今日已更新 177 条资讯 | 累计 26160 条内容
关于我们

今日精选

HOT

最新资讯

共 26160 篇
第 475/1308 页
AI 资讯 Dev.to

ASP.NET Core: Building High-Performance Web Applications and APIs

ASP.NET Core: Building High-Performance Web Applications and APIs A practical guide to ASP.NET Core — the cross-platform framework for building REST APIs, MVC applications, and backend services on .NET, covering architecture, minimal APIs, middleware, performance, and modern patterns. Table of Contents Introduction Architecture Overview Minimal APIs MVC and Controllers Middleware Pipeline Dependency Injection Configuration and Options Authentication and Authorization Performance Features Testing and Observability Quick Reference Table Conclusion Introduction ASP.NET Core is a free, open-source, cross-platform framework for building web apps, APIs, and backend services. It's a ground-up rewrite of the original ASP.NET, designed around three priorities: Performance — it's consistently one of the fastest mainstream web frameworks in independent benchmarks (e.g., TechEmpower). Modularity — you opt into only the middleware and services your app actually needs, instead of a fixed, heavyweight pipeline. Cross-platform — runs identically on Windows, Linux, and macOS, and deploys to containers, serverless, or bare metal. This guide covers the core building blocks you'll use in almost any ASP.NET Core project, from a five-line minimal API to a full MVC application with authentication and background services. 1. Architecture Overview Every ASP.NET Core app starts from a unified entry point — Program.cs — using the minimal hosting model introduced in .NET 6. var builder = WebApplication . CreateBuilder ( args ); // Register services (dependency injection container) builder . Services . AddControllers (); builder . Services . AddEndpointsApiExplorer (); builder . Services . AddSwaggerGen (); var app = builder . Build (); // Configure the HTTP request pipeline (middleware) if ( app . Environment . IsDevelopment ()) { app . UseSwagger (); app . UseSwaggerUI (); } app . UseHttpsRedirection (); app . UseAuthorization (); app . MapControllers (); app . Run (); Two phases matter here:

Rhuturaj Takle 2026-07-06 20:32 9 原文
AI 资讯 Dev.to

Top 5 AI UI Design Tools in 2026: I Tested Them All With the Same Prompt

Looking for the best AI UI design tool in 2026? I tested Flowstep, Google Stitch, Figma Make, Lovable, and Base44 with the exact same SaaS project management prompt to compare UI quality, design consistency, code generation, developer workflow, Figma integration, and overall usability. If you've searched for an AI UI design tool recently, you've probably noticed that every product claims it can turn a simple prompt into a polished interface in seconds. Landing pages are full of beautiful dashboards, glowing testimonials, and promises that you'll never have to start from a blank canvas again. The problem is that those demos rarely tell you what happens when you ask the AI design tool to generate something that looks like an actual product instead of a single screenshot. I wanted to know how these AI UI generator tools would perform on a realistic workflow. Could they keep a design system consistent across multiple screens? Would they generate layouts that developers could build on? Could they produce code that was worth keeping, or would I end up rebuilding everything from scratch anyway? Instead of trying different prompts for different tools, I decided to make things as fair as possible. I wrote one detailed prompt for a SaaS project management application and used it everywhere. The five AI design tools I tested were: Flowstep Google Stitch Figma Make Lovable Base44 They all approach AI-assisted UI generation differently, and after spending time with each one, it became clear that they're not really competing to solve the same problem. If you're trying to figure out which AI UI design tool is worth adding to your workflow in 2026, here's what I learned after putting all five through the exact same test. Why AI UI Design Tools Are Becoming Part of Every Developer's Workflow A year or two ago, most AI UI design tools were good at generating a nice-looking landing page and not much else. Today, the landscape looks very different. Some tools can generate an entire mul

Hadil Ben Abdallah 2026-07-06 20:29 7 原文
工具 Product Hunt

PlugThis

Like Lovable, but for Chrome extensions Discussion | Link

fmerian 2026-07-06 20:06 10 原文
AI 资讯 HackerNews

Ask HN: Are there good security benchmarks for LLMs?

I'm looking for this myself but figured it's good to have an actual discussion about this. I'm pretty new to the benchmarking side of LLMs. For example, I looked at eyeballvull [1]. It seems promising but I don't see wide support for example. I respect the author for still committing. A benchmark where an agent scans a repo in full is what I'm looking for. But then I also wondered: maybe there are others out there that I haven't been aware of yet. And, at the risk of potentially being flooded, f

melvinroest 2026-07-06 19:53 3 原文
开发者 Reddit r/programming

Execution Truth vs Execution Authority

Ran into this while working on a coordination primitive for a payments system: locks and consensus (Redis, Raft, etcd) all answer "who can act right now" none answer "did the action actually complete" once a crash happens. That's a harder, separate problem most systems just inherit Temporal's answer to (determinism + replay). Blog submitted by /u/munch_muffin_solas [link] [留言]

/u/munch_muffin_solas 2026-07-06 19:32 6 原文