标签：#web

I have tried to use the custom html block via WordPress but it seems to be limited with complexity. I am trying to add many sections and subcategories that follow a tree structure onto my webpages. What should I know before modifying the page's code directly, I think I have a raw HTML plugin installed. submitted by /u/neonrider2018 [link] [留言]

A few years ago I would've said crashes are the worst bugs. Now I think it's the opposite. The worst bugs are the ones where everything technically works. The request succeeds. The button works. The API returns 200. Nothing shows up in logs. Meanwhile users are getting confused, clicking the same thing repeatedly, or abandoning a flow entirely. By the time someone notices, it's been happening for weeks. What's the most frustrating example of this you've run into? Edit:- I am not getting the point why everyone is downvoting this post ? It's a serious question guys submitted by /u/Icy-Roll-4044 [link] [留言]

As the title goes. I'm just too f*cking slow! I'm sitting with a client's project for 6+ months (without pay) and I've covered only about 50% so far. This project is mildly complex- a custom video distribution platform with background jobs. However, have I been faster, it would have gone live by now! I took a whole lot of time understanding the technical concept, the underlying system design. Right then, I got hold of the sinister thing called procrastination, in combination with fear of failure, as well as perfectionism! The actual implementation is going even slower. I'm the perfect candidate to be replaced by AI; at least in terms of speed. I fear how will I learn and work on other technologies later on! This is also destroying my overall confidence and career. I have seen the sentence 'ship fast, polish later.' But I just won't follow it even if I go broke financially. Man, I'm fed up of myself! Has anyone ever recovered from similar situation? submitted by /u/swb_rise [link] [留言]

The Care Quality Commission regulates 56,000+ healthcare and social care locations in England — care homes, GP surgeries, hospitals, dental practices, home care agencies. If you work in care sector tech, you've probably needed this data at some point. There's a CQC REST API, and I was planning to wrap it. Then I hit the auth wall. The API is now authenticated CQC migrated their API to api.service.cqc.org.uk and added bearer token authentication. You need to register at their developer portal, create an application, and include an Authorization: Bearer <token> header on every request. That's not a dealbreaker for enterprise use cases, but it creates friction for a data product — it means requiring users to register with CQC before they can run your actor. I checked the old API base ( api.cqc.org.uk/public/v1 ) as a fallback. HTTP 403. Fully blocked. The open-data file rescue CQC publishes a monthly open-data file called HSCA_Active_Locations.ods . It's a 23 MB OpenDocument Spreadsheet with every active regulated location in England — all 56,000 of them. Free, no auth, Open Government Licence. The URL is date-stamped and changes each month, but the transparency page always links to the current version. The approach: scrape the transparency page to find the current ODS URL, download the file, parse it, filter rows, push results. No API. No auth wall. The ODS parsing challenge ODS files ( .ods ) are ZIP archives containing XML. The standard tool for parsing them in Node.js is SheetJS ( xlsx package, v0.18.5 — the last Apache 2.0 release). The first surprise: the workbook has three sheets — README , HSCA_Active_Locations , and Dual_Registration_Locations . SheetJS defaults to the first sheet, which is the README with 34 rows. I added logic to find the sheet with the most rows. for ( const name of workbook . SheetNames ) { const probe = XLSX . utils . sheet_to_json ( sheet , { header : 1 }); if ( probe . length > bestCount ) { bestCount = probe . length ; bestSheet = shee

