Elasticsearch Query Language (ES|QL) now generally available - Elasticsearch Labs
Want to get Elastic certified? Find out when the next Elasticsearch Engineer training is running! Elasticsearch is packed with new features to help you build the best search solutions for your use case. Dive into our sample notebooks to learn more, start a free cloud trial, or try Elastic on your local machine now. Today, we are pleased to announce the general availability of ES|QL (Elasticsearch
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
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
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
Getting started What is NumPy? Installation NumPy quickstart NumPy: the absolute basics for beginners Fundamentals and usage NumPy fundamentals NumPy for MATLAB users NumPy tutorials NumPy how-tos Advanced usage and interoperability Using NumPy C-API F2PY user guide and reference manual Under-the-hood documentation for developers Interoperability with NumPy Extras Glossary Release notes 2.4.0 2.3.
I spend an awful lot of my day in Unix terminals running shell commands. For some reason, the variance in efficiency between different people when using the shell is huge: I know people who can run rings around me, and I’ve come across more than one paid professional who doesn’t use the “up” key to retrieve the previous command. I chose that last example very deliberately: most of the commands mos
Try Mastering Emacs for free! Are you struggling with the basics? Have you mastered movement and editing yet? When you have read Mastering Emacs you will understand Emacs. It’s that time again: there’s a new major version of Emacs and, with it, a treasure trove of new features and changes. Notable features include the formal inclusion of native compilation, a technique that will greatly speed up y
A mega tutorial with dozens of examples on how to use the pathlib module in Python 3 When I started learning Python, there was one thing I always had trouble with: dealing with directories and file paths! I remember the struggle to manipulate paths as strings using the os module. I was constantly looking up error messages related to improper path manipulation. The os module never felt intuitive an
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
Concurrency is not very intuitive. You need to train your brain to consider what happens when multiple processes execute a certain code block at the same time. There are several issues I often encounter: Failing to recognize potential concurrency issues: It's not uncommon for both beginner and seasoned developers to completely miss a potential concurrency problem. When this happens, and the concur
こんにちは、メディアサービス開発部サービス分析課の佐藤です。推しTRPGはD&D5版です。今年4月に入社し、事業横断データ基盤を構築しています。 今回はブックウォーカー社内でデータ基盤を構築するにあたって身につけたAWS関連の知識、主にRDSのexport snapshot to S3、Glue Job、AWS Serverless Application Model （以下SAMと略します）周りについて書いていきます。 背景 手法1. 定期的なデータ抽出 手法2. 外部接続 手法3. Change Data Capture システム構成の詳細 Export Snapshot to S3 AWS Glue Job Step FunctionsとEvent Bridge SAMとCI/CD 最終成果物とシステム運用 課題 parquetのデータ型 データの更新頻度 最後に 背景 株式会社ブッ
週刊Railsウォッチ: DI的な書き方が必要なとき、脆弱性学習用アプリRailsGoat、brakemanは優秀ほか（20210705前編）｜TechRacho by BPS株式会社
週刊Railsウォッチについて 各記事冒頭には🔗でパーマリンクを置いてあります: 社内やTwitterでの議論などにどうぞ 「つっつきボイス」はRailsウォッチ公開前ドラフトを（鍋のように）社内有志でつっついたときの会話の再構成です👄 お気づきの点がありましたら@hachi8833までメンションをいただければ確認・対応いたします🙇 TechRachoではRubyやRailsなどの最新情報記事を平日に公開しています。TechRacho記事をいち早くお読みになりたい方はTwitterにて@techrachoのフォローをお願いします。また、タグやカテゴリごとにRSSフィードを購読することもできます（例:週刊Railsウォッチタグ） 🔗Rails: 先週の改修（Rails公式ニュースより） 今回も以下の公式更新情報の続きを追います。次の更新情報も出ましたね。 更新情報: Rails 6.
Python Dependency Injection
Writing clean, maintainable code is a challenging task. Fortunately, there are many patterns, techniques, and reusable solutions available to us to make achieving that task much easier. Dependency Injection is one of those techniques, which is used to write loosely-coupled yet highly-cohesive code. In this article, we'll show you how to implement Dependency Injection as you develop an app for plot
Introduction: These Aren’t the JSONs You’re Looking For JSON (JavaScript Object Notation) was designed as a simple, lightweight, and human-readable data interchange format, often positioned as a more accessible alternative to XML. It has become the de facto standard for web APIs and system integration. However, while the specification itself is straightforward, different programming languages and
In this article, I will introduce the pandas library of Python programming language for data science. We will also see practical examples of code to create data frames, logical operations, and looping, apart from examples of code for the advanced concepts of pandas. Introduction to pandaspandas is a great library of Python for data science for most industry applications with massive amounts of dif
Sketch of a Post-ORM
I’ve been writing a lot of database access code as of late. It’s frustrating that in 2023, my choices are still to either write all of the boilerplate by hand, or hand all database access over to some inscrutable “agile” ORM that will become a crippling liability in the 2-3y timescale. This post is about how I want to use databases, from the perspective of an application server developer—not a DBA
GitHub - ComfyUI-Workflow/awesome-comfyui: A collection of awesome custom nodes for ComfyUI
ComfyUI-Gemini_Flash_2.0_Exp (⭐+172): A ComfyUI custom node that integrates Google's Gemini Flash 2.0 Experimental model, enabling multimodal analysis of text, images, video frames, and audio directly within ComfyUI workflows. ComfyUI-ACE_Plus (⭐+115): Custom nodes for various visual generation and editing tasks using ACE_Plus FFT Model. ComfyUI-Manager (⭐+113): ComfyUI-Manager itself is also a cu
Django for Startup Founders: A better software architecture for SaaS startups and consumer apps
In an ideal world, startups would be easy. We'd run our idea by some potential customers, build the product, and then immediately ride that sweet exponential growth curve off into early retirement. Of course it doesn't actually work like that. Not even a little. In real life, even startups that go on to become billion-dollar companies typically go through phases like: Having little or no growth fo
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
Why I use attrs instead of pydantic
NumPy 2.0.0 Release Notes — NumPy v2.4.dev0 Manual
Laurence Tratt: Better Shell History Search
What's New in Emacs 28.1?
Python pathlib Cookbook: 57+ Examples to Master It (2022)
The AI-Native Software Engineer
Handling Concurrency Without Locks
いくつものDBからデータをかき集めるには - BOOK☆WALKER inside
JSON is not JSON Across Languages | Dochia CLI Blog
pandas: An Ultimate Python Library for Data Science