Mastering Heap Sort Algorithm in JavaScript for Efficient Data Sorting

🚀 LeetCode Problem Solved - Best Time to Buy and Sell Stock Today I solved the Best Time to Buy and Sell Stock problem on LeetCode using JavaScript with an optimized single-pass approach. 📊 Approach The goal is to determine the maximum profit from buying and selling a stock given its daily prices. The key idea is to: • Track the minimum price encountered so far • Calculate the potential profit for each day • Update the maximum profit whenever a higher profit is found This allows us to compute the result in one pass through the array. ⚡ Complexity 🔹 Time Complexity: O(n) – Traverse the prices array once 🔹 Space Complexity: O(1) – No extra data structures used ✅ Result ✔️ All test cases passed 📦 Constant space complexity Problems like this reinforce the importance of array traversal, state tracking, and optimizing brute-force solutions into efficient linear algorithms. Consistent practice with these problems strengthens DSA fundamentals and problem-solving skills for coding interviews. #leetcode #javascript #dsa #algorithms #codingpractice #softwareengineering #webdevelopment

🚀 Just shipped a PDF text and image extraction tool. I built a full stack system that converts PDFs into structured outputs you can actually work with. The goal: make it simple to extract both text and visual content from large documents to feed your LLM easily. What it does 📄 Extracts text from PDFs and converts it into clean Markdown (headers, paragraphs, tables) 🖼 Detects and exports figures and tables as separate images 📦 Supports batch uploads with a live progress tracker ⬇️ One-click Download All to export everything as a ZIP Tech stack 🖥 Frontend Next.js 14 (App Router), TypeScript, React, Tailwind — deployed on Vercel 🐍 Backend Python + Flask with a sequential job queue for reliable multi-file processing — deployed on Hugging Face Spaces 🔗 Architecture Next.js API proxy routes backend calls and keeps the HF Space private and secure 📑 PDF processing PyMuPDF4LLM for text extraction + DocLayout-YOLO for layout detection Challenges I ran into 🧩 Tables and figures split across pages → built logic to detect bounding boxes across pages and stitch them into a single image 📝 Pairing images with their captions → added spatial matching between figures and nearby caption blocks ⚙️ Handling multi-file uploads safely → implemented a sequential background queue 🎥You can try a live demo here : https://lnkd.in/dGhQwa6N #DataEngineering #Python #NextJS #PDFProcessing #DataExtraction #FullStackDevelopment #BuildInPublic

🚀 𝗗𝗮𝘆 𝟮𝟮/𝟯𝟬 – 𝟯𝟬 𝗗𝗮𝘆𝘀 𝗼𝗳 𝗣𝘆𝘁𝗵𝗼𝗻 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 Continuing my journey of building one Python project every day to improve consistency and real-world problem-solving. Today’s focus: **Desktop Application Development** 🧠 𝗣𝗿𝗼𝗷𝗲𝗰𝘁: 𝗚𝗼𝗼𝗴𝗹𝗲 𝗧𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗼𝗿 (Tkinter App) Built a simple and functional **Google Translator desktop application** using Python and Tkinter. This project helped me understand how to integrate APIs with a GUI and handle real-time user input. Also we can Translate any language into a different one. ✨ 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀: • Translate text between multiple languages 🌍 • User-friendly dark-themed interface 🎨 • Source & destination language selection 🔁 • Real-time translation on button click ⚡ • Clean and structured layout using Tkinter 💡 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝗨𝘀𝗲𝗱: • Tkinter for GUI development • ttk widgets (Combobox, Buttons) • API integration for translation • Event handling (`command` functions) • Text widget input/output handling 🔗 𝗚𝗶𝘁𝗛𝘂𝗯: https://lnkd.in/ddwCDU-G A practical project that combines UI design with real-world functionality — making learning both fun and useful. Building discipline through code — one project at a time. Follow along as I complete 30 Python projects in 30 days 🚀 #Python #BuildInPublic #DeveloperJourney #30DaysOfCode #PythonProjects #Tkinter #GUI #Coding #Learning

Excited to share my latest project: AI-Powered Website Generator I built a simple web application that can generate a basic responsive website from a natural language description. - Technologies Used: • Python • FastAPI • HTML / CSS / JavaScript - Features: • Enter a website description (prompt) • Automatic website generation • Live preview of generated site • Download generated HTML file This project helped me practice backend development with FastAPI and integrating frontend with APIs. 🔗 GitHub Project: I would appreciate any feedback! #Python #FastAPI #WebDevelopment #MachineLearning #Projects #AI

