标签：#JavaScript

TL;DR It's been a while since I've done a collection (maybe month ago), but today let's look at 12 new and not-so-new projects that can really help you in development. They touch on different areas of development, but we will mainly talk about web development. If there's a project worth adding to the next collection, feel free to write about it in the comments, and maybe it will be included. 1. 🤖 OpenWork - The open source Claude Cowork alternative. And we will continue, of course, with AI projects. This tool will allow you to work in one convenient interface with many popular LLMs. OpenWork is the desktop app that lets you use 50+ LLMs. 💎 Check out the OpenWork repository ☆ 2. 💻 T3 Code - The open-source control plane for coding agents. If you know a YouTuber like Theo, then you should know this project. It's an OpenCode alternative that lets you work with AI in an easy-to-use chat interface. It enables control of the agents on your machine with a best-in-class mobile app (iOS, Android), web app and Electron-based desktop app. 💎 Check out the T3 Code repository ☆ 3. ⚙️ Summarize - Point at any URL or file. Get the gist. The first project is a small tool for extracting short info of content. Summarize was created by one of the creators of the well-known OpenClaw. Fast summaries from URLs, files, and media. 💎 Check out the Summarize repository ☆ 4. 👾 Godot - Free and open source 2D and 3D game engine A truly legendary engine like Unity or Unreal Engine for games. If you are a game developer, you should know this project. From pet projects for the university to multi-million dollar games - it gives it all. Godot Engine is a feature-packed, cross-platform game engine to create 2D and 3D games from a unified interface. It provides a comprehensive set of common tools, so that users can focus on making games without having to reinvent the wheel. 💎 Check out the Godot repository ☆ 5. 💎 React Bits - An open source collection of animated, interactive & fully customizable Rea

JavaScript Functions and Hoisting Functions are one of the most important concepts in JavaScript. A function is a reusable block of code that performs a specific task. JavaScript provides different ways to create functions, such as: Function Declaration Function Expression Arrow Function IIFE These functions can behave differently when hoisting is involved. What is Hoisting in JavaScript? Hoisting is the behavior where JavaScript processes declarations before executing the code. For example: console . log ( name ); var name = " Abishek " ; Output: undefined This happens because the var declaration is processed before execution. We can think of it like this: var name ; console . log ( name ); name = " Abishek " ; Notice that only the declaration is processed early. The value "Abishek" is assigned later. Hoisting does not physically move the code to the top. The same concept also applies to functions, but the behavior depends on how the function is created. What is a Function? A function is a reusable block of code that performs a specific task . Example: function greet () { console . log ( " Hello " ); } greet (); Output: Hello Here: function greet() → function declaration greet() → function call We can call the function whenever we need it. 1. Function Declaration A function declaration is the normal way of creating a function. greet (); function greet () { console . log ( " Hello " ); } Output: Hello Why does this work? Because function declarations are fully hoisted . JavaScript makes the function available before executing the code. Hoisting Rule Function declarations can normally be called before their declaration. Example: greet (); function greet () { console . log ( " Hello " ); } ✅ Works. 2. Function Expression A function expression is a function stored inside a variable. const greet = function () { console . log ( " Hello " ); }; greet (); Here: const greet is a variable, and the variable stores a function. Now look at this: greet (); const greet = function

