Arjun Vinod’s Post

🚀 Stop Managing API State Manually in React! If you're still using `useEffect` + `useState` for API calls… you're doing extra work 😅 Let’s talk about React Query (TanStack Query) 👇 --- 🧠 What is React Query? A powerful library to **fetch, cache, and manage server state (API data)** in React apps. --- ❌ Traditional Way (Problem) * Manual loading & error handling * Repeated API calls * No caching * Complex & messy code --- ✅ With React Query (Solution) * Automatic caching ⚡ * Background refetching 🔄 * Shared data across components 🔗 * Cleaner code 🧹 * Better performance 🚀 --- ⚙️ How it works? 1️⃣ Fetch data 2️⃣ Store in cache 3️⃣ Return instantly on next request 4️⃣ Refetch in background if stale 5️⃣ UI updates automatically --- 🔥 Key Benefits ✔️ Auto caching (no duplicate API calls) ✔️ Faster performance ✔️ Less boilerplate code ✔️ Built-in mutation support (POST/PUT/DELETE) ✔️ Smart retry & error handling ✔️ Data sync across components --- ⚠️ Disadvantages * Learning curve (staleTime, cacheTime) * Not needed for small apps * Slight increase in bundle size --- 🧩 When to Use React Query? ✅ API-heavy applications ✅ Dashboards / Admin panels ✅ Shared data across components ✅ Need performance optimization --- 🚫 When NOT to Use? ❌ Static or simple apps ❌ No backend/API usage ❌ Minimal state management #ReactJS #WebDevelopment #Frontend #JavaScript #ReactQuery #TanStackQuery #SoftwareDevelopment

🌐 Master Server-State: TanStack React Query vs. Redux 🔍 What is TanStack React Query? TanStack Query (formerly React Query) is a Server-State library. It’s designed specifically to manage asynchronous data—fetching, caching, synchronizing, and updating state that lives on a server. 📡✨ It automates the "boring" parts of development: Automatic Caching: No more manual loading spinners on every click. 🏎️ Background Refetching: Keeps your data fresh while the user stays on the page. 🔄 Error Handling: Built-in retry logic and error states. 🛠️ ⚖️ How is it different from Redux? Redux is for Client-State: It manages data that lives only in your app (like a sidebar being open, a dark mode toggle, or a multi-step form). It is highly predictable but requires lots of "boilerplate" (actions, reducers, thunks). 🧠 TanStack Query is for Server-State: It manages data that comes from an API. It replaces 50 lines of Redux boilerplate with a single, powerful hook. ⚡ 🏥 Real-Life Example: The "Library vs. Personal Notepad" 📚 Imagine you are researching a topic: Redux (Personal Notepad): You write down every single fact yourself. If a fact changes at the source, you have to manually cross it out and rewrite it. If you lose your notepad, you have nothing. 📝 TanStack Query (The Librarian): You ask the librarian for a book. They give it to you immediately if it’s on the shelf (Caching). If it’s old, they go get a new version while you keep reading (Background Update). If the book is missing, they try again automatically (Retries). 👩🏫✅ #ReactJS #TanStackQuery #Redux #WebDevelopment #FrontendArchitecture #JavaScript #StateManagement

Today I learned about performance optimization and data fetching in React using Code Splitting, Lazy Loading, Suspense, and React Query (TanStack Query). ** Code Splitting Code splitting helps break large bundles into smaller chunks, so the app loads faster and only required code is loaded when needed. ** React.lazy() It allows us to load components dynamically instead of loading everything at once. const Home = React.lazy(() => import("./Home")); ** Suspense & Fallback Suspense is used with lazy loading to show a fallback UI (like a loader) while the component is loading. <Suspense fallback={<h2>Loading...</h2>}> <Home /> </Suspense> ** React Query (TanStack Query) React Query helps in fetching, caching, and managing server data efficiently. It automatically handles API caching, loading states, and background updates. @Devendra Dhote @Ritik Rajput @Mohan Mourya @Suraj Mourya #ReactJS #WebDevelopment #FullStackDeveloper #CodingJourney