🚀 Excited to share my project CodeEZ! CodeEZ is an interactive platform for Algorithm Simulation and Code Visualization designed to make learning algorithms more intuitive and practical. The platform currently includes 32 algorithms across categories such as sorting, searching, greedy algorithms, dynamic programming, DFS, BFS, tree algorithms, graph algorithms, and heuristic approaches. Instead of only reading theory, CodeEZ allows users to see how algorithms work step by step while the code executes in sync with the visualization. 🎥 In the attached demo video, you can see how algorithms are simulated and executed interactively. ✨ Algorithm Visualization Features • Layman-friendly explanation of each algorithm • Detailed description and working principle • Source code implementation • Code simulation synchronized with visualization • Line-by-line code execution tracking • Speed controller to adjust execution speed • Automatic input generation / input change for experimentation 💻 Online Code Editor Users can write and execute code directly in the browser. Supported Languages: • Java • C# • C++ • C • JavaScript 🔐 Authentication • Secure login and authorization using NextAuth 🛠 Tech Stack • Next.js • Tailwind CSS • MongoDB & Mongoose • D3.js for algorithm visualization • Monaco Editor for code editing • Piston Engine for online compilation & execution 🔗 GitHub Repository https://lnkd.in/dSehMQCa Building CodeEZ allowed me to combine Data Structures & Algorithms with modern full-stack development, creating a platform that helps visualize and understand complex algorithmic concepts more effectively. I would love to hear your feedback! #Algorithms #ComputerScience #FullStackDevelopment #NextJS #JavaScript #WebDevelopment #Projects

🚀 LeetCode Problem Solved – Reverse String Solved the Reverse String problem on LeetCode using JavaScript with an optimized in-place approach. ✅ Key Idea: Reverse the string by swapping characters from the start and end of the same array, modifying it directly without creating any extra array. 🔹 Time Complexity: O(n) 🔹 Space Complexity: O(1) – No extra space used (in-place modification) 💡 Approach: • Use a two-pointer technique • One pointer starts from the beginning of the array • Another pointer starts from the end • Swap characters and move both pointers toward the center until they meet 📊 Result ✔️ All test cases passed ⚡ Runtime: 0 ms 📦 Space Complexity: O(1) Consistently practicing problems like this helps strengthen Data Structures & Algorithms fundamentals and improves problem-solving skills for coding interviews. #leetcode #javascript #dsa #twopointers #programming #codingpractice #softwareengineering

Built a Calculator… but with a twist. Instead of using built-in evaluation functions, I challenged myself to implement a calculator using **core Data Structures & Algorithms concepts**. Used **Stack-based evaluation** Parsed expressions manually Applied **infix to postfix conversion** logic Focused on clean logic over shortcuts This project helped me strengthen my understanding of how real-world systems handle expressions internally — something we often take for granted. Key takeaway: Sometimes, building "simple" things from scratch teaches you more than complex frameworks. As a MERN developer, I’m trying to go deeper into **DSA + system-level thinking**, not just UI. Would love your feedback or suggestions to improve this further! #DSA #JavaScript #MERN #Coding #SoftwareDevelopment #LearningInPublic

🚀 Ultima-DL - Built with Vibe Coding I needed a powerful media downloader for personal use, so instead of searching for tools, I decided to vibe code one with AI assistance. The result is Ultima-DL, a lightweight media downloader designed with a clean architecture and fast extraction pipeline. ⚙️ Tech Stack Python + Flask backend Vanilla HTML / CSS / JavaScript frontend yt-dlp for media extraction FFmpeg for merging high-resolution video and audio streams Tkinter for native folder selection What Makes It Interesting • No API required – the system extracts available formats directly from the video page using yt-dlp • Supports Standard, Pro (4K), and Audio-only downloads • Automatically merges adaptive streams using FFmpeg • Fast playlist extraction using lightweight metadata mode • Real-time progress tracking using Server-Sent Events • Temporary download pipeline with automatic cleanup Because the app does not rely on external APIs, it avoids API keys, quotas, and rate limits. Instead, it reads the same streaming data that browsers use to play videos. GitHub Repo: https://lnkd.in/d6_xeAtM #python #vibeCode #OpenSource

🚀 Built Prompt2App – One Prompt to Full-Stack Reality ⚡️ I engineered Prompt2App to bridge the gap between a simple idea and a working prototype. It’s a system designed to automate the entire scaffolding process, from high-level planning to multi-file code generation. The Architecture & Features: 🤖 Agentic Flow: Multi-agent orchestration (Planner + Coder) for structured, high-fidelity code. 🐍 High-Perf Backend: FastAPI (Python) with asynchronous API handling. 🦙 Local Inference: Integrated Ollama (Llama 3.2) for zero-cost, private LLM execution. 🛠 Resilient Parsing: Custom heuristics to handle non-deterministic LLM outputs and "messy" JSON. Once the prompt is processed, Prompt2App instantly generates: A reactive React + Tailwind Frontend. A RESTful FastAPI Backend with CRUD logic. Persistent data handling via JSON/File-system. #GenAI #SoftwareEngineering #Python #FastAPI #LLMOps

🕸️ I chose Sync API over Async for web scraping—and I don’t regret it. While building a Playwright scraper, I deliberately avoided async. Here’s why 👇 🔹 Why Sync API worked better for me • Linear, predictable execution (open → extract → store) • Easier debugging without async state issues • Faster iteration cycles during development • Fewer race conditions to worry about 💡 In my case: scraping hundreds of pages sequentially worked reliably—without needing concurrency. 🔹 Where Async does make sense • Large-scale scraping (thousands of requests) • Parallel pipelines and distributed systems • Async-first ecosystems ⚖️ Key insight: • Most scraping problems are I/O-bound—but not always concurrency-bound. • Adding async too early can increase complexity faster than it improves performance. 👀 Question: Have you actually seen real performance gains with async scraping—or just added complexity? #WebScraping #Playwright #Python #Automation #AsyncProgramming #SoftwareEngineering #DataEngineering