Most scraping projects start by finding a website to scrape. This one started from the opposite direction: I knew the data existed as official government downloads, and my job was to make it accessible via a clean API. The data source Ofsted (the UK school inspections body) publishes monthly management information as CSV files on GOV.UK. The file covers all 22,000+ state-funded schools in England with their latest inspection grades, local authority, postcode, phase, and size data. It's 16 MB, published under the Open Government Licence v3.0 — explicitly permitting commercial use. No scraping needed. No authentication. Just a CSV download and some parsing logic. The architecture The actor is deliberately simple: Fetch the GOV.UK stats page to find the current month's CSV URL (the URL hash changes with each release) Download the CSV (~16 MB from assets.publishing.service.gov.uk ) Parse it with csv-parse Apply the user's filters (name, local authority, region, postcode prefix) Push matching records to the Apify dataset No Crawlee. No browser. No proxy. Just fetch() and a CSV parser. const match = html . match ( /href=" ( https: \/\/ assets \. publishing \. service \. gov \. uk \/[^ " ] +latest_inspections_as_at [^ " ] + \. csv ) "/ ); That one regex does the URL discovery. The GOV.UK page lists files in reverse chronological order, so the first match is always the latest release. The interesting part: Ofsted changed their grading system mid-build I built this in May 2026. In November 2025, Ofsted scrapped their 20-year-old four-word judgement system (Outstanding / Good / Requires Improvement / Inadequate) and replaced it with a report card format — six separate grade areas, each on a five-point scale: Exceptional Strong Expected standard Needs attention Urgent improvement Plus a standalone Safeguarding verdict (Met / Not met). The April 2026 CSV reflects this change entirely. There's no "Overall effectiveness" column. Schools inspected before November 2025 have null gr

When a team hits a ceiling with their coding agent, the first instinct is to reach for a better model. The reasoning feels obvious: the model is the part that produces the code, the code is the part that is wrong, therefore a smarter model will produce more correct code. Wait for the next release. Switch providers. Bump the tier. This is sometimes right. It is much more often wrong, and the cost of being wrong about it is that you spend months waiting for a model upgrade to solve a problem the model was never the cause of. The harness is the cause of the problem more often than the model. Most teams discover this only after they have exhausted the model-upgrade reflex and finally turn to look at everything else. What a model upgrade actually buys you Newer, stronger models do tangibly improve some things. They handle longer contexts more reliably. They make fewer simple reasoning errors on complex tasks. They follow nuanced instructions more closely. On a fixed prompt, with a fixed task, a better model produces a better answer. What model upgrades do not change: The fact that the agent has no idea your team prefers functional components over class components, because the convention is not in any file the agent reads. The fact that your tests do not actually fail when the code is wrong, so the agent can ship broken code that passes CI. The fact that your codebase has three different ways of handling errors and the agent picks one at random on each PR. The fact that the rule the senior engineer keeps repeating in reviews is not encoded anywhere the next session can see. None of these are fixed by a smarter model. They are fixed by a better harness. A smarter model loaded into the same broken harness will produce slightly more sophisticated versions of the same problems. The diagnostic The diagnostic is one question: when the agent fails, does it fail because it lacked information, or because it lacked capability? A capability failure looks like: the task required reas

Maybe an odd question but Pornhubs start page are actually recommendations based on your viewed videos. I suppose most folks here use incognito mode so, no cookies, clean state on each launch. Yet, if you launch another incognito window for the site, you will realize it remembered your viewing behavior and the videos reflect it. But how do they do this? There is no account, no cookies, no local storage. And technically, they wouldn't be allowed to track you in the first place due to the GDPR. Yet, it's the case. Anyone know how they achieve this? submitted by /u/SourSovereign [link] [留言]

I made a portfolio for the University as an assignment, but there's some very sensitive information like my id number and my full name. I don't want any random person on the internet to stumble on it, I only want the professor to see it. So i want an exact link that is very hard so only people with this link can access my website. Is there some free website host for this exact thing? submitted by /u/W3-SD [link] [留言]

submitted by /u/fagnerbrack [link] [留言]