Developer Relations has traditionally been built around one primary audience: Developers. We write docs for them. We build tutorials for them. We create SDK examples, maintain GitHub repositories, run communities, and answer implementation questions. But AI coding assistants are changing the developer journey. The developer may now ask an AI agent to research a library, understand an API, write an integration, or debug an error. That means your documentation can become an input to an AI agent before it ever reaches a developer. The new developer journey Previously: Developer → Search → Docs → Code Now: Developer ↓ AI Assistant ↓ Docs / GitHub / API Reference ↓ AI interprets information ↓ Code ↓ Developer reviews The developer is still the user. But the AI can become the first consumer of your developer experience. That's why documentation quality matters differently now. Write documentation that removes guessing Consider this: Use our SDK for authentication. It sounds simple, but it leaves a lot unanswered. A developer or AI agent still needs to figure out: Which package? How do I install it? Where does the API key go? Can I use it in the browser? What happens when authentication fails? What's the response format? A better example provides actual implementation context: const client = new Client({ apiKey: process.env.API_KEY }); const user = await client.users.get("123"); console.log(user); Then explain what the code does, what the inputs mean, and what can go wrong. This helps both audiences. Examples are part of the API An API reference without good examples can force developers to guess. AI agents have the same problem. If the API is: client.users.create(options) showing a complete request is more useful: const user = await client.users.create({ name: "Alex", email: " alex@example.com " }); Then document: Required fields Optional fields Response shape Validation errors Authentication requirements The more important the API, the less you want people guessing. Don'

Imagine a website where users can post comments. Someone submits this as their comment: <script> alert ( " Hello " ); </script> If the application takes that input and places it directly into the HTML it serves to other users, the browser doesn't see a comment. It sees a script tag. The vulnerability isn't that JavaScript exists on the page. JavaScript belongs on web pages. The problem is that untrusted user input ended up in a context where the browser interpreted it as executable content rather than inert text. The Core Problem A browser rendering a webpage doesn't distinguish between HTML the developer wrote and HTML that arrived through a comment field. It parses what it's given. If user input gets embedded into the page without being handled carefully, the browser processes it the same way it processes everything else. User Input ↓ Web Application ↓ HTML / DOM ↓ Browser ↓ Input interpreted as executable content Untrusted data should remain data. XSS occurs when the application allows that data to cross into a context where the browser interprets it as code or executable markup. The boundary between "string containing angle brackets" and "HTML the browser will parse" is where the vulnerability lives. Three Forms of XSS XSS shows up in a few different ways depending on where the injection happens and how the input travels. Stored XSS is when untrusted input gets saved to a database and later served to other users. The comment example above is stored XSS. An attacker submits input once, and every user who views that page subsequently receives it. The application acts as an unwitting distribution mechanism. Reflected XSS involves input that isn't stored but gets reflected back in an immediate server response. Search pages are a common example: if a query is echoed into the page as "You searched for: [query]" and the query isn't handled carefully, an attacker can craft a URL whose query parameter contains a payload. When another user visits that URL, the server refl

On July 11, 2026, I started building a project inspired by link-in-bio platforms. The idea was pretty straightforward: Create a profile → customize it → add your links → share it. So I built Rizzzler. And right now, it has 11 users. Yep. 11 😂 Not exactly the kind of number you'd put on a startup pitch deck. But those 11 users actually made me think about the project in a completely different way. The problem I noticed 🤔 I started looking at how people were using Rizzzler. And I noticed something: People would create their profile... Then disappear. Some wouldn't come back for a week. Some wouldn't even check the app for weeks. And eventually I realized something obvious. Why would they? Rizzzler was primarily a profile website. Once you've created your profile and shared your link, what reason do you have to open it again? You don't. That got me thinking: What else can we actually do with a profile? I didn't want Rizzzler to become something people set up once and completely forget about. I wanted the profile to actually do something. And that's where I got a pretty crazy idea. What if Rizzzler became more than a profile? I've used services that let you log into other applications using their account. For example: Sign in with GitHub. That got me thinking: What if Rizzzler could do something similar? Instead of Rizzzler only being a place where you create a profile... What if developers could use Rizzzler as an identity provider? And suddenly I had a new idea: Sign in with Rizzzler That was probably the craziest idea I've had for this project so far. And I decided to build it. I built my own OAuth 2.0 system 🔐 I started building the OAuth 2.0 mechanism, the developer-side integration, and the documentation. I also created a developer docs page so developers can understand how to integrate Sign in with Rizzzler into their applications. I've tested the mechanism locally, but there's an important distinction: It hasn't been properly tested by a real third-party applica

