Array Basics: Indexing & Operations | DSA Foundations

🚀 Just Published: Array Patterns – Max, Min & Frequency | DSA Foundations Today I uploaded a new video on my YouTube channel JDCodebase where I explain one of the most important thinking concepts in Data Structures — Array Patterns. In this video, I cover: • How to track Maximum and Minimum efficiently • How Frequency counting works using objects (hashmap concept) • Introduction to Prefix Sum • How to find the Second Largest element without sorting • Time & Space Complexity explanation Instead of memorizing problems, I focused on understanding patterns that can solve many questions. These concepts are used in problems like: Duplicates, Unique Elements, Majority Element, and many LeetCode questions. If you are starting DSA or want to strengthen your fundamentals, this will help you build strong logic. 🎥 Video link in the comments. I’m building a complete DSA Foundations Series on JDCodebase — step by step, from zero. #DSA #DataStructures #JavaScript #Coding #Programming #LearnToCode #SoftwareDevelopment #TechLearning #JDCodebase

🚀 𝗦𝗵𝗶𝗽𝗽𝗲𝗱 𝗠𝘆 𝗙𝗶𝗿𝘀𝘁 𝗣𝘆𝘁𝗵𝗼𝗻 𝗣𝗮𝗰𝗸𝗮𝗴𝗲 𝗼𝗻 𝗣𝘆𝗣𝗜… 𝗮𝗻𝗱 𝗦𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗪𝗶𝗹𝗱 𝗛𝗮𝗽𝗽𝗲𝗻𝗲𝗱 📝✨ I thought this would be a simple “publish & move on” project. Turns out… it became one of the biggest learning curves of my dev journey. 👀🔥 💥 Broken builds 💥 Weird packaging errors 💥 Unexpected CLI bugs And a lot of “why is this even failing?” moments. But today… after all the chaos: 𝗧𝗼𝗱𝗮𝘆, 𝗜 𝗼𝗳𝗳𝗶𝗰𝗶𝗮𝗹𝗹𝘆 𝘀𝗵𝗶𝗽𝗽𝗲𝗱 𝗧𝗲𝘅𝘁𝗻𝗼𝘁𝗲𝘀 🐍 A tiny CLI tool. One command. Surprisingly useful. 💡 The biggest win? Not just shipping… Learning how packaging works, debugging real-world errors, and shipping something people can actually use. 👉 Read the full story: 🌐 https://lnkd.in/db7a5neY 𝗧𝗿𝘆 𝗜𝘁: 🐍 PyPI → https://lnkd.in/dpzhWn_A 💻 GitHub → https://lnkd.in/dS9W57bE 🔁 Share to help others ❤️ Like if you found it useful 📥 Save for your next project 👥 Tag someone who needs this #python #pythonprogramming #KnowledgeSharing

I am happy to share AUTOMATIC-SCHEDULER, a Python-based academic scheduling system that I developed to generate optimized weekly class schedules using Google OR-Tools CP-SAT (Constraint Programming - Satisfiability). The project was designed to support academic departments in automating timetable preparation for faculty, rooms, sections, and course offerings. By using structured CSV input files and constraint-based optimization, the system can generate feasible schedules while enforcing practical rules such as avoiding faculty, room, and section conflicts, respecting blocked times, protecting lunch breaks, matching room type and capacity requirements, and preventing laboratory classes from being scheduled on Fridays. The application was built with Python, Tkinter, and Google OR-Tools CP-SAT, combining a desktop interface with a powerful optimization engine. It also includes timetable viewing, validation tools, diagnostics for unscheduled offerings, CSV export, and sample input generation. This project demonstrates how programming and optimization can be applied to improve academic scheduling processes and reduce the complexity of manual timetable preparation that usually takes 3 days to a week into just a matter of minutes. #Python #GoogleORTools #AcademicScheduling #Optimization #Tkinter #OperationsResearch #Automation #SoftwareDevelopment GitHub: https://lnkd.in/gj5nmU_m

🚀 MY DSA LEARNING LOG "Not a 100 days or 365 days challenge, just about my consistency in problem solving." Today I solved Trapping Rain Water – LeetCode 42 (Hard). ⚡ Approach 1: Prefix & Suffix Arrays ⏱️ Time: O(n) | 📦 Space: O(n) ⚡ Approach 2: Two Pointers (Optimized) ⏱️ Time: O(n) | 📦 Space: O(1) ⚡ Runtime: 2 ms ✨ Key Takeaway: Optimized space by moving from extra arrays to a two-pointer approach based on min(leftMax, rightMax). 🔗 GitHub: https://lnkd.in/g9Mgu4eT #DSA #LeetCode #ProblemSolving #Java #CodingJourney

