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开发者

[Showoff Saturday] Website where you can browse DJ sets by city on a map

Been DJing for years and always wanted a way to explore what people are playing in specific cities. Couldn't find anything like that, so I had a crack at it. Click a country, pick a city, and browse DJ sets recorded there. Uses Mixcloud sets and you can browse and play them in browser. https://setatlas.app Happy to hear any feedback or suggestions. submitted by /u/Leather_Catch2136 [link] [留言]

2026-06-06 原文 →
开发者

Finding a article about new algorithm on web rendering

Sorry to bother you guys, I just cannot remember or find about an article which about a developer find a new way to make thing faster on frontend (html or something) rendering about serveral months or last year. Anyone remember it? Please tell me. Thank you. submitted by /u/Full_Environment_205 [link] [留言]

2026-06-06 原文 →
AI 资讯

I made a website that let's you edit any supported image on the internet for free

I've been building an image editor that basically lets you edit images, on the fly. Just paste the URL, and you can start editing the image pretty much instantly. Essentially removing the need to download, upload etc. It's very convenient for those who want to quickly make edits. Completely free to use, no login or signup required to use. You can see it here: canvix.me I officially got approved for by google for my official chrome extension, which allows you to right-click any supported image on the internet (png jpg webp etc), Edit image with Canvix option. Right away, you can start editing the image. You can see how it works by screenshot posted on the chrome extension page https://chromewebstore.google.com/detail/edit-image-with-canvix/akjooicgafjjcnpjdfnaajkipciedbco I especially made this for users who constantly need to edit images like me. This in beta testing still, any feedback would be greatly appreciated to improve it. submitted by /u/Filerax_com [link] [留言]

2026-06-06 原文 →
AI 资讯

Building letterbookd

i deleted my earlier post because yeah, it sounded too ai/slop. fair criticism tbh. english is not my first language, so i used ai/translation to explain the project better, but it made the whole thing sound fake and too polished. my bad. so i’ll try to explain it myself this time. so, pardon the wording... i like tracking what i read. i like ratings, reviews, shelves, seeing what other people are reading, making lists, all that stuff. but goodreads always feels weird for me to use. not because the idea is bad, actually the idea is great, but the app/site feels old, messy and not really social enough for something that supposed to be about taste. so i started building my own book tracking app. it’s called Cilt (NOT CLIT!!!!!!!!) for now: https://cilt.app/ the basic idea is kind of “letterboxd for books”, but i know that sentence is overused as hell. what i mean is, i want logging books to feel simple and a bit fun, and after some time your profile should feel like an archive of your reading taste, not just random database list. right now / planned features are: - log the books you read -rate and review them -make shelves like reading, want to read, favorites etc. -create public lists -follow other readers -see what people with similar taste are reading -discover books from reviews/lists, not only generic ratings -track reading goals and stats -search books by title, author, isbn, publisher -have a profile that feels more personal i know there are already apps for this. i’m not saying i invented the wheel or anything. my problem is most alternatives either feels too old, too plain, or they don’t really have the social/taste part that makes letterboxd or even steam fun. also fyi: i didn’t use vibe coding for the whole project. i used it mostly on the frontend side, and when i use it i prefer to say it openly. it’s still very early, so feedback would be really useful. especially from people who still use goodreads even they hate it, or people who tried storygraph/fable