I want to make a feature where my users would be able to customize a 2D svg character. They would choose their sex, their skin color, their clothes color, and maybe even put on accessories later. The arms of these characters would also change position. Obviously, I don't want to create an svg image for every possible combination, e.g. brown-man-red-shirt-pose1.svg white-woman-blue-shirt-pose1.svg, etc. If I did so I would have at least a hundred files to change each time I update the design of the characters which I don't wish on my worst enemy. So I would like a way to dynamically generate these combinations on the fly each time I render a character to the user. I asked a chatbot about it and it told me to treat my svg files the same way I treat my html templates with Django and render them using the render_to_string() function which allows me to pass variables for my template to display. I believe this way of doing it makes sense. For the different colors applied to the character, I would only need to add the following syntax: {{ shirt_color }} as the value of a path's "fill" in my svg and pass the value of the color in render_to_string() . However, if I want to attach the arms to the characters during render to not have a file for every arm pose there is with the same exact base character in each one, it becomes a bit more complicated. I would need to integrate a whole svg file inside of the first one and would need to care about its positioning and everything. I would also need to clean up the file each time I render it inside another svg file because of everything that comes with (<?xml version="1.0" encoding="UTF-8" standalone="no"?>, <!-- Created with Inkscape ( http://www.inkscape.org/ ) --> and the svg tag itself). So what is the most commonly agreed upon way of doing this? submitted by /u/Affectionate-Ad-7865 [link] [留言]

Author's note: In the spirit of fairly critiquing AI and practicing a suggestion I end the article with, this article and the accompanying illustration were created entirely without AI assistance. Agentic coding AI is here, and it’s transforming the software industry. But with agentic coding out now for over a year, has it felt like the software industry has really transformed? From my from vantage point, although there are some really cool projects that have been built only because of new agentic coding tools, it generally feels like we’re awash in a sea of software slop. Tim Kadlec wrote a great article, “Losing Focus” , that really resonated with me, especially this quote: “I don’t think the quality of software has increased all that much in in the past 12 months. I think maybe the amount of software has, but it’s very, very hard to find software that’s reliable.” - Max Scoening, Head of Product at Notion I’ve been hearing loads of stories and murmurs about AI from the people I know in tech, and I think there’s a lot being lost in the binary divide that a lot of people seem to fall into - either AI is bad and can do nothing right, or AI is the new future of engineering, and every company should have all their code written by AI today . I want to posit that right now we’re in the messy middle. An era of hype and grifters that want to sell you an AI fantasy that hasn’t been reached, which obscures the real present - powerful AI tools that can speed up professional developers, but can lure non-developers into shipping products that aren’t nearly ready for prime-time. My Background But first, if you don’t know me, let me explain why you should listen to my perspective. I’ve been working professionally in software (specifically web development, focused on the frontend), for over ten years. In that time I’ve worked at a non-profit, a for-profit, led a small startup, freelanced, and have led a number of open-source volunteer teams at Chi Hack Night , including right now

The same agent, same prompts, did markedly different work on two codebases I work in. One has a test suite that runs in eight seconds. The other takes twelve minutes. The eight-second project gets a careful, iterative collaborator. The twelve-minute project gets a confident guesser. I noticed it first as a vibe. The agent in the slow codebase would write five files at once, then announce the task complete without having run anything end to end. The agent in the fast codebase would write one function, run the tests, react to the failure, fix it, run them again. Same model. Same configuration. The only difference was how expensive it was to learn whether the previous step was right. That is the whole post in one sentence. An agent's effective intelligence is bounded by how fast it can verify its hypotheses. Cut the verification cost and you raise the agent's apparent IQ. Raise it and you lower the agent's apparent IQ. The model in the middle is unchanged. Why this binds harder for agents than for humans A human engineer can hold a hypothesis in their head. "I think this works. I will check it later." The cost of holding the hypothesis is roughly free; the human has institutional memory, intuition, a sense of what the code does that does not require running the code to confirm. They can defer verification without losing fidelity. An agent cannot. It has no intuition about your codebase. The only ground truth it has access to is what the tests say, what the type checker says, what the build says. When those signals are cheap, the agent uses them constantly. When they are expensive, the agent stops using them and starts speculating. Speculation by an agent looks plausible. It produces code that compiles, follows the patterns it has seen in your repository, names things sensibly. The problem is that plausible is not the same as correct. The agent that speculates is shipping a guess; the agent that iterates is shipping a tested answer. From the diff alone, they can be hard