The problem: every "free" image converter wants your files If you've ever needed to quickly convert a batch of photos to WebP or shrink a folder of PNGs before shipping them to production, you've probably run into the same annoyance I did: most " free online converters " require you to upload your files to a remote server first. That's fine for a random screenshot. It's not fine when the images are: Unreleased product shots under NDA Client assets you're not supposed to redistribute Personal photos you'd rather not hand to a third-party server you know nothing about So I started looking at what the browser can actually do on its own — and it turns out, more than most people assume. What the browser can already do Modern browsers ship with everything needed to decode, resize, re-encode, and compress images entirely client-side: + toBlob() / toDataURL() for re-encoding to JPG, PNG, or WebP The File API for drag-and-drop and batch uploads Web Workers to keep the UI thread responsive during batch conversion JSZip (or similar) to bundle multiple converted files into a single downloadable ZIP None of this requires a backend. No image ever has to leave the user's machine. Why this matters beyond privacy Besides the obvious privacy win, doing conversion in-browser has some nice side effects: No server costs that scale with usage. A traditional image-conversion API has to provision compute for every request. A client-side tool scales for free — the user's own CPU does the work. No upload/download round trip. For large batches, skipping the network entirely is often faster than uploading to a server and waiting for a processed file back. Works offline once loaded. A PWA-style client-side converter keeps working even with a flaky connection. The trade-offs It's not free lunch: Very large batches (hundreds of high-res images) can strain the main thread if you're not careful with Web Workers. WebP/AVIF encoder quality and speed vary by browser engine, so you can't guarantee byte

async/await without the pitfalls Async/await is the bread and butter of modern JavaScript. It makes asynchronous code look synchronous, which is great for readability. But it comes with its own set of footguns that can bite you in production. Here's how to avoid them. Pitfall 1: Forgetting await in a loop You might write something like this, expecting each request to finish before the next starts: async function fetchAll ( urls ) { const results = []; for ( const url of urls ) { const res = await fetch ( url ); // this is fine, but see below results . push ( await res . json ()); } return results ; } That's actually correct. The issue arises when you forget await inside a .map() or .forEach() : // Wrong: map returns an array of promises, not data const data = urls . map ( async ( url ) => { const res = await fetch ( url ); return res . json (); }); // data is now an array of promises, not the JSON data async functions always return a promise. So if you use map with an async callback, you get an array of promises. To fix it, use Promise.all : const data = await Promise . all ( urls . map ( async ( url ) => { const res = await fetch ( url ); return res . json (); })); But beware: Promise.all fails fast. If one request fails, the whole thing rejects. If you need to handle failures individually, use Promise.allSettled instead. Pitfall 2: Swallowing errors silently A common mistake is to catch an error and do nothing, which makes debugging a nightmare: try { const data = await fetchData (); // process data } catch ( error ) { // do nothing? bad! } Always at least log the error. Even better, handle it gracefully or rethrow it: try { const data = await fetchData (); } catch ( error ) { console . error ( ' Failed to fetch data: ' , error ); throw error ; // rethrow if you want the caller to handle it } If you're using async/await , unhandled promise rejections can crash your app in Node.js. Always have a catch or a global handler. Pitfall 3: Sequential execution when you ne

