Dec 10, 2025
api
Good API design is crucial for developer experience and system success. Here are best practices for designing RESTful APIs.
1. Use RESTful Conventions Resource-Based URLs # Good: Resource-based GET /api/users GET /api/users/123 POST /api/users PUT /api/users/123 DELETE /api/users/123 # Bad: Action-based GET /api/getUsers POST /api/createUser POST /api/deleteUser HTTP Methods GET: Retrieve resources POST: Create resources PUT: Update entire resource PATCH: Partial update DELETE: Remove resource 2. Consistent Naming Use Plural Nouns # Good GET /api/users GET /api/orders GET /api/products # Bad GET /api/user GET /api/order GET /api/product Use kebab-case or camelCase # Good: Consistent GET /api/user-profiles GET /api/orderItems # Bad: Mixed GET /api/user_profiles GET /api/order-items 3. Version Your API URL Versioning GET /api/v1/users GET /api/v2/users Header Versioning GET /api/users Accept: application/vnd.api+json;version=2 4. Use Proper HTTP Status Codes Success Codes 200 OK # Successful GET, PUT, PATCH 201 Created # Successful POST 204 No Content # Successful DELETE Client Error Codes 400 Bad Request # Invalid request 401 Unauthorized # Authentication required 403 Forbidden # Not authorized 404 Not Found # Resource doesn't exist 409 Conflict # Resource conflict 422 Unprocessable # Validation errors Server Error Codes 500 Internal Server Error 502 Bad Gateway 503 Service Unavailable 5. Consistent Response Format Standard Response Structure { "data": { "id": "123", "type": "user", "attributes": { "name": "John Doe", "email": "[email protected]" } }, "meta": { "timestamp": "2025-12-10T10:00:00Z" } } Error Response Format { "error": { "code": "VALIDATION_ERROR", "message": "Invalid input", "details": [ { "field": "email", "message": "Invalid email format" } ] } } 6. Pagination Cursor-Based Pagination GET /api/users?cursor=eyJpZCI6IjEyMyJ9&limit=20 Response: { "data": [...], "pagination": { "cursor": "eyJpZCI6IjE0MyJ9", "has_more": true } } Offset-Based Pagination GET /api/users?page=1&limit=20 Response: { "data": [...], "pagination": { "page": 1, "limit": 20, "total": 100, "total_pages": 5 } } 7. Filtering and Sorting Filtering GET /api/users?status=active&role=admin GET /api/orders?created_after=2024-01-01&created_before=2024-12-31 Sorting GET /api/users?sort=name,email&order=asc,desc GET /api/users?sort=-created_at # Descending 8. Field Selection Sparse Fieldsets GET /api/users?fields=id,name,email GET /api/users/123?fields=id,name Include Related Resources GET /api/users/123?include=orders,profile 9. Rate Limiting Headers X-RateLimit-Limit: 1000 X-RateLimit-Remaining: 999 X-RateLimit-Reset: 1609459200 Response HTTP/1.1 429 Too Many Requests Retry-After: 60 10. Authentication and Authorization Use Standard Methods # Bearer token Authorization: Bearer <token> # API key X-API-Key: <key> Return Clear Errors { "error": { "code": "UNAUTHORIZED", "message": "Invalid or expired token" } } 11. Documentation OpenAPI/Swagger openapi: 3.0.0 info: title: User API version: 1.0.0 paths: /users: get: summary: List users responses: '200': description: Success Interactive Documentation Swagger UI: Visual API documentation Postman: API testing and docs Redoc: Beautiful API docs 12. Error Handling Consistent Error Format { "error": { "code": "RESOURCE_NOT_FOUND", "message": "User with ID 123 not found", "request_id": "req_abc123" } } Validation Errors { "error": { "code": "VALIDATION_ERROR", "message": "Validation failed", "errors": [ { "field": "email", "message": "Invalid email format", "code": "INVALID_FORMAT" } ] } } 13. Caching Cache Headers Cache-Control: public, max-age=3600 ETag: "33a64df551425fcc55e4d42a148795d9f25f89d4" Last-Modified: Wed, 21 Oct 2015 07:28:00 GMT Conditional Requests GET /api/users/123 If-None-Match: "33a64df551425fcc55e4d42a148795d9f25f89d4" # 304 Not Modified if unchanged 14. Security Best Practices Use HTTPS Always use HTTPS in production.
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ReadDec 10, 2025
testing
This write-up condenses the published DEV tutorial “Browser-based performance testing with K6” into an actionable walkthrough for frontend teams.
