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seydx/node-av: FFmpeg bindings for Node.js. Features both low-level and high-level APIs, full hardware acceleration, TypeScript support, and modern async patterns
seydx/node-av: FFmpeg bindings for Node.js. Features both low-level and high-level APIs, full hardware acceleration, TypeScript support, and modern async patterns
FFmpeg bindings for Node.js. Features both low-level and high-level APIs, full hardware acceleration, TypeScript support, and modern async patterns - seydx/node-av
·github.com·
seydx/node-av: FFmpeg bindings for Node.js. Features both low-level and high-level APIs, full hardware acceleration, TypeScript support, and modern async patterns
When React parent components need to know their children
When React parent components need to know their children
In React, it’s always preferable to maintain a linear data flow. If a parent needs something, lift the state instead of smuggling it back up. All rules are made to be broken, though.
·jayfreestone.com·
When React parent components need to know their children
I wish Deno would keep doing what it does best
I wish Deno would keep doing what it does best
Deno emerged as a solution to the overwhelming configuration requirements of the modern TypeScript ecosystem by offering a zero-config, single-binary experience. By integrating essential tools for formatting, linting, and testing alongside web-standard APIs, it removed the tedious setup rituals that often deterred developers. Recently, however, Deno has pivoted toward deep Node.js compatibility, supporting npm packages and traditional module structures to accelerate adoption. This shift creates a strategic risk where high compatibility might inadvertently discourage developers from targeting Deno’s unique APIs, especially as Node.js adopts Deno’s innovations like native TypeScript support and permission models. Commercial pressures may be forcing a prioritization of rapid growth and compatibility over the patient development of a truly self-sufficient, vertically integrated toolchain. While Deno remains a powerful choice, its convergence with the legacy ecosystem suggests a move away from the radical simplicity that originally defined its mission. The ongoing convergence of runtimes serves as a vital reminder of the trade-offs between technical purity and the demands of commercial viability.
·hackers.pub·
I wish Deno would keep doing what it does best
AI versus a Grue
AI versus a Grue
Turning Chrome's Built-in AI to tackle Zork
·raymondcamden.com·
AI versus a Grue
Flow for TypeScript Users | Flow
Flow for TypeScript Users | Flow
Flow vs. TypeScript: how object exactness, variance defaults, `as` casts, type guards, and Flow's `component`/`hook`/`renders` syntax differ from TypeScript.
·flow.org·
Flow for TypeScript Users | Flow
Building an Active NavLink Component in Next.js | Aurora Scharff
Building an Active NavLink Component in Next.js | Aurora Scharff
Active link styling is one of the most common things you need in a real application. Here is how to build a reusable NavLink component for a Next.js app, taking inspiration from React Router, that handles Cache Components and flicker-free hydration.
·aurorascharff.no·
Building an Active NavLink Component in Next.js | Aurora Scharff
The Best Loading States Are No Loading States
The Best Loading States Are No Loading States
Applications often end up with all sorts of UI whose sole purpose is to occupy the space where data should eventually appear. We're all spending a surprising amount of time solving the same problem, and none of it is really product work.
·jjenzz.com·
The Best Loading States Are No Loading States
indexが無い数億レコードのテーブル集計に立ち向かう|zochang
indexが無い数億レコードのテーブル集計に立ち向かう|zochang
noteでエンジニアをやっているyamagataです。最近は1歳半の娘が話せる単語が少しずつ増えてきて、お話するのが楽しくなってきました。 1. はじめに:直面した課題 さて、弊社のダッシュボードバッチ処理において、パフォーマンスの限界に直面していました。 対象となるデータは1日分だけでも最大約320万件。関連するテーブル(スキデータのテーブルなど)は7億レコードを超え、全体では30億レコード規模に達する巨大なデータを扱っています。 当初の処理ロジックは12年前から続くもので、以下のような問題を抱えていました。 クエリ実行回数: 1日あたり最大約1,600万回 実行時
·note.zochang.com·
indexが無い数億レコードのテーブル集計に立ち向かう|zochang
実装前に設計を徹底的にインタビューし、要件を明確にするためのスキル `/grill-me`
実装前に設計を徹底的にインタビューし、要件を明確にするためのスキル `/grill-me`
コーディングエージェントの自律性が向上し、並行して複数のエージェントを動かすことが当たり前になってきた今、エージェントの動きを逐一監視することは現実的ではなくなっています。そのため実装前に人間と AI の間で共通理解を形成することが重要になっています。この記事では、実装前の設計フェーズで要件を明確にし、人間と AI の間で共通理解を形成するためのスキル `/grill-me` について紹介します。
·azukiazusa.dev·
実装前に設計を徹底的にインタビューし、要件を明確にするためのスキル `/grill-me`
Introducing Vercel Drop - Vercel
Introducing Vercel Drop - Vercel
Vercel Drop lets you deploy a file, folder, or .zip by dragging it into your browser. No Git or CLI required. Framework projects build automatically.
