今日已更新 297 条资讯 | 累计 35186 条内容
关于我们

标签：#t

找到 16751 篇相关文章

AI 资讯

The Only Productivity Hack That Actually Worked for Me

The Only Productivity Hack That Actually Worked for Me I've tried every website blocker in existence. They all have the same flaw: one click and they're off. That settings toggle might as well not exist when the urge to procrastinate hits. I needed something I couldn't override. So I built the opposite. The Problem Every blocker follows the same pattern: it blocks, you unblock, you procrastinate. The issue isn't discipline — it's that your future self and your present self want different things. And that future self will happily undo anything you set up. What I needed was a system where both selves agreed on the rules upfront and then neither could break them. The Solution kblocker is a Linux kernel module that hooks into netfilter and drops TCP connections to whatever sites I configure. The key feature isn't the blocking — it's how you turn it off. When blocking is enabled, kblocker generates a 128-bit key. With PGP mode, it automatically encrypts that key to people I trust and then erases it from kernel memory. The raw key no longer exists anywhere on my system. To disable the blocker, one of those people has to decrypt it and send it back to me. I outsourced my willpower. When I want to focus, I run: sudo kblockerctl enable 120 Two hours of blocked distractions. If I feel the urge to procrastinate, I can't — I'd have to text a friend, explain why, wait for them to decrypt it, and paste the result. By then the urge is gone. The Result I've gone from losing entire afternoons to YouTube to actually finishing things. The blocker has caught me mid-reflex to type youtube.com more times than I can count. It's free if anyone wants it: github.com/Dan-J-D/kblocker If you keep breaking your own focus tools, this is for you.

2026-06-14 原文 →
AI 资讯

I Built Minesweeper in ~50 Lines — the Only Hard Part Is Flood-Fill

Minesweeper feels intricate — numbers, cascading reveals, flags. Build it and you find it's a grid, a neighbour count, and one recursive function . This is Day 6 of my GameFromZero series. Each cell holds four facts const cell = { mine : false , open : false , flag : false , n : 0 }; n = how many of the 8 neighbours are mines. That number is all the player gets to reason about. Count neighbours once After scattering mines randomly, precompute every non-mine cell's n : let n = 0 ; neighbours ( r , c , ( rr , cc ) => { if ( cells [ rr ][ cc ]. mine ) n ++ ; }); cell . n = n ; Flood-fill is the whole trick When you open a cell with zero neighbouring mines, there's nothing dangerous nearby — so auto-open all 8 neighbours, and if any of those are also zero, they cascade. That's why one click can clear half the board. It's recursion: function open ( r , c ) { const cell = cells [ r ][ c ]; if ( cell . open || cell . flag ) return ; // base case cell . open = true ; if ( cell . n === 0 ) neighbours ( r , c , ( rr , cc ) => open ( rr , cc )); // recurse } This is the same algorithm behind the paint-bucket tool and maze region-filling. Flags + win/lose Right-click toggles a flag (and blocks accidental opens). Click a mine → lose. Win when opened cells = total − mines: if ( cell . mine ) gameOver (); if ( opened === R * C - M ) win (); That's the entire game. Master the state-step-draw loop once and every classic — Snake, Pong, Tetris, 2048, Minesweeper — is an evening each. ▶️ Play it + read the step-by-step breakdown: https://dev48v.infy.uk/game/day6-minesweeper.html Day 6 of GameFromZero.

2026-06-14 原文 →
开发者

Why I Built Haggl: Making Price Comparison Across Europe Easier

For a long time I found myself checking different European stores to see where products were cheapest. It was slow and annoying. I had to open lots of tabs, change countries, check delivery costs and compare prices myself. I used other comparison websites, but I wanted something simpler. So I decided to build Haggl.eu. Haggl lets you compare prices across Europe from one search, helping you find better deals and save money. This is my first public project and I am learning a lot while building it. The site is still a work in progress, but I have plenty of ideas for the future. I want to add more stores, more countries, price history tracking and better delivery comparisons. My goal is to make it as easy as possible to find the best deal without spending ages clicking through different pages. I would love to hear any feedback or suggestions. Thank you everyone :) https://haggl.eu

2026-06-14 原文 →
开发者

I Built a 4-Sided Plot Area Calculator with 2D & 3D Visualization

I Built a 4-Sided Plot Area Calculator with 2D & 3D Visualization Most online plot calculators only work for simple rectangular plots. However, many real-world properties have four sides with different measurements, making area estimation much more difficult. That's why I built a 4-Sided Plot Area Calculator that allows users to enter the North, South, East, and West dimensions and instantly calculate the approximate plot area. 🔗 https://www.premiumconverters.com/plot-area-calculator Features 📐 Supports irregular 4-sided plots 🏠 Calculates area in Marla, Kanal, Acres, and more 🖼️ Interactive 2D top-down visualization 🏗️ Isometric 3D plot rendering 📏 Feet & inches input support 📱 Mobile-friendly experience Why I Built It In many countries, especially in South Asia, property dimensions are often recorded as side measurements rather than perfect geometric shapes. Existing tools rarely address this use case properly. I wanted to create a simple solution that homeowners, buyers, real estate professionals, and developers could use without needing complex surveying software. The Result The calculator transforms four side lengths into a practical estimate while providing visual feedback that helps users better understand their property's shape. Building tools that solve real-world problems is one of the most rewarding parts of software engineering. Have you ever built a niche tool that unexpectedly helped thousands of users?

