Python JavaScript Coding Interview Prep Tool in Browser

🚀 𝗝𝘂𝘀𝘁 𝗘𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗧𝗲𝘅𝘁𝘂𝗮𝗹... 𝗮𝗻𝗱 𝗶𝘁’𝘀 𝗶𝗻𝘁𝗲𝗿𝗲𝘀𝘁𝗶𝗻𝗴 👀 Lately, I’ve been playing around with Textual (Python TUI framework) — no big project yet, just pure experimentation. And honestly… it feels different. 💡 Building UI without a browser 💡 No React, no Angular 💡 Just Python + terminal Still early for me, but a few things stood out: • Super fast to spin up • Clean UI with CSS-like styling • Everything in one language (Python) • Runs anywhere — even over SSH Not saying it replaces web or desktop apps… But for internal tools, dashboards, or admin panels — this could be really useful. For now, I’m just exploring and testing ideas. Let’s see where it goes 𝗔𝗻𝘆𝗼𝗻𝗲 𝗲𝗹𝘀𝗲 𝘁𝗿𝗶𝗲𝗱 𝗧𝗲𝘅𝘁𝘂𝗮𝗹 𝘆𝗲𝘁? #Python #Textual #LearningInPublic #DevExperiment #FullStackDeveloper

👉 Read the full article here: https://lnkd.in/dPBDH8fZ 🚀 New Article Published: Array Flatten in JavaScript Understanding how to work with nested arrays is an important skill for every JavaScript developer. In this article, I explained: • What nested arrays are • Why flattening arrays is useful • The concept of array flattening • Different approaches (built-in methods, recursion, loops) • Common interview scenarios I also included step-by-step explanations and visual thinking to make the concept easy to understand. This topic really helped me improve my problem-solving mindset while working with real-world data structures. Big thanks to Hitesh Choudhary Sir, Piyush Garg Sir and Chai Aur Code for continuous learning and guidance 🙌 #JavaScript #WebDevelopment #Coding #LearningInPublic #Developers #Frontend #100DaysOfCode

🚀 𝗗𝗷𝘂𝗹𝗲 𝘃𝟮.𝟬.𝟬 𝗶𝘀 𝗵𝗲𝗿𝗲. Last weekend I released Djule v1. Today, v2 is already here. Djule started as an experiment to make server-rendered UI in Python feel more modern without needing a heavy frontend framework. In just a week, it has gone from an early parser/runtime foundation to something that feels much more like a real language and developer workflow. For anyone who has not seen it before: 𝗗𝗷𝘂𝗹𝗲 is a new templating language built on top of Django. It lets you build more expressive, component-based UI while still keeping Django’s server-rendered architecture. 𝗪𝗵𝗮𝘁’𝘀 𝗻𝗲𝘄 𝗶𝗻 𝘃𝟮: • 𝗛𝗧𝗠𝗟 𝗳𝗲𝗲𝗹𝘀 𝗺𝗼𝗿𝗲 𝗻𝗮𝘁𝘂𝗿𝗮𝗹 Native support Self-closing HTML and component tags Interpolated strings inside attributes Better multiline syntax for expressions and grouped values • 𝗖𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀 𝗮𝗿𝗲 𝗲𝗮𝘀𝗶𝗲𝗿 𝘁𝗼 𝘄𝗿𝗶𝘁𝗲 𝗮𝗻𝗱 𝗿𝗲𝘂𝘀𝗲 Multiline component parameter lists Default component parameters Simpler props like error=True instead of error={True} • 𝗘𝗿𝗿𝗼𝗿 𝗺𝗲𝘀𝘀𝗮𝗴𝗲𝘀 𝗮𝗿𝗲 𝗺𝘂𝗰𝗵 𝗯𝗲𝘁𝘁𝗲𝗿 Clear parser diagnostics Real file and line context when something breaks Better import and component error reporting • 𝗗𝗷𝗮𝗻𝗴𝗼 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗺𝘂𝗰𝗵 𝘀𝗺𝗼𝗼𝘁𝗵𝗲𝗿 Dedicated Django template backend Settings-aware import roots Support for Django-style global context processors and built-in tags That means Djule now works much more naturally inside a real Django project without needing a bunch of manual setup. 𝗧𝗵𝗲 𝗩𝗦 𝗖𝗼𝗱𝗲 𝗲𝘅𝘁𝗲𝗻𝘀𝗶𝗼𝗻 𝗮𝗹𝘀𝗼 𝗴𝗼𝘁 𝗮 𝗺𝗮𝗷𝗼𝗿 𝘂𝗽𝗴𝗿𝗮𝗱𝗲: • Live diagnostics while you type • Autocomplete for components, props, imports, globals, and snippets • Better import UX • Django-aware editor globals • Go-to-definition for components • Improved highlighting for newer Djule syntax v2 feels like the point where Djule starts becoming more than just “a parser I built” and starts feeling like a real language workflow. 👇 𝗬𝗼𝘂 𝗰𝗮𝗻 𝘁𝗿𝘆 𝗶𝘁 𝗵𝗲𝗿𝗲: PyPI: pip install djule VS Code Marketplace: rhxrr.djule Would love to hear what people think, especially from people building with Python or Django. #Python #Django #WebDevelopment #OpenSource #ProgrammingLanguages #VSCode #DeveloperTools

