React Query vs useEffect for API Calls in React

What really happens after a user clicks a button? . . Behind every modern web app, there’s a precise lifecycle. This architecture combines: - Next.js – React framework for fast UI rendering - FastAPI – High-performance async Python backend - NGINX – Reverse proxy and traffic manager - PostgreSQL Global Development Group – Reliable, production-grade database Now let’s break down the flow 👇 1- User clicks a button → Interaction triggers frontend logic 2- Next.js sends HTTPS request → Secure API communication begins 3- NGINX receives incoming traffic → Reverse proxy routes request properly 4- FastAPI processes business logic → Validation, authentication, core operations 5- Database query executed → PostgreSQL retrieves structured data 6- JSON response returned → Structured data travels back securely 7- Next.js renders new state → React updates virtual DOM 8- UI updated instantly → User sees fresh dynamic content That’s the invisible engine behind modern apps. Clean separation. Async performance. Scalable architecture. #Nextjs #API #FASTAPI #POSTGRESSQL #Web3

Managing server data in React can be more challenging than it appears. Many applications still depend on useEffect for API calls, which involves manually handling loading states, errors, cleanup, and refetching in every component. While this approach may work for smaller cases, it can become fragile and difficult to scale. React Query offers a clear distinction between client state and server state. It provides features such as built-in caching, request deduplication, background refetching, and predictable data synchronization. This allows teams to concentrate on UI and business logic rather than infrastructure code. This post will cover: • Why useEffect is not the best choice for server data • The problems that React Query addresses • When it is appropriate to implement React Query (and when it may not be) Understanding server state is a crucial skill for developing reliable, modern React applications. #ReactJS #ReactQuery #TanstackQuery #FrontendArchitecture #WebDevelopment #JavaScript

RS-X now works with React 🎉 I’m happy to share that RS-X can now be used with React. With RS-X, you can think in a more declarative way about your data and operations: - You define your data model - You define your operations via expressions - You bind the expressions to your data model - You can now just manipulate the data, and the expressions will update automatically You can see it directly in action on StackBlitz: https://lnkd.in/egRP2y7q For more details, check out the full article here: https://lnkd.in/eaf8auJb #React #Angular #TypeScript #JavaScript #FrontendDevelopment #WebDevelopment #StateManagement #ReactiveProgramming #OpenSource

𝗔𝗿𝗲 𝗬𝗼𝘂 𝗠𝗮𝗸𝗶𝗻𝗴 𝗔𝗣𝗜 𝗖𝗮𝗹𝗹𝘀 𝗪𝗿𝗼𝗻𝗴? React Router Loaders: Stop the Request Waterfall The hidden performance killer in most React apps? Sequential data fetching. 𝗧𝗵𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: 𝗥𝗲𝗾𝘂𝗲𝘀𝘁 𝗪𝗮𝘁𝗲𝗿𝗳𝗮𝗹𝗹𝘀 Traditional approach with useEffect: - Your Dashboard page renders first - Then it starts fetching dashboard data (300ms) - Once that loads, the UserProfile component renders - Now the profile starts fetching its data (300ms) - Total wait time: 600ms😱 Each nested component waits for its parent to finish before it can even start loading. 𝗧𝗵𝗲 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻: 𝗣𝗮𝗿𝗮𝗹𝗹𝗲𝗹 𝗟𝗼𝗮𝗱𝗶𝗻𝗴 React Router loaders flip this around: - You navigate to /dashboard/profile - BOTH the dashboard AND profile data start fetching immediately - They load in parallel (300ms for both) - Page renders with all data ready - Total wait time: 300ms⚡ You just saved 50% of your load time! 𝗧𝗵𝗲 𝗥𝗲𝗮𝗹 𝗜𝗺𝗽𝗮𝗰𝘁: The deeper your route nesting, the bigger the win: - 2 nested levels: Save 300ms - 3 nested levels: Save 600ms   - 4 nested levels: Save 900ms 𝗕𝗼𝗻𝘂𝘀: 𝗣𝗿𝗲𝗳𝗲𝘁𝗰𝗵𝗶𝗻𝗴 With React Router's prefetch feature, data starts loading when users HOVER over a link. By the time they click, the page loads instantly. No waiting. 𝗪𝗵𝗮𝘁 𝗮𝗯𝗼𝘂𝘁 𝗥𝗲𝗮𝗰𝘁 𝗤𝘂𝗲𝗿𝘆? React Query is excellent for caching and mutations, but it still fetches after components render. The winning combination: - React Router loaders for route-level data (parallel loading) - React Query for dynamic updates, polling, and mutations 𝗧𝗵𝗲 𝗯𝗼𝘁𝘁𝗼𝗺 𝗹𝗶𝗻𝗲: Parallel > Sequential. Always. Your users are waiting on sequential waterfalls. Fix it. Wait times in this post are simplified they can vary in real life scenarios 👇 Comment below if you have faced challenges like this #ReactJS #WebPerformance #ReactRouter #JavaScript #FrontendDevelopment

