Connecting frontend with backend looked easy… until I actually tried it. When I started my project, I genuinely thought: “Just call the API and display the data. That’s it.” Yeah… not even close. Sometimes the API wouldn’t respond. Sometimes I’d get errors that made zero sense. Sometimes the data coming back was completely different from what I expected. I remember spending hours stuck on things like: 1. why is this request failing? 2. why is the response empty? 3. why is my UI not updating even after getting data? That’s when it hit me… It’s not just about writing API calls. It’s about actually understanding how data flows between frontend and backend. At some point, I started seeing it differently. Data doesn’t just magically show up in the UI. There’s a full journey behind it: User clicks something → Frontend sends a request → Backend receives it → Processes it (maybe talks to the database) → Sends a response back → Frontend updates the UI And if something breaks anywhere in between… everything breaks. There were times my request wasn’t even reaching the backend. Sometimes the backend was working fine, but I was reading the response wrong. And sometimes the data was correct, but I wasn’t updating state properly… so nothing changed on the screen. Things that slowly helped me: 1. testing APIs in Postman first 2. logging everything instead of guessing 3. handling errors properly (instead of ignoring them and hoping it works) Honestly, it was frustrating. But looking back, that’s where most of the real learning happened. #webdevelopment #reactjs #nodejs #springboot #fullstackdeveloper

GraphQL Series — Day 2 Now that we know what GraphQL is… let’s understand the foundation of it — Types 👇 👉 GraphQL is a strongly typed system 👉 Every piece of data has a clearly defined type 👉 This makes APIs predictable and easier to work with 💡 Think of it as a blueprint that defines what data looks like. 🧠 Types in GraphQL 1. Scalars (basic values) ✔ String ✔ Int ✔ Float ✔ Boolean ✔ ID 👉 These are the simplest building blocks. 2. Object Types ✔ Used to define structured data ✔ Similar to objects in JavaScript Example idea: A User type can have name, email, and id 3. Nested Types ✔ Types can reference other types ✔ Helps represent real-world relationships 👉 Example: User → Posts → Comments 4. Non-Null (!) Types ✔ Ensures a field must always have a value ✔ Prevents unexpected null errors 👉 Makes your API more reliable ⚡ Why Types Matter ✔ Clear contract between frontend & backend ✔ Better developer experience ✔ Fewer runtime surprises ✔ Easier to scale APIs Follow for more frontend insights 📘 #GraphQL #Frontend #WebDevelopment #APIs #JavaScript #ReactJS #TechLearning #LearnInPublic #DevCommunity #FrontendEngineer #100DaysOfCode

A technical comparison of NestJS and Express.js for backend development. Learn architecture, tooling, performance, deployment, NZ data considerations, and business impact.

Built a Persistent Task Manager (React) as part of my learning journey focusing on state architecture and real-world data handling. This project goes beyond simple state and introduces how applications manage and persist data effectively. What I built A task manager where users can: Add tasks Delete tasks Mark tasks as complete Filter tasks Persist data even after refresh Concepts practiced • useReducer for structured state management • localStorage for persistence • CRUD operations • Filtering logic • State architecture design Key takeaway This project helped me understand how to structure and manage complex state instead of relying only on basic useState. Designing state properly makes applications more scalable and easier to maintain. Next improvements Task priority Due dates Categories Repo- https://lnkd.in/dP_fGmAA Step by step moving toward building production-level React applications. #reactjs #frontend #webdevelopment #buildinpublic

🚀 Why GraphQL is changing the way we build APIs Most developers start with REST APIs… until they hit real-world problems like: ❌ Over-fetching data ❌ Under-fetching data ❌ Multiple API calls for one screen ❌ Versioning headaches That’s where GraphQL comes in. 💡 What is GraphQL? GraphQL is a query language for APIs that lets the client request exactly the data it needs — nothing more, nothing less. 🔑 Key advantages: • Single endpoint instead of multiple REST routes • Fetch nested data in one request • Strongly typed schema (better developer experience) • No more over/under fetching • Faster frontend development cycles ⚙️ Simple example mindset shift: REST: GET /user GET /user/orders GET /user/profile GraphQL: { user { name orders { id total } } } One request. Clean data. Less pain. 🔥 Where GraphQL shines: • Dashboards with complex data • Mobile apps (reduce network calls) • Microservices architecture • Real-time apps with subscriptions 📌 My takeaway: GraphQL doesn’t replace REST everywhere — but it solves real scaling problems when your frontend becomes data-hungry. 💬 Question for developers: Have you used GraphQL in production or are you still on REST APIs? What challenges did you face? #GraphQL #WebDevelopment #BackendDevelopment #FrontendDevelopment #APIs #JavaScript #NodeJS #FullStackDeveloper #ReactJS #SoftwareEngineering