I compared the same logic in JS and Rust. The result? The "complex" Rust version wasn't just drastically faster — it was actually shorter and cleaner. If you’ve worked with JavaScript, Python, or Java, you’ve likely encountered the classic problem of counting how many times each character appears in a string. In JavaScript, the typical approach looks like this: if (map.has(ch)) { map.set(ch, map.get(ch) + 1); } else { map.set(ch, 1); } While this seems straightforward, there’s a hidden performance flaw: The Double Lookup & Value Copying. This one-liner requires extra work from the engine: 1️⃣ map.get(ch): Calculates the hash, traverses memory, finds the bucket, and extracts a copy of the number. 2️⃣ + 1: Creates a brand-new number primitive in memory. 3️⃣ map.set(ch, ...): Calculates the hash again, traverses memory again, finds the same bucket, and copies the new number back into it. Now, let's see how Rust handles the same logic: *counts.entry(ch).or_insert(0) += 1; This isn't just syntactic sugar; it utilizes Rust's Entry API, designed for maximum hardware efficiency. Here’s why it’s blazingly fast: - It calculates the hash exactly once. - It locates the memory bucket exactly once. - It returns a &mut (a direct mutable pointer/reference) right to that memory slot. The += operator modifies the primitive value in-place without copying it out or needing a .set() method to put it back. This results in code that reads like a high-level script but executes with the speed of a systems language. Zero-cost abstractions at their finest! #Rust #JavaScript #Programming #Performance #SoftwareEngineering #WebDev #RustLang

🚀 Starting my journey in web development! I’m happy to share my first project — a Flask CRUD Web Application 💻 🔹 Built using: Flask, MySQL, HTML, CSS 🔹 Features: Create, Read, Update, Delete operations 🔹 Deployed using Render 🔹 Source code available on GitHub 🌐 Live Demo: https://lnkd.in/gXdhjUYY 💻 GitHub Repo: https://lnkd.in/gRbe_2YB This is just the beginning — looking forward to building more advanced and impactful projects ahead! #Flask #Python #WebDevelopment #BeginnerProject #svhec Dr. Muralisankar Kumaresan Guide KABILESH RAMAR

🚀 Week 6 Backend Dev Challenge: Regular Expressions(Regex) This week, I worked on something that felt both nerdy and surprisingly exciting: validating a credit card number using JavaScript. Yes I know, credit card validation doesn’t sound exciting at first… but once you dive into Regular Expressions, your brain suddenly enters “detective mode.” 😅 I had a Verve card lying around so I decided to use it for this. I made some research and found out Verve cards had different prefixes. Some started with 5060, 5078 and 6500. To validate the card, I had to use a regex pattern. Think of regex as that strict friend who checks every tiny detail before letting anyone into the party. 😂 The pattern I used: ^(5060|5078|6500)[0-9]{12,13}$ What it does: ✅️Makes sure the card number starts with a valid Verve prefix ✅️Ensures the rest are numbers only ✅️Checks that the length is just right and blocks anything that looks suspicious 👀 It’s like building a mini-security gate with code. Instead of writing just a random function, I challenged myself to use Object-Oriented Programming which I’ve been learning recently. So I created a class, added properties, and built a validate() method inside it. Suddenly, my little validator felt more like a program and less like a quick hack. The cool part? Using OOP made it super easy to create multiple card objects: card1 → valid card2 → invalid Each one tested itself, like they had their own personalities. OOP really helps you write cleaner, more organized, and more scalable code. I finally get why people hype it so much. 😄 Honestly, this task made me appreciate how much detail goes into something as “simple” as validating a card number. #JavaScript #LearnToCode #Regex #OOP #CodingJourney #BackendDev