⚡ 𝗥𝗲𝗮𝗰𝘁 𝗖𝗮𝗰𝗵𝗶𝗻𝗴 𝗔𝗣𝗜 𝗗𝗮𝘁𝗮 (𝗥𝗲𝗮𝗹-𝗪𝗼𝗿𝗹𝗱 𝗣𝗮𝘁𝘁𝗲𝗿𝗻) In my last few posts, I shared about: • Pagination • Retry logic • Infinite Scroll Today I want to talk about one thing I recently focused on while building React apps 👇 𝗖𝗮𝗰𝗵𝗶𝗻𝗴 𝗔𝗣𝗜 𝗱𝗮𝘁𝗮 ❓ 𝗪𝗵𝘆 𝗶𝘀 𝗰𝗮𝗰𝗵𝗶𝗻𝗴 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁? When we don’t use caching: – The same API gets called again and again – Network calls increase – UI feels slower than it should ✅ 𝗦𝗼 𝘄𝗵𝗮𝘁 𝗶𝘀 𝗔𝗣𝗜 𝗰𝗮𝗰𝗵𝗶𝗻𝗴? In simple words: We store the API response somewhere and reuse it instead of calling the API every time. This helps in: • Faster UI • Better performance • Smoother user experience 🧠 𝗕𝗮𝘀𝗶𝗰 𝗶𝗱𝗲𝗮 𝗜 𝗳𝗼𝗹𝗹𝗼𝘄𝗲𝗱 1️⃣ Call the API 2️⃣ Store the response (state / ref / object) 3️⃣ Next time, check if data already exists 4️⃣ If yes → use it 5️⃣ If not → call the API again 🔄 𝗖𝗮𝗰𝗵𝗶𝗻𝗴 𝗶𝘀 𝗿𝗲𝗮𝗹𝗹𝘆 𝘂𝘀𝗲𝗳𝘂𝗹 𝗶𝗻 𝗰𝗮𝘀𝗲𝘀 𝗹𝗶𝗸𝗲 ✔️ Pagination ✔️ Infinite scroll ✔️ Navigating back and forth ✔️ Avoiding duplicate API calls This small change makes a 𝗯𝗶𝗴 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗶𝗻 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗮𝗽𝗽𝘀. 📸 I’ve attached a small code snippet showing: • Simple in-memory caching • Avoiding repeated API calls 👉 𝗡𝗲𝘅𝘁 𝘁𝗼𝗽𝗶𝗰𝘀 𝗜’𝗺 𝗽𝗹𝗮𝗻𝗻𝗶𝗻𝗴: • Pagination vs Infinite Scroll (interview point of view) • Intro to React Query (why it’s used in real projects) Would love to know — 𝘄𝗵𝗮𝘁 𝘀𝗵𝗼𝘂𝗹𝗱 𝗜 𝘀𝗵𝗮𝗿𝗲 𝗻𝗲𝘅𝘁? 👇 #ReactJS #FrontendDevelopment #ReactHooks #JavaScript #LearningInPublic #WebDevelopment

🗑️ Stop writing useEffect for data fetching. Seriously. If your React code looks like a soup of useEffect, useState, isLoading, and isError just to fetch a list of users, you are doing it the hard way. 🥵 Enter TanStack Query (aka React Query). 🦅 It is not just a data fetching library; it is an Async State Manager. It handles the stuff that is actually really hard to build yourself: - Caching: "I already fetched this 5 seconds ago, show the cached version instantly." ⚡ - Deduping: "You clicked the button 10 times? I'll only send 1 request." 🛑 - Background Updates: "User switched tabs and came back? Let me silently refresh the data." 🔄 - Stale-While-Revalidate: Show old data while fetching new data. The Comparison: ⚖️ ❌ The Old Way (Manual Labor): You have to manually toggle loading true/false, catch errors, avoid race conditions, and fix memory leaks if the component unmounts. It's a bug factory. 🐛 ✅ The TanStack Way: You tell it what to fetch, and it handles the how, when, and where. It removes ~50% of your boilerplate code and makes your app feel instant. If you aren't using it in 2026, you are working too hard. 🛀 #TanStackQuery #ReactJS #WebDevelopment #Frontend #JavaScript #CodingTips #StateManagement