Why k6 browser Simulates real browser interactions (Chromium) vs. protocol-only tests. Captures Web Vitals (LCP/INP/CLS) and UX signals (spinners, interactivity). Reuses familiar k6 scripting with async/await + locators. Setup Install k6 (latest) and ensure Node/npm are available. Project skeleton: k6-tests/ libs/ # flows (login, add to cart, checkout) pages/ # Page Object Model classes tests/ # test entry scripts utils/ # shared options (browser config, VUs, iterations) Configure browser scenario (utils/k6-options.js): export const browserOptions = { scenarios: { ui: { executor: "shared-iterations", vus: 1, iterations: 15, options: { browser: { type: "chromium" } }, }, }, }; Example flow (simplified) import { browser } from "k6/browser"; import { check } from "k6"; export const options = browserOptions; export default async function () { const page = await browser.newPage(); await page.goto("https://www.saucedemo.com/"); await page.locator("#user-name").type("standard_user"); await page.locator("#password").type("secret_sauce"); await page.locator("#login-button").click(); check(page, { "login ok": () => page.locator(".title").textContent() === "Products" }); await page.close(); } Running & reporting CLI run: k6 run ./tests/buyItemsUserA.js Live dashboard: K6_WEB_DASHBOARD=true K6_WEB_DASHBOARD_OPEN=true k6 run ... Export HTML report: K6_WEB_DASHBOARD=true K6_WEB_DASHBOARD_EXPORT=results/report.html Metrics to watch (aligns to Core Web Vitals) browser_web_vital_lcp — largest content paint; target < 2.5s p75. browser_web_vital_inp — interaction to next paint; target < 200ms p75. browser_web_vital_cls — layout shift; target < 0.1. Add custom checks for “spinner disappears”, “cart count”, “success message”. Tips Keep tests short and focused; one scenario per file. Reuse Page Objects for maintainability. Run with realistic VUs/iterations that mirror expected traffic. Use screenshots on failure for debuggability (page.screenshot()). Takeaway: k6 browser mode gives frontend teams reproducible, scriptable UX performance checks—ideal for catching regressions before they reach real users.
ReadDec 10, 2025
frontend
This post distills the key ideas from the published DEV article “Frontend Performance Optimization: A Comprehensive Guide 🚀” into a concise, production-focused playbook.
What matters Fast first paint and interaction: prioritize above-the-fold content, cut JS weight, avoid layout shifts. Ship less: smaller bundles, fewer blocking requests, cache aggressively. Ship smarter: load what’s needed when it’s needed (on demand and in priority order). Core techniques 1) Selective rendering Render only what is visible (e.g., IntersectionObserver + skeletons). Defer heavy components until scrolled into view. 2) Code splitting & dynamic imports Split by route/feature; lazy-load non-critical views. Example (React): const Page = lazy(() => import("./Page")); <Suspense fallback={<div>Loading…</div>}> <Page /> </Suspense>; 3) Prefetching & caching Prefetch likely-next routes/assets (<link rel="prefetch"> or router prefetch). Pre-warm API data with React Query/Next.js loader functions. 4) Priority-based loading Preload critical CSS/hero imagery: <link rel="preload" as="style" href="styles.css">. Use defer/async for non-critical scripts. 5) Compression & transfer Enable Brotli/Gzip at the edge; pre-compress static assets in CI/CD. Serve modern formats (AVIF/WebP) and keep caching headers long-lived. 6) Loading sequence hygiene Order: HTML → critical CSS → critical JS → images/fonts → analytics. Avoid long main-thread tasks; prefer requestIdleCallback for non-urgent work. 7) Tree shaking & dead-code elimination Use ESM named imports; avoid import *. Keep build in production mode with minification + module side-effects flags. Measurement & guardrails Track Core Web Vitals (LCP, INP, CLS) plus TTFB and bundle size per release. Run Lighthouse/WebPageTest in CI; fail builds on regressions above agreed budgets. Monitor real-user metrics (RUM) to validate improvements after deploys. Quick starter checklist Lazy-load routes and heavy widgets. Preload hero font/hero image; inline critical CSS if needed. Turn on Brotli at CDN; cache static assets with versioned filenames. Set performance budgets (JS < 200KB gz, LCP < 2.5s p75, INP < 200ms). Automate audits in CI and watch RUM dashboards after each release. Bottom line: Combine “ship less” (smaller, shaken, compressed bundles) with “ship smarter” (prioritized, on-demand loading) and enforce budgets with automated checks to keep your app fast over time.
ReadDec 10, 2025
react
This article summarizes the DEV post “How to Use React Query for Efficient Data Fetching” and focuses on a minimal, production-ready setup.
