築しようとしている開発者にとって便利な構成要素です。「JSONモード」は、有効なJSON出力を生成するためのモデルの信頼性を向上させますが、モデルの応答が特定のスキーマに準拠することを保証するものではありません。本日、APIに「Structured Outputs」を導入します。これは、モデルによって生成された出力が、開発者が提供するJSONスキーマと完全に一致するように設計された新機能です。 複雑なJSONスキーマのフォローの評価では、「Structured Outputs」を備えた新しいモデル「g

                                          OpenAI API の Structured Outputs の使い方|npaka
                                        • How I wrote my own "proper" programming language

                                          The diagram above is the compiler for the language Bolt we’ll be building. What do all the stages mean? I have to learn OCaml and C++? Wait I haven’t even heard of OCaml… Don’t worry. When I started this project 6 months ago, I had never built a compiler, nor had I used OCaml or C++ in any serious project. I’ll explain everything in due course. In this series of posts we’ll be building a proper pr

                                            How I wrote my own "proper" programming language
                                          • swift-transformers で LLM を動かしてみた - ABEJA Tech Blog

                                            ABEJA でエンジニアをしている石川です。これは ABEJA アドベントカレンダー 2024 の 18 日目の記事です。 CoreML で機械学習モデルを動かす swift-transformers を試す Mistral 7B モデルを動かす swift-transformers で推論を実装する Python で動かしてみる CoreML モデルに変換 Swift で動かす パフォーマンス We Are Hiring! macOS/iOS で機械学習モデルを動かすにはいくつかの方法がありますが、Apple シリコンの能力を十分に引き出すためには CoreML を使うのが最適です。 Python 向け機械学習フレームワークである PyTorch も MPS バックエンドによって、Apple シリコンの GPU を利用することはできます。しかし、Apple の NPU (Neural P

                                              swift-transformers で LLM を動かしてみた - ABEJA Tech Blog
                                            • Lean for JavaScript Developers — overreacted

                                              Lean for JavaScript DevelopersSeptember 2, 2025 This is my opinionated syntax primer for the Lean programming language. It is far from complete and may contain inaccuracies (I’m still learning Lean myself) but this is how I wish I was introduced to it, and what I wish was clarified. Why Lean? This post assumes you’re already eager to learn a bit of Lean. For motivation, I humbly submit to you two

                                                Lean for JavaScript Developers — overreacted
                                              • My thoughts on writing a Minecraft server from scratch (in Bash)

                                                My thoughts on writing a Minecraft server from scratch (in Bash) For the past year or so, I've been thinking about writing a Minecraft server in Bash as a thought excercise. I once tried that before with the Classic protocol (the one from 2009), but I quickly realized there wasn't really a way to properly parse binary data in bash. Take the following code sample: function a() { read -n 2 uwu echo

                                                • A Lisp Interpreter Implemented in Conway’s Game of Life

                                                  Lisp in Life is a Lisp interpreter implemented in Conway’s Game of Life. The entire pattern is viewable on the browser here. To the best of my knowledge, this is the first time a high-level programming language was interpreted in Conway’s Game of Life. Running Lisp on the Game of Life Lisp is a language with a simple and elegant design, having an extensive ability to express sophisticated ideas as

                                                    A Lisp Interpreter Implemented in Conway’s Game of Life
                                                  • ​Getting Started with Python

                                                    Python is a powerful programming language that provides many packages that we can use. Using the versatile Python programming language, we can develop the following: AutomationDesktop applicationAndroidWebIoT home automationData Science and the list goes on.In this article, our primary focus will be knowing how to start learning Python and the essentials required to be a data scientist. Below is t

                                                      ​Getting Started with Python
                                                    • 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

                                                      • 【GROMACS】Umbrella samplingによるMD simulation 【In silico創薬】【SMD】 - LabCode

                                                        Windows 11 Home, 13th Gen Intel(R) Core(TM) i7-13700, 64 ビット オペレーティング システム、x64 ベース プロセッサ, メモリ:32GB Umbrella Samplingの概要と目的Umbrella Samplingは、分子がめったに起こさないような状態変化(たとえば、タンパク質同士が離れるなど)を詳しく調べるための計算手法です。通常の分子動力学(MD)では、エネルギー的に安定な状態にとどまりやすく、重要な変化が起こる確率が低いため、十分な情報が得られません。 たとえば、タンパク質AとBがくっついている状態から、少しずつ離れていく様子を観察したいとき、まずAとBを少しずつ引き離すSteered Molecular Dynamics(SMD)などのシミュレーションで、さまざまな距離の構造を取得します。その中から、0.5nm、0.7

                                                        • Fine-Tune Whisper For Multilingual ASR with 🤗 Transformers

                                                          For demonstration purposes, we'll fine-tune the multilingual version of the small checkpoint with 244M params (~= 1GB). As for our data, we'll train and evaluate our system on a low-resource language taken from the Common Voice dataset. We'll show that with as little as 8 hours of fine-tuning data, we can achieve strong performance in this language. 1{}^11 The name Whisper follows from the acronym

                                                            Fine-Tune Whisper For Multilingual ASR with 🤗 Transformers
                                                          • Writing Pythonic Rust

                                                            Over the past several weeks I have been attempting to reimplement the API of an existing python library as a wrapper for an equivalent library in Rust. tl;dr: this ended up being much harder than I expected it to be, partly because of important differences in the behaviour of the two languages, and partly because of the (self-imposed) obligation to match an existing (idiomatic) python API. Motivat