A few weeks ago I built a free online Merge PDF tool that runs 100% in the browser. Today I'm sharing its sibling: a Split PDF tool using the same library — pdf-lib — with zero file uploads, zero watermark, and zero server code. You can try it live here: https://yourutilityhub.com/pdf/split-pdf Why split PDFs in the browser? Most online PDF tools upload your file to a server — which means your document is never truly private. Splitting pages locally means: No uploads — nothing leaves your device No watermark or signup Free — no per-page charges Works offline, fast, for files of any size (limited by your browser's memory) The plan We'll load the PDF, pick a page range (or specific pages), copy those pages into a fresh PDFDocument , and save the result — all with pdf-lib . Let's walk through the full working component . 1. Install and import npm install pdf-lib import { PDFDocument } from " pdf-lib " ; 2. Load the uploaded file const arrayBuffer = await file . arrayBuffer (); const pdf = await PDFDocument . load ( arrayBuffer ); const totalPages = pdf . getPageCount (); PDFDocument.load() accepts an ArrayBuffer . We read it straight from the File object — no server involved. 3. Split by page range (e.g. 1-5 or 3- ) const parts = pageRange . split ( " - " ); const startRaw = parseInt ( parts [ 0 ]. trim (), 10 ); const endRaw = parts [ 1 ]. trim () === "" ? totalPages : parseInt ( parts [ 1 ]. trim (), 10 ); // validate 1..totalPages const startPage = Math . min ( startRaw , endRaw ) - 1 ; // 0-based const endPage = Math . max ( startRaw , endRaw ) - 1 ; const newPdf = await PDFDocument . create (); const pageIndices = []; for ( let i = startPage ; i <= endPage ; i ++ ) { pageIndices . push ( i ); } const copiedPages = await newPdf . copyPages ( pdf , pageIndices ); copiedPages . forEach ( page => newPdf . addPage ( page )); The trick: copyPages() wants 0-based indices , but users type 1-based page numbers, so we subtract 1. "3-" with an empty end means "to the last pa

Open a page and it can start guessing which browser extensions you run before you click a thing. Not "extensions in general" - which ones . Your password manager, your ad blocker, the wallet, the internal tool your employer ships, the accessibility extension you depend on. The page never asks and you never see it happen. This is not a bug in Chrome. It is the sum of a few features working exactly as designed, and the people best placed to close it are extension authors who mostly do not know they left it open. I maintain an extension and a library that talks to it, so I have spent real time on the detectable side of this. Here is how a page does it, what the answer is worth to whoever is asking, and what actually stops it. Technique one: ask the extension directly Some extensions accept messages from web pages on purpose - our own does, so a customer's "report a bug" button can tell whether the extension is there. The API is chrome.runtime.sendMessage : chrome . runtime . sendMessage ( EXTENSION_ID , { type : ' ping ' }, ( reply ) => { if ( reply ) { // it is installed, and it answered } }); For a page to be allowed to send that message, the extension has to list the page's origin in its manifest, under externally_connectable . Authors who want their extension to work with any site reach for the wildcard: "externally_connectable" : { "matches" : [ "<all_urls>" ] } And that one line is the door. <all_urls> does not mean "my customers' sites". It means every site on the internet may now open a channel to this extension - which means every site may ping it and learn whether you have it. The convenience the author wanted for their own pages, they handed to everybody's. This technique is narrow, because it only finds extensions that chose to talk to pages. The next one is not narrow. Technique two: knock on the extension's own files Extensions ship assets - icons, injected stylesheets, images. Any asset marked web-accessible is reachable at a fixed URL built from the ext

GitHub热门项目 | [CVPR'25 Oral] MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision | Stars: 2,863 | 29 stars today | 语言: JavaScript