2026-06-06 原文 →
AI 资讯

Drift Protocol $285M Exploit - North Korean APT Attack on Solana

On April 1, 2026, Solana's largest decentralized perpetual futures exchange Drift Protocol suffered an attack, losing approximately $285 million . This is the second-largest DeFi hack of 2026 (behind KelpDAO's $292M attack the same month). Together, these two incidents totaled $577M — 76% of all DeFi stolen funds in 2026 . Key Finding : This was not a smart contract vulnerability. The attacker penetrated protocol personnel through social engineering , used Solana's durable nonce feature to pre-sign malicious transactions, and drained the entire treasury in 12 minutes . Mandiant confirmed the attacker as North Korean state-sponsored APT group UNC6862. ⏱️ Attack Timeline Time Event 6 months prior North Korean hackers establish fake trading company identities, attend crypto industry events Weeks prior Operatives attend crypto conferences in person, build deep trust with Drift contributors Late Feb - Early Mar Telegram group discussions about trading strategies, posing as partners Dec 2025 - Jan 2026 Fake company "Ecosystem Vault" builds partnership with Drift, deposits $1M+ Feb - Mar Attackers gain access to some contributors' code repositories Mar 23 Create 4 malicious wallets using Solana durable nonce feature Mar 27 Security Council migrates to 0-second timelock , removing safety buffer Apr 1, 16:06:09 UTC Execute pre-signed malicious transactions 16:06 - 16:18 UTC Treasury completely drained in 12 minutes Post-Apr 1 Funds swapped via Jupiter, bridged to Ethereum via CCTP, mostly dormant 🔧 Attack Technical Analysis Initial Penetration The attackers used a multi-layered social engineering + technical infiltration combination: HUMINT Operation Spent months building credible identities, attending global industry events Used intermediaries rather than direct contact (classic Lazarus tactic) ZachXBT noted this layered identity structure is a hallmark of Lazarus operations Malicious Code Injection Shared code repositories containing malicious code Exploited unpatched VSCo

2026-06-06 原文 →
AI 资讯

Astro + Cloudflare Pages: 3 Deploy Bugs You'll Probably Hit

I've been building a static Astro site on Cloudflare Pages over the last few weeks. Sharing the 3 deployment bugs that cost me the most time, in case they save anyone else the same loop. Setup Astro 5 + Cloudflare Pages + Tailwind 4. Content lives in a few JSON files; each page is a dynamic route mapped over the data. Free-tier hosting, no backend. Standard static-first stack. Bug 1: Trailing-slash 307 chain I started with trailingSlash: 'never' in Astro config. Build output went to dist/foo/index.html . Result: Astro emitted canonical tags as /foo (no slash), but Cloudflare Pages served /foo/ (auto-adding the slash via 307). Google Search Console flagged pages as "Redirect error" because the canonical URL pointed at a redirect chain instead of a real 200. I first tried build.format: 'file' to get flat dist/foo.html output, hoping that would bypass the trailing slash. That made it worse — Cloudflare still 307-stripped, but now to a non-existent .html file → 404. Fix: stop fighting the platform. ​ js // astro.config.mjs export default defineConfig({ trailingSlash: 'always', // ... }); ​ trailingSlash: 'always' plus default directory build aligns the canonical URL with what Pages actually serves. The redirect errors resolved on next re-crawl. Bug 2: _redirects rejected at deploy I tried to do a www → apex 301 in public/_redirects : https://www.example.com/* https://example.com/:splat 301! Cloudflare rejected the deploy with three validation errors: ​ Line 13: Only relative URLs are allowed. Line 22: Duplicate rule for path /foo. Line 23: Duplicate rule for path /bar. ​ Pages tightened _redirects validation — absolute-URL sources aren't accepted anymore. The duplicate errors were because Astro's own redirects config in astro.config.mjs generates HTML meta-refresh files that Pages parses as implicit redirect rules — conflicting with my explicit ones. Fix: delete _redirects entirely. Use a Cloudflare Redirect Rule from the dashboard for cross-host 301s (Wildcard pattern,

2026-06-06 原文 →
AI 资讯

I Benchmarked Lynkr Against LiteLLM on the Same Backends.

