Simplify URL Matching in JavaScript with URLPattern API

🚀 From Arrays to Efficiency: Mastering Set in JavaScript Today I solved the “Unique Rows in Boolean Matrix” problem using one simple yet powerful concept — Set. At first glance, the problem looks like a typical nested loop challenge. But instead of going brute force, I leveraged Set to achieve a clean and optimal solution. 💡 Key Idea: Convert each row into a string and store it in a Set to automatically handle duplicates. ✨ Why this is powerful: Eliminates duplicates in O(1) lookup time Avoids unnecessary nested loops Keeps the solution clean and readable 📊 Complexity: Time: O(n × m) Space: O(n × m) 🔥 Takeaway: Sometimes, the difference between an average solution and an optimal one is just knowing the right data structure. Today it was Set. Tomorrow, it could be something else. 💬 Curious: Where else have you used Set to simplify a problem? #JavaScript #DSA #CodingInterview #WebDevelopment #ProblemSolving #100DaysOfCode

💡 Quick JS Trick: Group Anagrams Want to group words that are anagrams of each other? Use sorting & a Map — super clean and efficient: ✅ How it works: 🔹 Sort letters in each word → same letters = same key. 🔹 Use a Map to group words by this key. 🔹 Return all grouped values. ✨ Benefits: ✅ Simple ✅ Fast ✅ Works for any list of strings #JavaScript #CodingTips #Algorithms #DataStructures #CleanCode #WebDevelopment #JSChallenge

Today I finally understood how JavaScript actually stores data in memory — and it changed the way I look at code. Earlier, I used to just write variables and functions without thinking much about what’s happening behind the scenes. But now it makes a lot more sense: Primitive values (like numbers, strings, booleans) are stored directly in memory Reference types (like arrays and objects) are stored differently — the variable holds a reference, not the actual value That’s why things like this behave unexpectedly sometimes: Copying objects doesn’t create a real copy Changing one reference can affect another Understanding this cleared up a lot of confusion I had while debugging. Still learning, but this felt like a small breakthrough Hitesh Choudhary Piyush Garg Chai Code #JavaScript #WebDevelopment #100DaysOfCode #LearningInPublic

👉 If you're writing modern JavaScript, these 10 underrated features can instantly improve your code 👇 💡 Optional Chaining ("?.") → Stop “cannot read property of undefined” errors 💡 Nullish Coalescing ("??") → Smarter defaults (without breaking "0" or """") 💡 Array.at() → Clean way to access last elements 💡 structuredClone() → Proper deep copy (no hacks) 💡 Promise.any() → First successful API wins 💡 Object.hasOwn() → Safer property checks 💡 replaceAll() → Replace all matches without regex 💡 Top-Level Await → Cleaner async code in modules 💡 Logical Assignment ("||=", "&&=", "??=") → Write less, do more 💡 WeakMap / WeakSet → Memory-efficient data handling 🔥 These aren’t “advanced” features — They’re modern JavaScript essentials in 2026. --- 💬 Curious — Which one are you already using in production? And which one is new for you? --- #JavaScript #WebDevelopment #Frontend #FullStackDeveloper #Coding #SoftwareEngineering #TechJobs

Built an efficient LRU Cache from scratch using JavaScript. Key highlights of the implementation: Designed a custom Doubly Linked List for O(1) insertions and deletions Used a HashMap to achieve constant-time access Ensured optimal eviction strategy by always removing the least recently used node Maintained strict O(1) time complexity for both get and put operations Performance: Runtime: 102 ms (faster than ~57% of submissions) Memory: 113.67 MB This problem reinforced how combining data structures (HashMap + DLL) leads to highly optimized systems — a pattern widely used in real-world caching systems like databases and browsers. Continuing to focus on writing clean, efficient, and scalable code. #DataStructures #Algorithms #JavaScript #SystemDesign #Coding

Backtracking: Combination Sum Problem Day 4 👈 Problem: - Given an array of numbers and a target value, find all unique combinations where the numbers sum up to the target. 🧠 Summary (Simple Understanding) Think of it like: "Pick a number → reduce target → try again → backtrack → try next number" This pattern helps you explore all possibilities efficiently without duplicates. #DataStructures #Algorithms #Backtracking #Recursion #TypeScript #JavaScript #CodingInterview #DSA #LeetCode #ProblemSolving #SoftwareEngineering

Subject - Common mistake while using fetch in JavaScript Many beginners (including me) try to do this: const data = await fetch('https://lnkd.in/gNBBq58S'); const json = await JSON.stringify(data); 🚫 This is wrong because fetch() returns a Response object, not actual JSON data. ✅ Correct approach: const data = await fetch('https://lnkd.in/gNBBq58S'); const json = await data.json(); ✔️ Lesson: Always use .json() to extract data from the response. Small mistake, but important for real-world projects. #javascript #webdevelopment #frontend #coding #learninpublic

Day 10/100 of JavaScript 🚀 Today’s topic : Fetch API "fetch" is used to make HTTP requests in JavaScript and is a modern replacement for XMLHttpRequest Basic usage : fetch("https://lnkd.in/gCA7VyNQ") .then(res => res.json()) .then(data => console.log(data)) .catch(err => console.error(err)); Using async/await : async function getData() { try { const res = await fetch("https://lnkd.in/gCA7VyNQ"); const data = await res.json(); console.log(data); } catch (err) { console.error(err); } } What it does : - Returns a Promise - Cleaner than XMLHttpRequest - Works well with async/await #Day10 #JavaScript #100DaysOfCode

I recently implemented my first Linked List from scratch in JavaScript — no libraries, just raw pointer manipulation. This wasn’t just about writing code; it forced me to understand how data structures actually work under the hood. Here’s what I built: A custom Node structure with value and next pointers Core operations: addAtHead addAtTail addAtIndex deleteAtIndex get What made this interesting wasn’t the syntax — it was the edge cases and pointer management: Handling insertions at head vs tail Maintaining consistent length Avoiding broken references during insertion/deletion Fixing off-by-one errors in traversal Biggest takeaway: Linked Lists are simple in theory, but brutally unforgiving if your pointer logic is even slightly off. This exercise sharpened how I think about: Data structure integrity Boundary conditions Writing predictable, bug-resistant logic Still refining and testing edge cases — but this was a solid step forward. #JavaScript #DataStructures #LinkedList #Coding #SoftwareEngineering #LearningInPublic

What To Know in JavaScript (2026 Edition). Part 1. Iterator Helpers (lazy data processing) JavaScript introduced Iterator Helpers — methods like .map(), .filter(), .take() directly on iterators. The goal is to avoid unnecessary intermediate arrays and improve performance. Instead of chaining operations that create arrays at every step, you get: → less memory usage → fewer computations → more predictable performance #frontend #webdev #javascript #performance