The Challenge: Realtime in the Age of Server Components The paradigm shift toward React Server Components (RSC) and the Next.js App Router has fundamentally changed how we architect web applications. We are now defaulting to server-side rendering, which is fantastic for performance, SEO, and initial load times. However, a common friction point arises when we need to inject high-frequency, bidirectional realtime data into these server-rendered pages. Too often, developers fall into the trap of importing heavy socket libraries directly into their server components or wrapping their entire application in massive context providers, effectively bloating the client bundle and negating the performance gains of the App Router. The Solution: The "Client Island" Pattern Instead of fighting the architecture, we can embrace "Client Islands"—a pattern where we isolate the stateful, client-side logic into a tiny, focused leaf component. By keeping the WebSocket management strictly client-side, we ensure that our server-rendered pages remain lightweight, fast, and cacheable. Implementing the WebSocket Island The goal is to keep the WebSocket connection lifecycle outside of the rendering flow. We utilize useEffect to manage the connection, ensuring it only runs on the client, and we tap into data fetching libraries like TanStack Query or SWR to surgically update the UI. ' use client ' ; import { useEffect } from ' react ' ; import { useQueryClient } from ' @tanstack/react-query ' ; export function RealtimeSync ({ token }) { const queryClient = useQueryClient (); useEffect (() => { const ws = new WebSocket ( `wss://realtime.example.com?token= ${ token } ` ); ws . onmessage = ( event ) => { const data = JSON . parse ( event . data ); queryClient . setQueryData ([ ' items ' ], data ); }; return () => ws . close (); }, [ token , queryClient ]); return null ; // This component renders nothing, just manages the side effect } Persistence via RootLayout To prevent the connection from dropp

Three parts into this series, and if you'd asked me to define the word sitting underneath every...

In this post I'll show how to merge PDF files entirely in the browser using PDF.js and pdf-lib — no server, no file upload, no backend. Everything runs on the user's machine, which is great for privacy and for keeping hosting costs at zero (it's just a static site). Why process PDFs on the client? Most "free" PDF websites quietly upload your documents to their server, which: Exposes private/sensitive files to third parties Imposes size limits Often slaps a watermark on the output Requires you to trust their storage If you handle PDFs with client-side JavaScript (WebAssembly / WASM + PDF.js), none of that happens. The user's file never leaves their device, and you don't need a backend at all — so it's cheap and private. Caveats pdf-lib works well with standard PDFs; heavily encrypted or unusual documents may need extra handling. Very large PDFs are memory-hungry since everything is client-side, but for typical documents it's fast and free. Some complex PDFs with unusual fonts can lose fidelity — test on your own files first. Try it I packaged this approach (plus split, compress, rotate, unlock, image-to-PDF) into a free no-upload tool: https://yourutilityhub.com/pdf/merge-pdf The whole project is open source: https://github.com/Jalal-khn/utilityhub- If you have questions about the architecture or want a deeper dive on any part, ask away. The basic idea Read the input file with FileReader Parse it with pdf-lib (a pure-JS PDF library) Copy the source pages into a new document Save the merged PDF and trigger a download Here's the core function: js import { PDFDocument } from "pdf-lib"; async function mergePdfs(files) { const merged = await PDFDocument.create(); for (const file of files) { const bytes = await file.arrayBuffer(); const src = await PDFDocument.load(bytes, { ignoreEncryption: true }); const pages = await merged.copyPages(src, src.getPageIndices()); pages.forEach((page) => merged.addPage(page)); } const out = await merged.save(); return new Blob([out], { typ

GitHub热门项目 | | Stars: 317 | 27 stars today | 语言: JavaScript

Our tool transcribes audio in the browser — Whisper running locally via transformers.js , no upload. It worked fine, until analytics showed something too clean to be a coincidence: .mov uploads on mobile failed 100% of the time. Not 90%. Every single one. Desktop had never reported a single .mov failure. This is what I found, and how it got fixed without pulling in ffmpeg.wasm or WebCodecs. The 30-second reproduction I took one AAC audio track and put it in two containers — same encoder, same bytes for the audio itself, only the wrapper differs: const buf = await file . arrayBuffer (); await new AudioContext (). decodeAudioData ( buf ); On an iPhone 17 Pro simulator (iOS 18.7 / Safari 26.5): File iOS Safari Chromium sample.mov (ftyp qt ) EncodingError: Decoding failed OK sample.mp4 (ftyp isom ) OK OK So it isn't the codec. It's the container. The obvious fix that doesn't work First instinct: it's the brand in the ftyp box. Patch qt → isom , four bytes, done. It still fails. I'm writing this down so nobody else burns an afternoon on it. The ftyp brand is not what Safari looks at. The difference lives inside moov . The actual root cause Dig down to moov → trak → mdia → minf → stbl → stsd — the sample description that tells the decoder how the audio is encoded. Both files carry an mp4a entry. They are not the same mp4a entry: QuickTime writes: MP4 expects: version = 1 <— version = 0 compressionID = -2 (fffe) <— compressionID = 0 + 16 bytes of v1 extension <— (absent) esds wrapped in a 'wave' box <— esds is a direct child extra 'chan' channel layout (absent) iOS Safari's decodeAudioData only accepts a version 0 audio sample entry. Chromium accepts both — which is exactly why desktop never saw this and mobile never survived it. That version field is a uint16 . Two bytes decide whether the file plays. The fix: rebuild the container, don't touch the codec Since the audio bitstream is already valid AAC, nothing needs to be re-encoded. The job is pure byte plumbing: extract