                                                            • Unicode is harder than you think · mcilloni's blog

                                                              Reading the excellent article by JeanHeyd Meneide on how broken string encoding in C/C++ is made me realise that Unicode is a topic that is often overlooked by a large number of developers. In my experience, there’s a lot of confusion and wrong expectations on what Unicode is, and what best practices to follow when dealing with strings that may contain characters outside of the ASCII range. This a

                                                              • Why We Use Julia, 10 Years Later

                                                                Exactly ten years ago today, we published "Why We Created Julia", introducing the Julia project to the world. At this point, we have moved well past the ambitious goals set out in the original blog post. Julia is now used by hundreds of thousands of people. It is taught at hundreds of universities and entire companies are being formed that build their software stacks on Julia. From personalized me

                                                                  Why We Use Julia, 10 Years Later
                                                                • Agents for Amazon Bedrock now support memory retention and code interpretation (preview) | Amazon Web Services

                                                                  AWS News Blog Agents for Amazon Bedrock now support memory retention and code interpretation (preview) With Agents for Amazon Bedrock, generative artificial intelligence (AI) applications can run multistep tasks across different systems and data sources. A couple of months back, we simplified the creation and configuration of agents. Today, we are introducing in preview two new fully managed capab

                                                                    Agents for Amazon Bedrock now support memory retention and code interpretation (preview) | Amazon Web Services
                                                                  • Type Parameters Proposal

                                                                    Ian Lance Taylor Robert Griesemer August 20, 2021 StatusThis is the design for adding generic programming using type parameters to the Go language. This design has been proposed and accepted as a future language change. We currently expect that this change will be available in the Go 1.18 release in early 2022. AbstractWe suggest extending the Go language to add optional type parameters to type an

                                                                    • 789 KB Linux Without MMU on RISC-V

                                                                      Follow @popovicu94 In this guide, we’ll build a very tiny Linux kernel, weighing in at 789 K, and requiring no MMU support. We’ll write some userspace code and this will be deployed on a virtual RISC-V 64-bit machine, without MMU, and we’ll run some tiny programs of our own. As a reminder, please go through the guide for a micro Linux distro to understand the concepts behind what we’re doing today

                                                                        789 KB Linux Without MMU on RISC-V
                                                                      • Node.js — Node.js v22.10.0 (Current)

                                                                        Or if the package is only meant to be run on Node.js and wants to fallback to CJS on older versions that don't have require(esm): { "type": "module", "exports": { // On new version of Node.js, both require() and import get the ESM version "module-sync": "./index.js", // On older version of Node.js, where "module-sync" and require(esm) are // not supported, use the CJS version to avoid dual-package

                                                                          Node.js — Node.js v22.10.0 (Current)
                                                                        • はじめての自然言語処理 Transformer 系モデルの推論高速化の検証 | オブジェクトの広場

                                                                          今回は Transformer 系のモデル、具体的には BERT, T5, GPT の推論を高速化してみます。高速化手法として FasterTransformer, Torch-TensorRT, AWS Neuron を用い、素 の transfomers に比べ、どの程度速くなるか(ならないか)、利点・欠点を確認してみましょう。 1. はじめに 今回は Transformer 系のモデル、具体的には BERT, T5, GPT の推論を様々な技術を使って高速化してみます。 高速化の元ネタは Hugging Face の transformers1 縛りとして、素の transformers で推論する場合に比べ、 どの程度速くなるか(ならないか)見てみましょう。 推論を高速化する技術としては FasterTransfomer2, Torch-TensorRT3, AWS Neuron(

                                                                            はじめての自然言語処理 Transformer 系モデルの推論高速化の検証 | オブジェクトの広場
                                                                          • Plan 9 Desktop Guide

                                                                            PLAN 9 DESKTOP GUIDE INDEX What is Plan 9? Limitations and Workarounds Connecting to Other Systems VNC RDP SSH 9P Other methods Porting Applications Emulating other Operating Systems Virtualizing other Operating Systems Basics Window Management Copy Pasting Essential Programs Manipulating Text in the Terminal Acme - The Do It All Application Multiple Workspaces Tiling Windows Plumbing System Admin

                                                                            • OpenAssistant/oasst1 · Datasets at Hugging Face

                                                                              'Jew' or 'rabbi'"},"role":{"kind":"string","value":"assistant"},"lang":{"kind":"string","value":"en"},"review_count":{"kind":"number","value":3,"string":"3"},"review_result":{"kind":"bool","value":true,"string":"true"},"deleted":{"kind":"bool","value":false,"string":"false"},"rank":{"kind":"number","value":1,"string":"1"},"synthetic":{"kind":"bool","value":false,"string":"false"},"model_name":{"ki

                                                                                OpenAssistant/oasst1 · Datasets at Hugging Face
                                                                              • Node.js — Node.js v23.0.0 (Current)

                                                                                2024-10-16, Version 23.0.0 (Current), @RafaelGSS We’re excited to announce the release of Node.js 23! Key highlights include: Enabling require(esm) by default for Node.js applications Removing support for Windows 32-bit systems Stabilizing the node --run command Enhancements to the test runner, including glob pattern support for coverage files Node.js 23 will replace Node.js 22 as the ‘Current’ re

                                                                                  Node.js — Node.js v23.0.0 (Current)
                                                                                • Large Text Compression Benchmark

                                                                                   Large Text Compression Benchmark Matt Mahoney Last update: July 3, 2025. history This competition ranks lossless data compression programs by the compressed size (including the size of the decompression program) of the first 109 bytes of the XML text dump of the English version of Wikipedia on Mar. 3, 2006. About the test data. The goal of this benchmark is not to find the best overall compressi