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Today I accidentally became the maintainer of software that was already almost three decades old: reviving a 1990s Java utility to keep the last PAD submitter alive in 2026. I was looking for a way to submit my AI app RiverScript to old desktop software directories and ended up digging through the long-forgotten world of PAD files. There was one problem. The only batch submission tool I could find was a Java application that first appeared in the late 1990s. The last release was in 2017. It was written by Roedy Green of Canadian Mind Products — a software developer who passed away in 2023. He spent decades writing and freely distributing Java utilities, and maintaining the widely-read Java Glossary . Roedy Green also wrote How To Write Unmaintainable Code — a famous satirical guide about writing code nobody can maintain. So, Roedy, today the code you wrote almost three decades ago was maintained. The tool still did exactly what it was supposed to do. Thank you. It just had absolutely no idea the modern web existed. It happily produced URLs like http://https://riverscript.com instead of https://riverscript.com , disabled SNI globally (which was probably a perfectly reasonable workaround at some point), and couldn't cope with the fact that almost every website now redirects HTTP to HTTPS. So I dug through the legacy Java code, fixed the compatibility issues, and got it working again. I used it to submit my app to several software directories, then published the revived version on GitHub so anyone who still needs it can use it too. Maybe nobody will ever need it again. Maybe someone will. Either way, I'm happy this old thing works again. So today, the code of the man who wrote "How To Write Unmaintainable Code" is still being maintained even after he was gone. P.S. The public repository for Mini PAD Submitter 26.3 Revived — 2026 Community Fix is available and open to everyone. submitted by /u/Odd-Flamingo-6211 [link] [留言]

submitted by /u/mttd [link] [留言]

TikTok is starting to test an opt-in tool that scans for AI likenesses and lets creators report them to the company, as spotted by social media consultant Matt Navarra. The tool is initially being tested with "some" US creators, TikTok US spokesperson Zachary Kizer tells The Verge. YouTube has been working on a similar tool […]

The potential deal highlights a growing trend of complex, multi-stage funding rounds that mask true entry prices.

"Missiles are being launched at the joint force every single day in [Operation] Epic Fury."

The US is home to some of the most polluted air on the planet as smoke from 120 out-of-control Canadian wildfires drifts across the border.

Pebble founder Eric Migicovsky says buyers of its new e-paper smartwatches should know what they're signing up for and trust Pebble to make things right if they run into issues, despite the short warranty. "I think the most important thing is trust," Migicovsky told me in an interview this week. "Do people trust the product […]

The NHTSA recently called for autonomous vehicle companies to improve how cars respond in emergency situations.

Installing Apache Kafka 4.2 on Ubuntu 24.04 (WSL2) Using KRaft Mode: A Complete Step-by-Step Guide Learn how to install Apache Kafka 4.2 in KRaft mode, understand its architecture, create topics, produce and consume messages, and troubleshoot common configuration issues—all without ZooKeeper. 🚀 Introduction Apache Kafka has become the de facto standard for building event-driven , real-time , and high-throughput applications. Whether you're processing millions of financial transactions, collecting application logs, streaming IoT sensor data, or connecting microservices, Kafka provides a scalable and reliable messaging platform. Until recently, setting up Kafka required running Apache ZooKeeper alongside Kafka brokers. While powerful, ZooKeeper added operational complexity and introduced another distributed system that administrators had to manage. Beginning with recent Kafka releases, KRaft (Kafka Raft Metadata mode) removes this dependency by allowing Kafka to manage its own metadata internally. This makes installation simpler, reduces operational overhead, and improves scalability. In this guide, we'll install Apache Kafka 4.2 on Ubuntu 24.04.4 LTS (WSL2) , configure a single-node KRaft cluster, and walk through the complete lifecycle: Installing Kafka Understanding the Kafka architecture Configuring KRaft mode Starting the broker Creating topics Producing and consuming messages Troubleshooting common issues Understanding the purpose of each configuration parameter Rather than simply listing commands, I'll explain why each step is necessary so that you understand how Kafka works under the hood. What is Apache Kafka? Apache Kafka is a distributed event streaming platform designed to move data reliably and efficiently between applications. Instead of applications communicating directly with each other, they communicate through Kafka. A producing application writes messages to Kafka. Kafka stores those messages reliably. One or more consuming applications read those m

"We're turning the clock back on rational healthcare."

After the browser transfers a file, the server may still scan, transcode, extract metadata, or generate previews. The interface needs status updates, but the most fashionable real-time transport is not automatically the most reliable choice for an event guest on a mobile browser. Start with the update contract Define states and transitions before choosing transport: accepted -> queued -> processing -> ready accepted -> rejected processing -> processing_error Every status response should include a monotonically increasing version or timestamp. The client can ignore events older than the state it already knows. Polling is a strong baseline HTTP polling works through proxies, resumes naturally after a page wake, and is easy to cache and rate-limit. Use adaptive intervals: one second just after acceptance, then back off to several seconds when processing takes longer. const delay = Math . min ( 8000 , 1000 * 2 ** slowChecks ); Add jitter when many guests finish at the same time. Stop when the state is terminal, the page is gone, or a server-provided retry time says to wait longer. SSE fits one-way progress Server-Sent Events are attractive when the server only pushes status. The browser reconnects with a last-event ID, and the wire format is simple. But mobile networks and some intermediaries silently kill idle connections. Send occasional heartbeats and treat reconnection as normal. The reconnect handler must fetch current state because events may have been missed beyond the server replay window. Do not keep one SSE stream per file. Subscribe by guest session or album and filter authorized upload IDs on the server. WebSockets add more responsibility WebSockets make sense when the client also sends frequent commands over the same channel or when a host moderation console needs many rapid updates. For a guest waiting on two files, they add connection authentication, heartbeat, reconnect, replay, and load-balancer complexity without much user benefit. Never rely on the so

The trust proxy setting is an important concept in backend development, especially when implementing rate-limiting in our APIs. But deciding its accurate value depends heavily on our deployment topology. When we deploy our application in production, the client may not talk directly to our backend. There may be 1 or more proxies in between who forward the request to the next proxy or the backend server. Those proxies can be Load balancers, API gateways, reverse proxy like nginx or any custom service. So effectively, our request has to do some 'hops' over these proxies to reach backend. When we implement rate limiting in app to prevent the DOS attack, we generally intend this rate limit on the basis of client IP address. And this works fine when client request reaches our backend directly. But when we have multi-hop architecture, the simple setup won't work as expected. Because the most recent IP will be of the proxy and not the client. So all the traffic coming from different users will be considered from the single client(our own proxy) and thus there will be false positives as the rate limiting will trigger much often. In this scenario, we must tell our backend to ignore these extra hops(i.e. to trust our proxies). This is done by specifying trust proxy. If there is 1 proxy between client-server we set trust proxy to 1; if there are 2, or more, we set it accordingly. This will ensure our express app skips(trusts) these IPs, and accurately figures out actual client IP. The originating IP address of client is identified from 'X-Forwarded-For' header by the express app. But setting trust proxy is not that straightforward. The numerical value for trust proxy will not work in every case. If there are different paths from which our request reaches backend, there is a chance that the number of proxies may be different in each path. For example - internal vs external traffic: External(public) traffic: (Client -> Web Application Firewall -> Load balancer -> Reverse Proxy ->