"Supercharging Your React State Management with Zustand - DEV Community" Zustand is a lightweight state management library for React that offers a minimalistic API, reducing boilerplate code compared to solutions like Redux. It allows developers to create stores with simple hooks, facilitating efficient state management without the need for complex setup. Zustand's performance is optimized, ensuring that only necessary components re-render when state changes, and it integrates seamlessly with TypeScript for type safety. Its flexibility makes it suitable for both small and large applications, providing a scalable solution for managing state in React projects. Zustand is a lightweight, intuitive state management library for React that simplifies managing both local and global state. It eliminates the need for complex boilerplate code typical of libraries like Redux, offering a minimal API for quick setup and ease of use. Zustand integrates seamlessly with React, leveraging hooks for efficient state updates and selective subscriptions to improve performance. It supports middleware for advanced features like persistence, logging, and devtools integration. Zustand is particularly suitable for scalable applications, offering flexibility without compromising on performance. #️⃣ **#ReactJS #Zustand #StateManagement #WebDevelopment #JavaScript** https://lnkd.in/dEpHGxt9 --- ♻ Repost if you found the post helpful and help others find it. 🙏 Let's learn and grow together! 🚀

In Node.js, writing scalable backend code is not just about APIs… it’s about how you manage logic, state, and performance. That’s where Closures and Higher-Order Functions (HOF) play a key role. 🔥 Core Concepts (Node.js Perspective) ✔ Closures Preserve data across function calls Help avoid global variables Useful for managing request-level state ✔ Higher-Order Functions (HOF) Enable reusable and flexible logic Power middleware and async handling Make code modular and clean ⚡ Real-Time Node.js Use Cases ✅ 1. Middleware Design (Express.js) HOF used to wrap request handlers Closures store request-specific data 👉 Example: auth middleware, logging middleware ✅ 2. API Rate Limiting Closures maintain request count per user Prevents server overload in real-time systems ✅ 3. Caching Layer (Performance Optimization) Closures store previous API responses Reduce DB calls → faster response time ✅ 4. Booking / Payment Flow (Real Projects) Maintain state across multiple API calls Example: travel booking → availability → payment → confirmation ✅ 5. Error Handling Wrapper (HOF) Create reusable async error handlers Avoid repeating try-catch in every API ✅ 6. Custom Logger & Monitoring HOF wraps APIs for logging Closures store metadata like request time, user info 💡 Why It Matters in Node.js • Improves server performance • Helps handle high concurrent requests • Keeps code clean & scalable • Essential for event-driven architecture 🧠 Final Thought In Node.js, Closures + HOF are not optional… They are behind the scenes of every efficient backend system — from middleware to API handling.#NodeJS #JavaScript #BackendDevelopment #MERNStack #ExpressJS #FullStackDeveloper #SoftwareEngineering #APIDevelopment #Tech #Developers #CodingLife

🚀 Recently built something that felt less like a “project” and more like a real product. There were moments I questioned if I was doing it right… but I kept going Behind every feature, there were hours of confusion, retries, and learning 👍 Introducing InsightFlow — a full stack data visualization platform designed to simulate how modern applications handle and present business data. Tech Stack: ⚛️ React.js 🟢 Node.js + Express 🗄️ MongoDB 📊 Chart.js 📌 Key Features: • Interactive dashboard with dynamic data • API-driven architecture • Clean and responsive UI • Real-time-like data updates • Structured backend for scalability Challenges along the way: • State management got messy At one point, my React state had more mood swings than me on a Monday morning 🙂 • Debugging took longer than expected Spent hours fixing an issue… turned out to be a small API route mistake. • Making data meaningful Displaying data is easy. Making it useful and intuitive took real effort. • Frontend ↔ Backend sync issues When everything works individually… but not together 😅 💡 What I learned: This wasn’t just about building an app — it was about building patience. Worked with RESTful API design using Node.js and Express, focusing on clean routing and modular backend structure. Gained hands-on experience with MongoDB for schema design and optimized CRUD operations. Strengthened skills in asynchronous data handling and seamless frontend–backend integration. Also improved debugging practices and implemented data visualization to present insights effectively. Not every day was productive, but every day taught me something. Behind every feature, there were hours of confusion, debugging, and small wins. This project wasn’t perfect — but it was progress. And honestly, that’s what matters the most. #FullStackDeveloper #ReactJS #NodeJS #WebDevelopment #SoftwareEngineering #BuildInPublic