Everyone is adding AI to their product right now. Most of them are doing it wrong. Not because they chose the wrong model. Not because they used the wrong library. But because they treated AI integration like a regular feature and skipped all the engineering discipline that production systems require. I have integrated LLMs into multiple production applications. This is what I wish I had known before I started. The Mental Model Shift You Need First A traditional API call is deterministic. You send a request, you get a predictable response. You can write tests against it. You can cache it. You can reason about it. An LLM call is not deterministic. The same input can produce different outputs on different runs. The model can refuse, hallucinate, or return output in a format you did not expect. Your system needs to be designed around this reality, not in spite of it. This means defensive parsing, fallback logic, output validation, and graceful degradation are not optional extras. They are the core of the feature. Choosing the Right Model for the Right Job The biggest LLMs are not always the right choice. I learned this building EditDeck Pro, an AI creative platform for music. Some tasks needed a large frontier model for nuanced creative output. Others needed a fast, cheap model that could run many times per session without accumulating significant latency or cost. The pattern that works: Use a lighter model for classification, extraction, and short structured outputs. Use a larger model for generation tasks where quality matters more than speed. Route dynamically between them based on the task type. This can reduce your inference costs by 60 to 80 percent on workloads that mix simple and complex tasks. Prompt Engineering Is Software Engineering Prompts are code. They should be versioned, tested, and reviewed like code. I store prompts in a dedicated module with version numbers. When I change a prompt I run it against a fixed evaluation set of inputs and compare the out

HEY, so im trying to connect my chatbot (Custom Coded) to instagram API using webhooks but im unable to test it my pm2 logs shows (second image) and in my first image, i feel like the AI is just completly lying because i have been trying this for 2 days and he keeps on adding stuff and stuff now its just saying you cant test in development at ALL my facebook and instagram is connected facebook account is also connected to developers facebook and i believe so everything is enabled from my side My thought process is that im using wrong APP_SECRET and ACCESS_TOKEN combo because there are like 4 places that can be used to generate access token and ID and app secret and its so badly designed that i cant figure out what is what. very frustrated honestly. submitted by /u/Jumpy_Paramedic2552 [link] [留言]

I want to create a website in a couple of days. It's main purpose is to offer a free digital download. I want to capture email in the process, to provide follow-up guidance to using the product. There's no e-commerce involved and few pages (4-5). Analytics and domain registration would be a bonus. I want it to look nice - I'd like to have flexible visual design options or be able to adapt a template. I'm comfortable with the likes of WordPress, Wix, Squarespace, Shopify, Canva but not so much using code. In this situation, what would people recommend? 🙏 submitted by /u/jahwinnie [link] [留言]

I'm not sure if I'm in the right place to ask this, but I need to create a web application, and am looking forwhat stack might be best suited.. So far, SurveyJS seems to tick all the boxes, but I have zero experience with the stack. Another one is Flask/Waitress and JS. Ultimately, this will all have to run off a docker host.. I need it save form data, ideally in something like MariaDB, so the user can pick a form the previously filled out and edit it. Multiple users will be using it, authentication is being handled elsewhere, but everyone should be able to see/edit everyone elses' data.. This is a "nice to have", but is there a functionality to export the form data to XML? The app we're looking at building needs to be able to as a question like "How many cars have you driven", and then from that answer create a section or a sub-form for each car that would ask other questions about the cars. I don't mind throwing a bit of money at this, looking at all-in-one options like FluentForm if that ticks all the boxes Thanks so much! submitted by /u/the_zipadillo_people [link] [留言]