Flask vs FastAPI: A Comprehensive Performance Comparison - As experienced web developers and software engineers, we constantly seek the most efficient tools for our projects. When it comes to Python web frameworks for API development, Flask and FastAPI are two prominent contenders, each offering distinct advantages. This comprehensive comparison article dives deep into their core differences, exploring their respective features, syntax, and real-world performance benchmarks. We will analyze how each framework handles API requests, contrasting Flask's lightweight, unopinionated design with FastAPI's modern, high-performance approach built on asynchronous capabilities and Pydantic for data validation. Our discussion will extend beyond theoretical benchmarks, offering practical tips for implementation and delving into specific real-world examples where Flask's simplicity and vast ecosystem might be preferable, versus scenarios where FastAPI's speed, automatic documentation, and robust type checking provide an undeniable edge. We aim to provide a detailed Flask and FastAPI comparison that helps you understand their performance differences and make an informed decision when choosing between Flask and FastAPI for API development, ensuring your projects are built on the most suitable foundation for scalability and maintainability. Read the full article > https://lnkd.in/gQCc3m5R #iPixelInsights #WebDesignTips #DigitalMarketingStrategy #FrontendDevTalks #UIUXDesign #GoogleAdsHelp #TechForCreatives #SEOForBusiness #DesignVsDev #MarketingTechExplained

Most beginners start JavaScript… but don’t understand variables & data types deeply. They declare variables. Store values. Write basic code. It feels easy — until logic gets complex. Then the real problems start: Confusion in data handling. Unexpected bugs. Weak logic building. Difficulty scaling code. In 2026, JavaScript isn’t about syntax. It’s about building strong logic foundations. This is where it starts: • Understanding var, let, const clearly • Knowing different data types (string, number, boolean, object, array) • Storing and managing data efficiently • Writing clean and predictable logic • Avoiding common beginner mistakes Because strong logic doesn’t come from frameworks — it comes from mastering the basics. Curious — are your fundamentals strong or just “working somehow”? #JavaScript #WebDevelopment #Coding #Programming #FrontendDevelopment #LearnToCode #DeveloperLife #JSBasics

🔥 Master the art of coding loops in JavaScript! 🚀 Loops are a fundamental concept in programming that allow you to execute a block of code multiple times. They are essential for automating repetitive tasks and iterating over data structures. For developers, understanding loops is crucial for writing efficient and concise code. Whether you're working on data manipulation, user interfaces, or backend logic, loops help you process large amounts of data with ease. Here's a step-by-step breakdown: 1️⃣ Initialize a counter variable 2️⃣ Set the condition for the loop to continue 3️⃣ Execute the code block inside the loop 4️⃣ Update the counter variable at the end of each iteration Check out the code example below: ``` for (let i = 0; i < 5; i++) { console.log('Hello, loop ' + i); } ``` Pro Tip: Use caution with infinite loops! Always ensure your loop has a clear exit condition to avoid crashing your program. Common Mistake Alert: Forgetting to update the counter variable in a loop can lead to infinite loops. Always remember to increment or decrement the counter inside the loop. 🌟 Question for you: What creative project are you currently working on with loops in your code? Share below! 💡 🌐 View my full portfolio and more dev resources at tharindunipun.lk #JavaScript #CodingLoops #ProgrammingBasics #DevTips #LoopMastery #CodeNewbie #TechTalk #DeveloperCommunity #DigitalSkills

Most people building React frontends with Python backends overcomplicate the connection. React and FastAPI is honestly one of the cleanest full-stack combos right now. Here's why it works so well FastAPI gives you automatic docs at /docs the moment you define a route. No extra setup. Your React dev knows exactly what endpoints exist and what they return before you've even written the fetch call. Pydantic schemas on the FastAPI side act as a contract. If the backend returns a User object, you know exactly what fields are coming. Pair that with TypeScript interfaces on the React side and you've eliminated an entire class of runtime bugs. CORS setup is two lines. Async endpoints mean your API doesn't choke when React fires multiple requests simultaneously. Response times stay fast without extra infrastructure. The pattern that works in prod: FastAPI handles all data logic, auth, and business rules React owns the UI state and user interactions entirely They talk only through clean typed API boundaries No shared state nightmares. No tightly coupled mess. If you're coming from a Django or Express background and haven't tried this stack yet, it's worth a weekend project. The developer experience gap is noticeable. What's your go-to Python backend when building React apps? #React #FastAPI #Python #FullStackDevelopment #WebDevelopment