🚀 We stopped using Redux for server state — and built everything on TanStack Query instead. In a large Next.js 15 + React 19 app, this architecture scaled surprisingly well. Here’s what worked 👇 🏭 Query factories > raw hooks We wrapped useQuery / useInfiniteQuery into small factories. → Consistent query keys → Easy cache updates (setQueryData) → Simple invalidation No more scattered queryKey arrays across the codebase. 💾 Selective cache persistence (not everything!) Only important queries are saved to IndexedDB using a marker in the key. → No bloated cache → Fully controlled persistence ♾️ Virtual + infinite scrolling (game changer) We combined infinite queries with virtualization. 👉 The key idea: The virtualizer decides what to fetch — not the UI. This made large tables and kanban boards feel instant, even with thousands of rows. 📊 Reusable table layer Our table doesn’t care about data type. We inject a hook that returns paginated data. → Same table works for users, pipelines, or anything else → Clean separation of UI and data logic 🔄 Real-time updates without refetching WebSocket events directly update the cache using setQueryData. → UI updates instantly → No polling → One single source of truth 🔑 Simple invalidation We created a small utility with named invalidation helpers. → No one remembers query keys → Mutations stay clean 💡 Big takeaway Server state does NOT need Redux. TanStack Query already solves caching, syncing, and real-time updates — you just need to structure it well. #TanStack #ReactQuery #NextJS #React #Frontend #WebDev #JavaScript #TypeScript

🚀 Exploring React Query: A Game-Changer for Data Fetching! Recently, I’ve been diving into React Query, and it has completely changed how I handle server state in my React applications. Before using React Query, managing API calls meant dealing with a lot of boilerplate—loading states, error handling, caching, and refetching logic. Now, everything feels much cleaner and more efficient. ✨ What I’ve learned so far: 🔹 Simplified Data Fetching – With just a few lines of code, you can fetch, cache, and sync data effortlessly. 🔹 Automatic Caching – No need to manually store and manage API data. 🔹 Background Refetching – Keeps data fresh without interrupting the user experience. 🔹 Built-in Loading & Error States – Makes UI handling much easier. 🔹 DevTools Support – Helps visualize queries and debug effectively. 💡 One thing I really like is how it separates server state from UI state, making the application more scalable and maintainable. As someone growing in frontend development, learning tools like React Query is helping me write cleaner, more professional code. I’m excited to explore more advanced features like mutations, pagination, and query invalidation next! If you’re working with React and APIs, I highly recommend giving React Query a try 🙌 #React #ReactQuery #WebDevelopment #FrontendDevelopment #JavaScript #LearningJourney

Excited to announce Typedrift v1.0.0! 🎉 A new kind of React data-fetching library that eliminates the most painful part of modern full-stack development: “type drift “ between your frontend components and backend queries. What’s New in v1.0.0 - Props = Query: Define your component’s data needs via TypeScript interfaces, everything else is derived automatically. - Zero boilerplate resolvers with ‘view()’, ‘batch.one()’, ‘batch.many()’ - First-class mutations using ‘action()’ with Zod validation, guards, and built-in redirects - Production-ready: middleware, caching, OpenTelemetry, rate limiting, audit logs - Full React 19 + RSC compatibility - No codegen, no separate query hooks, no manual data wiring Why Typedrift? Because the biggest source of bugs in React/Next.js apps isn’t bad code, it’s “out-of-sync types” between what your component expects and what the server actually returns. Typedrift makes the component prop shape the “single source of truth”. The server must conform. Type safety becomes structural. If you’re tired of maintaining query files, fighting stale types, or dealing with the boilerplate of TanStack Query + Zod + manual wiring… this one’s for you. Check it out: https://lnkd.in/e5HRgUgA Would love your feedback, stars, or contributions! #React #TypeScript #NextJS #FullStack #DeveloperTools

Coming in typedrift v1.1.0 Exactly one week ago, I shipped the first version of Typedrift because I got tired of the same old headaches in data fetching for React-driven frameworks. Data fetching has always felt broken. You define exactly what data a component needs in its props… then duplicate that logic in a separate query. Over time, they drift. You only discover the mismatch at runtime. Typedrift fixes that. Instead of writing queries, you define a typed view from your model. That view becomes the single source of truth for both fetching on the server and the props your component receives. No more duplication. No drift. What’s new in v1.1.0: - TanStack Adapter: seamless integration with TanStack Start - Next.js Adapter: first-class support for App Router and Server Components Clean, type-safe data fetching with zero boilerplate and zero codegen. If you’ve felt the pain of maintaining queries that drift away from your components (especially if you’ve used Relay, tRPC, or TanStack Query), I’d love your feedback. Check it out: - NPM: https://lnkd.in/drSZji_9 - GitHub: https://lnkd.in/e5HRgUgA What do you think — does this approach solve a real problem for you? #React #TypeScript #DataFetching #WebDev #NextJS #TanStack