OpenSparrow v2.6 is out. This one's a big step forward — RAG (Retrieval-Augmented Generation) integration, bulk grid operations, and a whole new UX layer. RAG & AI integration You can now upload documents and let users ask questions against them. The system retrieves relevant sections and generates answers using an LLM (supports Ollama locally or any OpenAI-compatible API). What's new: RAG Statistics tab in admin — tracks query tokens, response times, document matches, and recent queries Multilingual auto-response — user questions are answered in their own UI language, no schema changes needed 20-language support — "Ask AI" panel fully translated, plus language dropdown in the test interface Good for things like: knowledge base Q&A, customer support automation, or letting internal teams ask questions about their own data. Grid & bulk operations Mass Edit module — select rows via checkboxes, bulk edit fields, change owners, duplicate, or delete with one click Keyboard shortcuts — arrow keys to navigate, Tab, Ctrl+C to copy, Ctrl+F to search, Ctrl-hold for help modal — works across all 20 languages Quick Data Cleanup toolbar — find & replace with live preview, case sensitivity, accent-ignore. Editor-gated with audit trail. Admin improvements Renamed "RAG Knowledge Base" to "Centrum AI" (heading is translatable) Migration Manager — tracks pending cleanup tasks after version upgrades, with automatic backups and audit trail FK columns render as dropdowns in forms by default Security & Quality All bulk operations (mass edit, cleanup, delete) are editor-role gated CSRF protection on every operation Full audit trail — every change is logged 20 languages fully supported across all new modules Fixed regressions in RAG API and CSV import Following this series? OpenSparrow v2.3 – visual admin panel, zero dependencies, now with ERD and M2M support OpenSparrow – open-source admin panel builder, zero dependencies, v2.1 just dropped Websites opensparrow.org github.com/wrobeltomasz/

Analytics is often treated as a reporting feature: a dashboard added after the product already exists. That is usually too late. For software operators, analytics is closer to infrastructure. It is the layer that makes the state of the product visible. Without it, a team cannot evaluate the situation, understand whether the product creates value, or know whether a workflow is improving. That is the reason WebmasterID is built around privacy-first analytics. The goal is not to collect more data than necessary. The goal is to preserve enough signal to make practical decisions without turning measurement into surveillance. Analytics answers operational questions Good analytics starts with plain questions. What happened? Which workflow changed? Which part of the product is used? Where do people leave? Which system events matter? What evidence supports the conclusion? Those questions sound simple, but they are the foundation of product judgment. If the data model cannot answer them, the team is forced to reason from anecdotes, support messages, and internal opinion. Those inputs still matter, but they are not enough on their own. Analytics gives operators a way to compare the current state with the previous state. It makes change visible. It also makes uncertainty visible when the evidence is incomplete. Product value needs evidence A product can look polished and still fail to create value. It can also look unfinished while solving a real operational problem. The difference is usually visible in behavior. Do users return? Do they complete the workflow? Do they avoid a manual step? Does the product reduce confusion? Does it make a business process easier to operate? Privacy-first analytics should help answer those questions without building a profile of every person. In many cases, first-party events, coarse context, workflow state, and careful retention rules are enough. The system does not need to know everything about a user to show whether a product path is working.

I use "what is my IP" sites maybe once a month. Every time I end up on something covered in ads, calling three different tracking APIs, and showing me results I don't fully understand. So I spent a weekend building whatsmy.fyi. The thing I didn't expect: you don't need an IP geolocation API at all if you're on Cloudflare Workers. Every request comes with a cf object that already has your city, country, ISP, TLS version, HTTP protocol, and RTT. Free. Zero latency. The part I enjoyed most was the WebRTC leak test. It checks whether your browser is exposing your real IP through RTCPeerConnection even when you're on a VPN. I ran it on my own setup. It was leaking. Zero logs. Zero storage. Just your data, shown to you. https://whatsmy.fyi

So im working on a saas and am wondering how most of you all handle ToS, liability, and where you get them from? Ill be storing customer data like addresses, emails, phone numbers in a db. Stripe for payment processing. I want to make sure i have a solid tos. To cover refunds, chargebacks, data stored in a db, etc… Should i just find a lawyer or are there resources online i can use? submitted by /u/spacedublin [link] [留言]