LeetCode Win Today 🚀 Solved “Apply Operations to an Array” with a simple two-pass approach. ⚡ Runtime: 0 ms (Beats 100%) Approach: 🔹 Pass 1: Traverse the array If nums[j] == nums[j-1] → Double the left element → Set the right element to 0 🔹 Pass 2: Move all zeros to the end using a two-pointer technique. 💡 Key Insight: Instead of solving everything in one complex loop, split the problem into two clean steps. 📊 Complexity: • Time → O(n) • Space → O(1) (in-place) Consistent practice. Clear thinking. Better code every day. 🧠⚡ #leetcode #dsa #algorithms #datastructures #coding #programming #python #softwareengineering #computerscience #tech #codinglife #problem-solving #100daysofcode #developers #codingjourney #techcommunity 🚀

🚀 900 LeetCode Questions Solved 🚀 Today I hit a milestone I once thought was impossible — 900 problems on LeetCode. This journey wasn’t about streaks or badges. It was about: Building disciplined problem-solving habits Strengthening data structures & algorithms fundamentals Learning to stay consistent even on low-motivation days Turning frustration into growth From struggling with basic recursion to confidently tackling dynamic programming and graph problems — every question added a layer of clarity. The biggest lesson? 👉 Consistency compounds. 👉 Small daily improvements beat occasional bursts of effort. Now aiming for 1000 — but more importantly, aiming to become a better thinker and engineer every single day. If you're on the DSA grind, keep going. The breakthrough is closer than you think. 💪 #LeetCode #DSA #CodingJourney #SoftwareEngineering #ProblemSolving #Consistency #TechGrowth #600DaysOfCode #Developers #python #Programming

Most people don’t struggle with Dynamic Programming because it’s hard. They struggle because they were never taught how to think in DP. If DP still feels random to you on LeetCode or CodeForces , this is exactly what’s missing. Dynamic Programming is not about memorizing patterns. It’s about understanding states, transitions, and building solutions step by step. This structured series is designed for anyone serious about DSA and problem solving. What you’ll master: • How to think in states and transitions • From basic recursion to advanced DP patterns • DP on arrays, strings, grids, and trees • Optimization techniques (space and time) • Combining DP with Greedy and Binary Search • Solving hard problems with clarity, not guesswork Whether you're preparing for interviews or aiming to get better at contests, this covers both. No random questions. No gaps. Just a clear roadmap to mastering DP the right way. If DP has ever felt confusing, this will change how you approach problems. Playlist: https://lnkd.in/gaBaDQZN Channel: https://lnkd.in/gTRG5v9M #dsa #dynamicprogramming #leetcode #codeforces #coding #interviewprep

Day 41 on LeetCode — Count the Number of Consistent Strings ✅ Today’s problem focused on hash maps and efficient character validation in strings. 🔹 Approach Used in My Solution The idea was to first store all allowed characters in a hash map for quick lookup. After that, I iterated through each word and checked whether every character exists in the allowed set. Key steps in the logic: • Store characters from the allowed string in an unordered_map • Traverse each word in the words array • Check every character of the word against the map • If a character is not allowed, mark the word as invalid • Count only the words where all characters are valid This approach keeps the lookup efficient and the implementation straightforward. ⚡ Complexity: • Time Complexity: O(n × m) (n = number of words, m = average length of each word) • Space Complexity: O(1) (since the character set is limited) 💡 Key Takeaways: • Practiced using hash maps for fast membership checks • Strengthened understanding of string traversal and validation • Reinforced building clean and readable solutions for character-based problems #LeetCode #DSA #Algorithms #DataStructures #HashMap #Strings #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

Unpopular opinion: C and JavaScript are basically the same. 😅 ...At least, that’s what I thought when I saw my first line of C code. Same curly braces. Same semicolons. Same for loops. But after my first week in Harvard’s CS50, I’ve realized the "grammar" is where the similarities end. Moving from a high-level language to C is like learning to build a car engine from scratch instead of just driving it. You can't ignore the details, and honestly? I’m loving the challenge. I’m thrilled to share that I just wrapped up my first three projects (Scratch, Hello, and Mario) with 100% scores. As you can see in the screenshot, there’s nothing more satisfying than a sea of green checkmarks! Key Milestones: • 🐱 Scratch: Visualizing logic and control flow. • 👋 "Me": My first true steps into writing and compiling C. • 🧱 Mario (Less): Designing a custom print_row function to handle nested loops and pyramid logic. To the developers in my network: What was the one concept in C that finally made "memory management" or "pointers" click for you? I’d love some tips as I head into the deeper waters of Week 2! #CS50 #Programming #LearningToCode #CProgramming #SoftwareEngineering #TechJourney #HarvardX