Shipping something I’ve wanted for a while → RamifyJS. It’s a reactive in-memory database for JavaScript/TypeScript. Not state management. Not a wrapper. A real data layer that runs entirely in-process. Why I built it: Most apps don’t need network latency or async overhead just to manage local data. I wanted something synchronous, fast, type-safe, and predictable with querying and live updates built in. What it focuses on: * In-memory collections with indexing * Fluent querying (filter, sort, paginate) * Reactive subscriptions to query results * Runs in browser, Node, and edge * Zero dependencies, tiny footprint * Fully typed The goal is simple: Treat local data like a proper database without paying the usual complexity cost. Docs + demo: https://lnkd.in/gSGh5ckP Would love honest feedback from engineers who care about performance and clean data layers.

Why your Fetch calls need more than just a .catch() ?🌐 Monitoring errors in modern JavaScript apps is tricky. Most developers think a simple global listener is enough, but "Async" errors often slip through the cracks. If you want full visibility into your data flow, you need to monitor these 3 specific layers: 1️⃣ The Gateway: setupFetchCapture Did you know that fetch doesn't throw an error for 404 or 500 status codes? As long as the server responds, fetch is happy. The Fix: We intercept the fetch call to check response.ok. If it's false, we report it. This catches server-side failures that usually go unnoticed. 2️⃣ The Safety Net: unhandledrejection What happens if a fetch fails (like a network timeout) and there is no .catch() block? It becomes a "Silent Killer" in your app. The Fix: Using the unhandledrejection listener allows us to catch these "broken promises." It’s the ultimate safety net for the JavaScript Event Loop. 3️⃣ The Human Logic: console.error Sometimes the network is fine, and the code doesn't crash, but the data is wrong. The developer manually logs an error like: console.error("Invalid API Key"). The Fix: By wrapping (Monkey Patching) the native console.error, we can capture these logical errors that the developer intentionally flagged. The Bottom Line: True observability isn't just about waiting for a crash. It’s about connecting the dots between the Network, the Event Loop, and the Developer's Intent. #JavaScript #WebDevelopment #Coding #Frontend #ProgrammingTips #SoftwareEngineering

I built a Store Rating Application to understand how real-world rating systems work. This is a full-stack project with: Backend: Express.js Database: PostgreSQL Frontend: React.js The app supports 3 roles: • Admin – manages users and stores, views system stats • User – searches stores and submits ratings (1–5) • Store Owner – views who rated their store and average rating What I learned from this project: ✔ Role-based access control ✔ API design for real use cases ✔ Database relationships ✔ Full-stack flow from UI to backend If you want to understand how a rating system works in practice, 👉 Check out the GitHub link for full implementation: [ https://lnkd.in/dSBtKhcE ] Feedback and suggestions are welcome. #FullStack #WebDevelopment #ReactJS #PostgreSQL #ExpressJS #Projects #Learning

🚀 Built a Backend-Based Notes Web App (Without Using a Database) I recently built a notes/task management web application using Node.js, Express, and EJS, where all data is stored and managed using the file system instead of a traditional database. 🔹 Key Highlights: 📁 Notes are created and stored as individual .txt files 🧠 Dynamic rendering using EJS templates 🔄 Automatic server restart using Nodemon 🛣️ RESTful routing to: Create new notes List all saved notes Read individual note content ❌ No database used — data persistence handled via Node.js fs module 🛠️ Tech Stack: Node.js Express.js EJS File System (fs) HTML, CSS This project helped me understand: How backend logic works without databases Request handling (GET, POST) Server-side rendering File-based data persistence Small step, but a strong foundation toward backend development 💻✨ Open to feedback and suggestions! #NodeJS #ExpressJS #BackendDevelopment #WebDevelopment #LearningByBuilding #JavaScript #EJS