2026-06-14 原文 →
AI 资讯

Your DR Test Passed. The Assumptions Didn't.

The test passed. The restore completed inside the window. The workload came online. The team signed off, closed the ticket, and filed the results. DR test: successful. And then, somewhere between the test environment and the next real incident, the recovery plan drifted out of alignment with the infrastructure it was written to protect. Not dramatically. Not all at once. Gradually — through a cloud migration, an IdP consolidation, a new SaaS dependency, a network redesign that didn't make it into the runbook. DR plan failure rarely happens where you tested. It happens at the assumptions the exercise never reached. The Test Has a Boundary. The Incident Doesn't. A DR exercise begins with a defined scope. A specific workload. A known starting state. A target environment that has been prepared in advance. The team is available, credentialed, and not managing anything else. The blast radius is controlled before the test starts. A real incident does none of that. Scope expands from the first alert. Authentication problems surface because the IdP that wasn't in exercise scope is now unreachable. Networking issues appear because the failover path assumes a routing table that was updated three months ago. A vendor the plan never named is unavailable, and the recovery sequence stalls waiting for a dependency that was never documented as a dependency. The plan was written for the conditions of the test. The incident arrives in conditions the plan never anticipated. That gap is where DR plan failure actually lives — not in the restore mechanism, but in everything the restore mechanism was assumed to be able to reach. Most DR Plans Depend on Things They Never Recover The recovery exercise validates a workload. What it rarely validates is the recovery infrastructure itself. Consider what a typical enterprise DR plan silently depends on: Assumed — Not Tested: Identity provider, backup management console, cloud account access, ticketing and incident management systems, third-party

2026-06-14 原文 →
AI 资讯

How the Web Actually Works: HTTP from the Ground Up

I've been going through Jim Kurose's networking lectures lately, and I kept finding myself pausing to re-read the same sections. Not because they were confusing - because things I'd been using for years were finally clicking into place. This post is me writing down what I learned, in the order it started making sense. Before HTTP, there's a webpage A webpage isn't one file. When you open a URL, your browser fetches a base HTML file - and that file references other objects. Images. Scripts. Stylesheets. Each one lives at its own URL. Each one has to be fetched separately. So loading a single "page" might mean firing off 20+ individual requests. This detail matters because the entire evolution of HTTP - from 1.0 to 3 - is basically the story of making those 20 fetches faster. HTTP runs on TCP. That has consequences. HTTP doesn't manage its own connections. It hands that job to TCP. When your browser wants something, it first opens a TCP connection to the server (port 80 for HTTP, 443 for HTTPS), and then asks for the object. Opening a TCP connection isn't free. It takes a round-trip - your machine says "hello," the server says "hello back," and then you can actually talk. That's one RTT(Round Trip Time) just to shake hands, before a single byte of your webpage arrives. So every HTTP request carries at least 2 RTTs of overhead: 1 to open the TCP connection, 1 for the actual request/response. Do that 20 times and you've spent 40 RTTs before the page renders. HTTP/1.0 vs HTTP/1.1: one change that mattered a lot HTTP/1.0 (non-persistent): open a TCP connection, fetch one object, close the connection. Repeat for every object. HTTP/1.1 (persistent): open a TCP connection, fetch as many objects as you need, then close. The server leaves the connection open after each response. That one change cuts subsequent fetches from 2 RTTs to 1 RTT each. For a page with 20 objects, that's real time saved - not microseconds, but hundreds of milliseconds that users actually feel. What an

2026-06-14 原文 →
AI 资讯

Translating 'I missed you' so it doesn't land like a form letter

I was trying to tell someone something real in her first language — not "I missed you" from a dropdown, but the version that sounds like a person said it. Google Translate gave me one answer. No indication whether it was what you'd text at midnight or what you'd write in a letter to someone's grandmother. That's the failure mode of literal translators: one output, no register, no sense of what you're actually choosing between. konid returns 3 options per query, ordered casual to formal, with the register explained and a cultural note on the difference between them. For Mandarin or Japanese, audio plays through your speakers via node-edge-tts — no API key, no browser tab — because reading a pinyin romanization and actually hearing the tone contour are two different things. The vowel length in Korean, the pitch drop in Japanese, the stress pattern in Arabic: you don't internalize those from text. You internalize them from hearing them repeated back while you're still in the context of trying to say something. The setup for Claude Code is one line: claude mcp add konid-ai -- npx -y konid-ai It runs as an MCP server, so it works in Cursor, VS Code Copilot, Windsurf, Zed, JetBrains, and Claude Cowork. Also installs as a ChatGPT app via Developer mode using the endpoint https://konid.fly.dev/mcp . Supports 13+ languages: Mandarin, Japanese, Korean, Spanish, French, German, Portuguese, Italian, Russian, Arabic, Hindi, and more. The name is Farsi — konid (کنید) means "do." MIT licensed. https://github.com/robertnowell/konid-language-learning

2026-06-14 原文 →
← 上一页 下一页 →