Fetching data is easy. Handling it like a pro is the hard part. 🔄📡 In the early days of React, we all got used to the "useEffect and Fetch" pattern. But as applications grow, simple fetching isn't enough. Modern users expect zero-latency, instant feedback, and seamless synchronization. Whether I'm using Next.js Server Actions or React Query, these are the 3 principles I follow to manage data like a Senior Developer: 1️⃣ Loading States & Skeletons: Never leave your user staring at a blank screen. I use Suspense and Skeleton Screens to provide immediate visual feedback, making the app feel faster even while the data is still traveling. 2️⃣ Caching & Revalidation: Don't waste your user's data or your server's resources. Implementing smart caching (like stale-while-revalidate) ensures that your UI is updated instantly with "stale" data while the "fresh" data fetches in the background. 3️⃣ Optimistic UI Updates: Why wait for the server to say "Success" before updating a Like button or a Todo item? By using Optimistic Updates, we update the UI immediately and roll back only if the request fails. This creates a "light-speed" user experience. The best apps don't just display data—they manage the flow of data effortlessly. What’s your go-to tool for data fetching in 2026? Are you team React Query, or are you moving everything to Next.js Server Actions? Let’s debate! 👇 #ReactJS #NextJS #WebDev #DataFetching #JavaScript #FrontendArchitecture #CodingTips

🚀 Exploring Modern Data Fetching in React with TanStack React Query In my recent work with React applications, I’ve been diving deeper into TanStack React Query and how it simplifies server-state management. 🔍Why TanStack React Query? Managing API data in React using traditional methods (useEffect + useState) can quickly become complex especially when dealing with caching, loading states, retries, and background updates. TanStack React Query solves these problems by: ✅ Automatic Caching – Reduces unnecessary API calls and improves performance ✅ Background Refetching – Keeps data fresh without manual intervention ✅ Built-in Loading & Error Handling – Cleaner and more maintainable code ✅ Pagination & Infinite Queries – Efficient handling of large datasets ✅ DevTools Support – Easy debugging and monitoring 💡 Key Advantage: It separates server state from UI state, making applications more scalable and easier to manage. 📌 Example Use Case: Instead of manually calling APIs in useEffect, we can simply use: useQuery({ queryKey: ['users'], queryFn: fetchUsers }) This approach reduces boilerplate code and improves overall developer experience. 🔥 Conclusion: If you are building modern React applications, integrating TanStack React Query can significantly enhance performance, maintainability, and user experience. #ReactJS #TanStack #ReactQuery #WebDevelopment #FrontendDevelopment #JavaScript #SoftwareDevelopment

State management and data fetching in React just got smarter with Redux Toolkit Query (RTK Query) 🚀 If you’ve ever struggled with handling API calls, caching, loading states, and keeping your UI in sync — RTK Query is a game changer. 🔹 What is RTK Query? A powerful data fetching and caching tool built on top of Redux Toolkit that eliminates the need for writing complex async logic. 🔹 Why use it? ✅ Automatic caching & re-fetching ✅ Built-in loading & error states ✅ Reduces boilerplate code drastically ✅ Seamless integration with Redux store ✅ Optimistic updates support 🔹 Key Concept: You define an API slice once, and RTK Query generates hooks like "useGetUsersQuery()" for you — clean, scalable, and efficient. 🔹 When should you use it? - Large-scale applications - Apps with frequent API interactions - When you want predictable state + caching 💡 Pro Tip: RTK Query can often replace libraries like React Query if you're already using Redux — keeping everything centralized. In modern React development, it's not just about managing state — it's about managing server state efficiently. RTK Query does exactly that. #ReactJS #ReduxToolkit #RTKQuery #WebDevelopment #Frontend #JavaScript #SoftwareEngineering #CleanCode