·vercel.com·
Introducing Vercel Drop - Vercel
Why pnpm no longer expands environment variables in a repository's .npmrc | pnpm
Why pnpm no longer expands environment variables in a repository's .npmrc | pnpm
pnpm used to expand $ placeholders everywhere it found them — including in the .npmrc and pnpm-workspace.yaml files that live inside the repository you just cloned. That turned out to be a way for a malicious repository to steal the secrets in your environment. As of v10.34.2 and v11.5.3, pnpm stops expanding environment variables in repository-controlled registry and credential settings.
·pnpm.io·
Why pnpm no longer expands environment variables in a repository's .npmrc | pnpm
tilo/smarter_json: A lenient, fast JSON processor for Ruby. It extracts strict JSON, NDJSON, JSONL, JSON5, HJSON, and messy JSON input humans or LLMs actually write — and in benchmarks it matches or beats Oj on nearly every file. SmarterJSON is opinionated: we want your JSON processing to be successful. Traditional JSON parsers are strict - SmarterJSON keep going
tilo/smarter_json: A lenient, fast JSON processor for Ruby. It extracts strict JSON, NDJSON, JSONL, JSON5, HJSON, and messy JSON input humans or LLMs actually write — and in benchmarks it matches or beats Oj on nearly every file. SmarterJSON is opinionated: we want your JSON processing to be successful. Traditional JSON parsers are strict - SmarterJSON keep going
A lenient, fast JSON processor for Ruby. It extracts strict JSON, NDJSON, JSONL, JSON5, HJSON, and messy JSON input humans or LLMs actually write — and in benchmarks it matches or beats Oj on nearl...
·github.com·
tilo/smarter_json: A lenient, fast JSON processor for Ruby. It extracts strict JSON, NDJSON, JSONL, JSON5, HJSON, and messy JSON input humans or LLMs actually write — and in benchmarks it matches or beats Oj on nearly every file. SmarterJSON is opinionated: we want your JSON processing to be successful. Traditional JSON parsers are strict - SmarterJSON keep going
When Rails Engines Are the Wrong Tool
When Rails Engines Are the Wrong Tool
This is an adapted excerpt from Chapter 15 of Modular Rails: Architecture for the Long Game, my book on building maintainable Ruby on Rails applications usin...
·davidslv.uk·
When Rails Engines Are the Wrong Tool
Special Cases in Go
Special Cases in Go
Go is a language that advertises simplicity without "special cases". But like all languages, special cases exist, sometimes in surprising places.
·dolthub.com·
Special Cases in Go
ory/talos: Web-scale and security-hardened API key server for users, services, machine to machine, and AI agents. Token derivation brings fine-grained capability tokens to avoid common API key pitfalls. Apache2 open source for indie deployments, commercial for scalable and HA.
ory/talos: Web-scale and security-hardened API key server for users, services, machine to machine, and AI agents. Token derivation brings fine-grained capability tokens to avoid common API key pitfalls. Apache2 open source for indie deployments, commercial for scalable and HA.
Web-scale and security-hardened API key server for users, services, machine to machine, and AI agents. Token derivation brings fine-grained capability tokens to avoid common API key pitfalls. Apach...
·github.com·
ory/talos: Web-scale and security-hardened API key server for users, services, machine to machine, and AI agents. Token derivation brings fine-grained capability tokens to avoid common API key pitfalls. Apache2 open source for indie deployments, commercial for scalable and HA.
AIネイティブ時代の設計書を考える | フューチャー技術ブログ
AIネイティブ時代の設計書を考える | フューチャー技術ブログ
Goならわかるシステムプログラミングなどのウェブ連載や書籍化でお世話になりまくりの鹿野さんのブログ記事が話題となっています。 golden-luckyの日記: AI時代のコンピューター技術書 これを読んで、今までモヤモヤ思っていたことに光明が射してきたので、ちょっと実験してみました。 AI開発のボトルネックは今どこか1年ほど前はあまり長時間モデルが働き続けることもなく、生成AIの月あたりのクオ
·future-architect.github.io·
AIネイティブ時代の設計書を考える | フューチャー技術ブログ