I Benchmarked Lynkr Against LiteLLM on the Same Backends. Lynkr Was Cheaper for Tool-Heavy Workloads Founder disclosure: I built Lynkr, so take this as a technical benchmark write-up, not a neutral industry report. The numbers below come from the same backend providers on both gateways. If you're routing AI coding traffic through a gateway, just switching providers is not enough. The real savings come from reducing the tokens that ever reach the model in the first place. I ran Lynkr and LiteLLM against the same backends — Ollama locally, Moonshot, and Azure OpenAI — across 9 scenarios. On the scenarios that actually look like agentic coding work, Lynkr was cheaper because it does three things before forwarding the request upstream: smart tool selection, TOON compression, and semantic caching. The short version Lynkr was measurably better on the cost-sensitive parts of the workload: Smart tool selection: 53% fewer input tokens, 52% lower cost TOON JSON compression: 87.6% fewer billed tokens on a large tool result, 50% lower cost Semantic cache: 171ms cache-hit response vs 3,282ms on the repeat query path Tier routing: escalated hard prompts to stronger models instead of blindly sending everything to the cheapest route Area Lynkr result Why it mattered Tool selection 53% fewer tokens Removes irrelevant tool schemas TOON compression 87.6% fewer tokens Shrinks large JSON tool outputs Semantic cache 171ms cache hit Avoids repeat model calls Tier routing Escalates hard prompts Doesn’t over-optimize for cheapest path This matters if you're running Claude Code, Codex, Cursor, or similar agent workflows where tools, file reads, grep output, and repeated context dominate your token bill. Setup Same benchmark inputs, same providers, same request shape. Machine: macOS on Apple Silicon Lynkr: v9.3.2 on Node 20 LiteLLM: v1.87.1 on Python 3.12 Backends used: Ollama local, Moonshot, Azure OpenAI Scenarios: 9 total across simple prompts, tools, history, cache, and routing Each scena

2026-06-06 原文 →
AI 资讯

Launching a Website on AWS in 2026: The Complete Guide for All Skill Levels

Launching a fast, secure, and scalable website no longer requires thousands in upfront server costs or dedicated DevOps teams. As of 2026, AWS powers 32% of the global public cloud market, offering flexible hosting options for every use case: from a 1-page personal portfolio to a high-traffic enterprise e-commerce platform. Whether you’re a beginner building your first site or a senior developer launching a production SaaS app, AWS lets you pay only for resources you use, with built-in tools for global performance, security, and automated deployments. This guide breaks down every AWS website hosting option, walks you through step-by-step setup for the most cost-effective popular stack, shares security best practices, and includes a transparent cost breakdown to help you avoid unexpected bills. Table of Contents How to Choose the Right AWS Website Hosting Option for Your Use Case Step-by-Step Guide: Launch a Static Website on AWS (S3 + CloudFront + Route 53) Deploy Modern Web Apps Faster with AWS Amplify Hosting Dynamic Website Hosting Options on AWS Critical Security Best Practices for AWS-Hosted Websites AWS Website Hosting Cost Breakdown (2026) Common Mistakes to Avoid When Launching a Website on AWS Conclusion References How to Choose the Right AWS Website Hosting Option for Your Use Case First, classify your website to pick the most cost-effective, low-overhead stack: Static vs Dynamic Websites Static websites : Made of pre-built HTML, CSS, JS, and media files with no server-side processing. Ideal for portfolios, landing pages, blogs, documentation, and marketing sites. Dynamic websites : Process user input, serve personalized content, or connect to databases. Ideal for WordPress, e-commerce, SaaS apps, social platforms, and membership sites. Quick Use Case Mapping Website Type Recommended AWS Stack Small static site / portfolio S3 + CloudFront + Route 53 Modern React/Next.js/Vue app with CI/CD AWS Amplify Small WordPress / LAMP stack site Amazon Lightsail Custo

2026-06-06 原文 →
AI 资讯

Free DNS health checker, full audit in one query

I put together a DNS audit tool that checks NS redundancy, MX, SPF, DMARC, DKIM, DNSSEC chain, DNSBL blacklists, SSL cert and HTTP/2-3 support, all in a single query. Results are visual, no need to dig through command line output. No account needed. https://yenidns.com Feedback welcome, what would make this more useful for your workflow? submitted by /u/Acceptable_Voice500 [link] [留言]

2026-06-06 原文 →
AI 资讯

War Owned

Hi! I just created a project where people can interact with someone who has experienced the effects of the war in Ukraine. The project consisted of interviewing different families that suffered during the war to understand the situation on an emotional and day-to-day level. Then, using this information, I created an AI agent with the sole purpose of discussing what it is like to live through a conflict. The goal is to reach people who may have forgotten about the conflict and make them more sensitive about the ongoing war. You can find the access to the project here: War Owned Project Please, can you share your thoughts? Thank you and warm regards from Barcelona! submitted by /u/Budget-Cheesecake-19 [link] [留言]