Hi everyone! 👋 I just published v1.0.0 of my very first web project: an installable Progressive Web App (PWA) built from scratch using HTML, CSS, and Vanilla JavaScript. I designed it to be extra accessible and versatile, especially for older adults, shopkeepers, students, and everyday users. ✨ Key Features Multiple Modes: Standard, Scientific, Sales, Interest (Simple & Compound), Unit Conversions, BMI, Age, and Adjustable Percentage. Customization: Adjustable button sizes and custom background themes (including Dark and Light modes). Offline PWA Support: Service worker caching allows full offline functionality and direct installation on mobile or desktop devices. 🔗 Try It Out & Explore Code 🚀 Live Demo: mdalif027-tech.github.io/easy-calculator 💻 GitHub Repository: github.com/mdalif027-tech/easy-calculator 💬 Looking for Feedback Since this is my first app, I would really appreciate any thoughts on: Mobile touch layout and responsiveness across screen sizes. UI/UX design or theme improvements. Recommendations for features to add in future releases. Thank you so much for checking it out!

Sometimes software development reaches a point where the tools designed to make your job easier start becoming part of the job. I ran into that with browser debugging. I wanted something that should have been simple: Set a breakpoint. Press F5. Debug my JavaScript. Instead, I found myself spending too much time thinking about development servers, browser launch configuration, debugger connections, ports, profiles, and the debugging environment itself. That led to a simple question: What if browser debugging could go back to convention over configuration? So I built CloudIDEaaS JavaScript Debugger . ⚡ The Goal: Press F5 and Debug The philosophy behind CloudIDEaaS is straightforward: Spend your time debugging your application instead of debugging your debugging environment. For a straightforward JavaScript or HTML project, I wanted the workflow to look like this: Set a breakpoint. Press F5 . Start debugging. Behind those three steps, CloudIDEaaS can start the local web server, launch Chrome, establish the debugging connection, configure your breakpoints, and then load the application. The important part is that you don't have to think about most of that. 🔴 Real Debugging Inside VS Code This isn't intended to replace Chrome DevTools or compete feature-for-feature with every large JavaScript debugging platform. It's focused on providing the debugging features I use most often directly inside Visual Studio Code: 🔴 Source and conditional breakpoints 👣 Step over, step into, and step out ▶️ Continue and pause 🔍 Local variables and object inspection 📚 Scopes and call stacks 🧮 Expression evaluation ⚠️ Exception breakpoint configuration 🌐 A built-in local web server One feature that was particularly important to me was startup breakpoints . The debugger establishes the connection and configures your breakpoints before loading the application, making it possible to catch JavaScript that executes during startup. 🧠 What's Actually Happening Under the Hood? Building the debugger a