🚀 Built a Scalable Backend Project: Task Management System I recently developed a 𝗧𝗮𝘀𝗸 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗔𝗣𝗜 with a strong focus on clean architecture, modular design, and real-world backend practices. 𝗪𝗵𝗮𝘁 𝗜 𝗕𝘂𝗶𝗹𝘁: • Create tasks with a primary assignee • Add collaborators (𝗯𝘂𝗹𝗸 𝗶𝗻𝘀𝗲𝗿𝘁 𝘀𝘂𝗽𝗽𝗼𝗿𝘁) • Update task status (todo → in-progress → done) • Dynamic filtering, sorting & pagination using a 𝘀𝗶𝗻𝗴𝗹𝗲 𝗳𝗹𝗲𝘅𝗶𝗯𝗹𝗲 𝗚𝗘𝗧 𝗔𝗣𝗜 • Detailed task view with joins (GET /tasks/:id) 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 & 𝗖𝗼𝗱𝗲 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 (𝗪𝗵𝗮𝘁 𝗜’𝗺 𝗣𝗿𝗼𝘂𝗱 𝗢𝗳): Instead of writing everything in one file, I designed a 𝗺𝗼𝗱𝘂𝗹𝗮𝗿 𝗮𝗻𝗱 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗯𝗮𝗰𝗸𝗲𝗻𝗱 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲: • controllers/ → Handle request & response • services/ → Business logic layer • query/ → Raw SQL queries (clean separation) • routes/ → API routing • middleware/ → Auth & validations • config/ → DB connection setup • migrations/ → Database schema management • types/ → Type safety with TypeScript 👉 This separation makes the system: ✔️ Easy to scale ✔️ Maintainable ✔️ Production-ready 𝗞𝗲𝘆 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝗔𝗽𝗽𝗹𝗶𝗲𝗱: • Proper DB relationships (𝟭:𝗡 𝗮𝗻𝗱 𝗠:𝗡) • RESTful API design (avoiding redundant endpoints) • Dynamic query building for flexible filtering • Bulk operations for better performance • Clean layering (Controller → Service → Query → DB) 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸: Node.js | Express | TypeScript | PostgreSQL 𝗕𝗶𝗴 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: Instead of creating multiple APIs like /assigned-tasks, /my-tasks, I built a 𝘀𝗶𝗻𝗴𝗹𝗲 𝗽𝗼𝘄𝗲𝗿𝗳𝘂𝗹 𝗲𝗻𝗱𝗽𝗼𝗶𝗻𝘁 (𝗚𝗘𝗧 /𝘁𝗮𝘀𝗸𝘀) that handles all use cases via query params — making the backend more scalable and clean. This project helped me move beyond basic CRUD and think in terms of 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝘀𝘆𝘀𝘁𝗲𝗺 𝗱𝗲𝘀𝗶𝗴𝗻 𝗮𝗻𝗱 𝗯𝗮𝗰𝗸𝗲𝗻𝗱 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲. Would love your feedback or suggestions 🙌 #BackendDevelopment #NodeJS #SystemDesign #APIDesign #TypeScript #LearningInPublic #SoftwareEngineering

I spent several weeks refactoring a React Native + Expo + Supabase codebase. A 2,461 line lib/supabase.ts file everyone was importing from, god screens over 1,400 lines, zero tests, 74 as any in the worst file, manual useState + useEffect + fetch all over the place, realtime subs inlined directly in components. Ended up being 87 PRs. Zero regressions. Monolith went to 11 domain modules, added 88 tests, extracted a bunch of hooks and components along the way. At some point the methodology got specific enough that I figured it was worth packaging. So I wrote it up as a Claude Code plugin. The core idea is structure preserving migration. I wanted to keep the same behavior, w a better organization. Never touch business logic during a move. Re exports keep consumers working during the split phase, then you strip them and audit at the end. What's in it: 8 phases with explicit skip conditions, progressive disclosure so only the active phase loads into context. 4 level rollback, commit, sub branch, phase, full reset. A code-validator agent (suuuper useful tbh, proud of this one) that gates every commit, auto detects the stack (RN, Next, Vite, plain TS), runs type check + lint + tests + some refactor specific static review for orphaned imports, circular deps, dynamic imports that grep misses. Plus reference docs on team coordination (solo vs small team vs 7+ dev squad), DB migrations with expand migrate contract, and the common pitfalls I hit. What it's not: Not for codebases under ~10k LOC, manual is just faster. Not a rewrite tool, it preserves behavior, doesn't rethink it. Not for non TS/JS monoliths since the re export pattern depends on ESM. Not for ship this week type deadlines, you budget in weeks not days. (tbc how efficient can be coding agents with it, my hot take is that I used Opus 4.6 on that, not 4.7) The numbers above are from one specific project. Your codebase is different, your numbers will differ. The method works, the specific counts won't copy paste. Repo: https://lnkd.in/e-rZEvTz Feedback welcome, PRs appreciated. For those who'll use it only, curious about: Non Supabase users, does the realtime extraction translate cleanly to WebSocket / Firestore / EventSource etc. ? Monorepo users, where do the audit scripts break? Anyone who's done a similar refactor differently, what did I miss? Again feedbacks and PRs appreciated thx