2026-06-06 原文 →
AI 资讯

Why Would a Site Like AMC Queue Visitors Before They Even Reach the Homepage?

noticed the AMC theatres site has had queue times of over an hour today… just to get onto the homepage. That’s a bit strange right? AMC has ~650 locations in the US. Assuming ~10 screens per location, ~5 showings per screen per day, and ~300 seats per auditorium (probably a generous estimate), that’s roughly 10 million available seats per day. Even if site traffic is 5x higher than actual ticket sales, we’re still talking about something in the ballpark of 50 million daily visitors. That’s obviously not nothing, but it also doesn’t seem like an absurd amount of traffic for a company this large. I’m curious what the technical/business rationale could be? submitted by /u/u16scharpf [link] [留言]

2026-06-06 原文 →
AI 资讯

Is switching to local AI worth it for web development?

I am a web developer who specializes in dashboard-like web applications. Due to recent price hikes for GitHub Copilot, I have been considering running a local model to help out with debugging, multi-file edits, learning about the codebase, and small-medium tasks. I intend to continue using GitHub Copilot or Claude Code for more advanced tasks, but I want to minimize token costs. I cannot test a local model myself right now because I lack the hardware to do so, which is why I am asking here. If I decided on using a local model, I would likely need to upgrade my graphics card from a 3080 to a 3090. Has anyone here tried running a local AI model? Which one are you using? How well does it work compared to Claude Sonnet 4.5 or other AI models? I would appreciate any advice or feedback. submitted by /u/Various-Complex-1582 [link] [留言]

2026-06-06 原文 →
AI 资讯

How do you protect yourself from unexpected usage charges - think aws/netlify?

On the side after work I've been experimenting a bit with aws cloud launching my own apps and website (its mostly for hobby/for fun not really expecting income but maybe one day) anyways, one of my website a couple months ago was hit by a bot attack which made my netlify monthly bill go from $20 to $140 in one day Which spooked me im not going to lie. And my knowledge of devops thing is so limited that I had to resort to asking ai to help debug this. We found that there was 8 million botted requests sent to my frontend website and on my .netify.app link netlify does not give you ddos protection unless you pay extra. My actual domain was protected by cloudfare rate limit I didnt even know I had this secondary domain for that website. Anyways that was useful discovery now I feel safer about netlify at least. I don't really want to give up this hobby. Is there anyway to get predictable billing I don't even mind if they shutdown my app if it exceeds usage. I read that fly.io is based on credit usage. Is that good for backend? submitted by /u/Ok_Indication_3656 [link] [留言]

2026-06-06 原文 →
AI 资讯

Learn SQL Once, Use It for 30 Years: Why the Skill Doesn't Expire

A post titled "Learn SQL Once, Use It for 30 Years" hit the front page of r/programming this week (307 points, 48 comments). The claim sounds like the kind of thing a database vendor would put on a billboard, so I went looking for the part that holds up. It turns out the longevity is not marketing. It is a property of how the language was designed, and it is the reason SQL is one of the few skills on a developer's resume that does not quietly expire. I run a site that compares developer tools, which means I spend a lot of time watching technologies rise, peak, and get replaced. Most of what you learn in this field has a half-life measured in single-digit years. The framework you mastered in 2019 is legacy by 2024. SQL is the strange exception, and the reasons are worth understanding before you decide where to spend your next month of learning. Where the staying power comes from SQL did not start as a language. It started as a math paper. In 1970, Edgar Codd published "A Relational Model of Data for Large Shared Data Banks," which proposed organizing data into tables of rows and columns with formal rules for combining them. IBM built a query language on top of that model in the mid-1970s, called it SEQUEL, and later renamed it SQL after a trademark conflict. The important detail is the order: the model came first, the language second. SQL is a surface over a mathematical foundation that has not needed to change. That foundation is why the skill compounds instead of decaying. When you learn SQL, you are not memorizing one vendor's API. You are learning the relational model, and the model is the same whether the data sits in Postgres, MySQL, SQLite, Oracle, or SQL Server. A join is a join everywhere. Move from one database to another and the syntax shifts at the edges, but the way you think about the problem carries over intact. Compare that to a frontend framework, where moving stacks means relearning how to think, not just how to type. Declarative is the whole trick