1. Problem Statement I wanted to contribute to an open source project called WikiEduDashboard , a web application built by Wiki Education. It helps instructors and program leaders run Wikipedia-editing classes and campaigns: students join a course, make edits to Wikipedia, and the dashboard tracks their work. To contribute code to this project, I first need a working copy of it running on my own PC. This is called a "local development environment." Without it, I can't test any changes I make before sending them back to the project. The problem: this project was built with tools that work best on Mac or Linux, not on plain Windows. So the first challenge wasn't even the project itself, it was figuring out how to run a Linux-friendly project on a Windows PC. 2. The Solution (High Level) Instead of fighting Windows directly, we used a feature built into Windows called WSL (Windows Subsystem for Linux) . WSL lets a real Linux system (Ubuntu, in our case) run inside Windows, side by side with your normal Windows apps. It's not a separate computer or a virtual machine you have to babysit, it just works like an extra terminal environment on the same PC. Once inside Ubuntu, we could follow the project's official setup instructions exactly as written, since those instructions assume a Mac or Linux machine. The overall plan looked like this: Get a Linux environment running on Windows (WSL + Ubuntu) Get a personal copy of the project's code (fork it on GitHub, then clone it) Install the programming language the project is built with (Ruby) Run the project's automated setup script, which installs the rest of the required tools (database, background job system, etc.) Start the actual application and view it in a browser Build the frontend (the visual, interactive part of the site) Set up an editor (VS Code) that can actually see and edit the code living inside Ubuntu 3. Step by Step: What We Did and Why Step 1: Install WSL and Ubuntu What: WSL is a Windows feature that runs a re

You type "Hi" and the computer stores 01001000 01101001 . Text is just numbers wearing a costume. Here is exactly how a string turns into binary, why UTF-8 matters, and how to do the conversion both ways in a few lines of JavaScript. What "binary" actually means here Computers do not store letters. They store numbers, and every number is a run of ones and zeros. Each character maps to a code point, that number becomes a byte, and each byte is written as eight bits . The letter A has the ASCII code 65. In binary that is: 65 = 01000001 Lowercase a is 97, which is 01100001 . So the whole word "Hi" ( H = 72, i = 105) becomes: 01001000 01101001 Group the bits into bytes of 8 and you can read any binary string back into text. Text to binary in JavaScript The reliable way is TextEncoder . It hands you the raw UTF-8 bytes, so you do not have to worry about character codes above 127. function textToBinary ( text ) { const bytes = new TextEncoder (). encode ( text ); return Array . from ( bytes ) . map ( b => b . toString ( 2 ). padStart ( 8 , " 0 " )) . join ( " " ); } textToBinary ( " Hi " ); // "01001000 01101001" toString(2) gives the binary digits, and padStart(8, "0") keeps every byte a full 8 bits. Without the pad, H would come out as 1001000 (7 bits) and the string would be impossible to split back cleanly. Binary back to text Reverse the process: strip spaces, cut the string into 8-bit chunks, parse each chunk as a base-2 number, then decode the bytes with TextDecoder . function binaryToText ( bin ) { const bits = bin . replace ( / \s +/g , "" ); const bytes = new Uint8Array ( bits . length / 8 ); for ( let i = 0 ; i < bytes . length ; i ++ ) { bytes [ i ] = parseInt ( bits . slice ( i * 8 , i * 8 + 8 ), 2 ); } return new TextDecoder ( " utf-8 " ). decode ( bytes ); } binaryToText ( " 01001000 01101001 " ); // "Hi" Two checks worth adding in real code: reject anything that is not 0 or 1 , and reject a bit count that is not a multiple of 8. Those two guards catch almo

When applying for engineering roles, automated applicant tracking systems (ATS) often silently reject candidates due to parsing blockers like multi-column layouts, missing quantitative metrics, or non-standard font embeddings. To fix this latency bottleneck, I built MyRizzume ( https://myrizzume.me ) — designed to parse and score resumes end-to-end in under 1,000ms. What it checks: Layout Integrity: Validates that column and table layouts won't merge or scramble text during ATS ingestion. Action Verb Strength: Highlights passive phrases and suggests active, quantifiable replacements. Keyword Density: Compares section headers and skill blocks against common parser taxonomies. Try it out live at https://myrizzume.me and let me know how it handles your layout!