Why React Query (TanStack Query) Handles fetching, caching, retries, background refresh, and deduping. Removes useEffect + manual loading/error state boilerplate. Scales to pagination, infinite scroll, and SSR hydration. 3-step setup Install: npm install @tanstack/react-query Create a client and wrap your app: import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; const queryClient = new QueryClient(); const App = () => ( <QueryClientProvider client={queryClient}> <MyComponent /> </QueryClientProvider> ); Fetch with useQuery: import { useQuery } from "@tanstack/react-query"; function UsersList() { const { data, isLoading, error } = useQuery({ queryKey: ["users"], queryFn: () => fetch("/api/users").then((r) => r.json()), }); if (isLoading) return <p>Loading…</p>; if (error) return <p>Something went wrong</p>; return <ul>{data.map((u) => <li key={u.id}>{u.name}</li>)}</ul>; } Features you get “for free” Auto refetch on window focus/network reconnect. Stale-while-revalidate caching with configurable TTLs. Retries with exponential backoff for transient failures. Query invalidation to refresh related data after mutations. Devtools for live inspection of query states. Power tips Prefetch likely-next routes to hide latency (e.g., on hover). Use useInfiniteQuery for endless scroll; surface hasNextPage/fetchNextPage. Pass auth tokens via queryFnContext; centralize fetcher. For SSR/Next.js, hydrate with dehydrate/Hydrate to avoid waterfalls. Performance guardrails Set per-query stale times and retry counts to balance freshness vs. load. Log slow queries and cache hit rate; watch INP/LCP when triggering refetches. Keep query keys stable and descriptive (e.g., ["post", postId]). Bottom line: React Query removes state-management overhead for remote data and delivers faster, more resilient UIs with minimal code.
ReadDec 10, 2025
rust
Coming from JavaScript to Rust? Here’s a practical guide to help you make the transition.
Why Rust? Rust offers:
Memory safety without garbage collection Performance comparable to C/C++ Modern tooling and package management WebAssembly support for web development Growing ecosystem with active community Key Differences 1. Ownership System Rust’s ownership system is unique:
// Rust: Ownership let s1 = String::from("hello"); let s2 = s1; // s1 is moved to s2 // println!("{}", s1); // Error: s1 is no longer valid // JavaScript: Reference let s1 = "hello"; let s2 = s1; // s1 is still valid console.log(s1); // Works fine 2. Mutability Rust requires explicit mutability:
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ReadDec 10, 2025
typescript
TypeScript has become the de facto standard for large-scale JavaScript applications. Here are the best practices to write better type-safe code in 2025.
1. Use Strict Mode Always enable strict mode in tsconfig.json:
{ "compilerOptions": { "strict": true, "noImplicitAny": true, "strictNullChecks": true, "strictFunctionTypes": true, "strictBindCallApply": true, "strictPropertyInitialization": true, "noImplicitThis": true, "alwaysStrict": true } } 2. Prefer Interfaces for Object Shapes Use interfaces for object shapes, types for unions/intersections:
// Good: Interface for object shape interface User { id: string; name: string; email: string; } // Good: Type for union type Status = 'pending' | 'approved' | 'rejected'; // Good: Type for intersection type AdminUser = User & { role: 'admin' }; 3. Use Discriminated Unions Make type narrowing easier with discriminated unions:
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ReadDec 10, 2025
productivity
Here are 9 developer productivity tools that can dramatically improve your workflow and save you hours every week.
1. Warp Terminal What it is: A modern, Rust-based terminal with AI assistance.
Why it’s great:
AI command suggestions Split panes and tabs Command palette Better autocomplete Integrated workflows Use case: Replace your default terminal for a better development experience.
2. Cursor AI Editor What it is: VS Code fork with built-in AI coding assistant.
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ReadDec 10, 2025
web-design
Web design is constantly evolving. Here are the modern design styles every frontend developer should know in 2025.
1. Glassmorphism Glassmorphism creates a frosted glass effect with:
Semi-transparent backgrounds Backdrop blur filters Subtle borders Layered depth Implementation .glass-card { background: rgba(255, 255, 255, 0.1); backdrop-filter: blur(10px); border: 1px solid rgba(255, 255, 255, 0.2); box-shadow: 0 8px 32px rgba(0, 0, 0, 0.1); border-radius: 16px; } Use Cases Cards and modals Navigation bars Overlays Dashboard elements 2. Neumorphism Neumorphism (soft UI) creates a soft, extruded look:
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ReadDec 10, 2025
ai
What LLMs can’t learn from text — and why human-like understanding may require bodies, not bigger models.
The Fundamental Limitation Large Language Models (LLMs) have achieved remarkable success by learning from text. But there’s a fundamental gap: they lack sensorimotor experience.
What is the Sensorimotor Gap? The sensorimotor gap refers to the difference between:
Textual knowledge: What can be learned from reading Embodied knowledge: What requires physical interaction Examples Text can teach:
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ReadDec 10, 2025
ai
Three weeks ago, I had 191,000 tokens in my upcoming tactical survival roguelite game’s codebase. Today, I have 104,000 tokens: a 45% reduction.
Here’s what I learned about AI-generated code and why removing it made my game better.
The Problem with AI-Generated Code What is “AI Slop”? AI slop refers to code that:
Works but is unnecessarily verbose Lacks clear intent and purpose Contains redundant patterns Has inconsistent style Includes unnecessary abstractions Lacks proper error handling Has poor performance characteristics Why Does It Happen? AI tools like ChatGPT and GitHub Copilot:
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