2026-06-06 原文 →
AI 资讯

Help with WordPress Site

Hi everyone, I've been working on building my own website for my upcoming small business in the pest control. My set up is cloudflare for domain, Hostinger for hosting, and WordPress for CMS. I have a fair amount of coding and tech knowledge (Code simple things in a different languages and understand enough abouting coding to understand most non robust code; have also built a couple simple websites in wordpress) and really want to do things right. My question is what tools, choices, or practices are there that someone trying to research the space wouldn't be able to easily find that provide high value? Things deeper in scope than just building pages with custom blocks, using plug ins, and tweaking settings. Essentially, of the millions of tools and implementations existing in this space, where should a person looking to move from amateur to advanced but not career web dev look? And what is the value in those tools or choices? Additionally. outside of page speed insights, what audits are actually worth running to ensure everything is secure and running as smooth as possible without costing an arm and leg cumulatively? If you were a single person looking to build as professional of a website as possible, in a reasonable timeline (a month or two), what things would you really be focused on? My overall goal is to build everything as close to professional as a single person realistically could, so if you guys could help, I'd really appreciate it! Thanks in advance submitted by /u/ChestnetR [link] [留言]

2026-06-06 原文 →
开发者

Where modern PHP stands in 2026: deployment, architecture, typing, and concurrency

Hello everyone, PHP comes up here from time to time, and I've noticed the discussion is usually based on what the language looked like 5+ years ago. Since I work with it every day and have genuinely come to enjoy it, I wrote a short article recapping where it actually stands today. It covers modern deployment (FrankenPHP, Docker), software architecture (modular monoliths, the Symfony kernel, agents), the type system and its tooling (PHPStan, PHP CS Fixer), and the state of concurrency (ReactPHP, Swoole, the True Async RFC). Full article: https://morice.live/posts/your-next-project-will-run-on-php/ Let me know if I missed anything, or if you'd like me to go deeper on a specific topic! submitted by /u/andre_ange_marcel [link] [留言]

2026-06-06 原文 →
AI 资讯

When building for better UX accidentally cuts your DB writes by ~95%

A bit of context: I'm having fun building my app. I'm trying to built something truly great for monitoring. I run a pool of workers on a couple of VPSes and probes about 10k endpoints on a tight loop down to every 15 seconds. The part that was quietly bleeding money, was that every probe result got written to our document db and all dashboards subscribed to those documents with real-time listeners (onSnapshot). In Firestore that's the obvious way to build a live dashboard and it actually works great until you draw out the actual data flow: workers write on every cycle every write fans out to a read to every browser that is running the dashboard so cost just scales with amount of cycles and open dashboards The database quietly became a message bus with billing on every message. I guess this is how you learn about proper architecture the hard way. 😄 A good Friday evening, with a glass of whisky, I decided to make something cool. I wanted a true live experience for the users, directly on the website. Basically something that looked directly into the VPS. So I flipped it. The WebSocket is the source of truth for live fields The DB gets demoted to config + state transition "Still up" heartbeats get batched, instead of writing "200 OK" everything cycle, we switch to a transition model and flush the no-change on a interval Results: ~95% fewer DB writes Live status reads went to zero Time from probe to pixel went from 1-3 seconds to <300ms (p90) It feels a bit like cheating. Making the product insanely more cool and useful, while also cutting costs, and not only cutting immediate costs. This thing scales like crazy. Basically the only real thing needed is a good amount of memory. Memory is not cheap nowadays, but it's definitely cheaper than continuous real-time DB reads and writes. Some tradeoffs worth mentioning. I kept the DB listeners as fallback if socket drops. The UI degrades instead of breaking. Websockets are real ops work. Is has become a bit harder to maintain an

2026-06-06 原文 →