"Removing Duplicates from Sorted Linked List in O(n) Time"

🚀 DSA Progress – Day 103 ✅ Problem #472: Concatenated Words 🧠 Difficulty: Hard | Topics: String, DFS, Dynamic Programming, Memoization 🔍 Approach: Implemented a DFS + Memoization strategy to identify all words that can be formed by concatenating two or more other words from the given list. Step 1 (Preparation): Store all words in a set for O(1) lookups. Step 2 (Recursive Checking): For each word, split it into all possible prefix–suffix pairs. If the prefix exists in the set, check if the suffix is either directly in the set or can be recursively formed using other words. Step 3 (Memoization): Use a dictionary (mp) to cache previously computed results to avoid redundant recursive calls. Step 4 (Result Collection): If a word can be formed by concatenation, add it to the result list. 🕒 Time Complexity: O(n × L²) n = number of words L = maximum word length Each word may be split at every position. 💾 Space Complexity: O(n + L) For the word set, recursion stack, and memoization dictionary. 📁 File: https://lnkd.in/gHA3vtD5 📚 Repo: https://lnkd.in/g8Cn-EwH 💡 Learned: This problem taught me how to efficiently combine recursion and memoization for overlapping subproblems. It felt like solving an advanced version of the Word Break problem but applied across an entire list of words. Breaking down the logic into small, reusable parts (isConcat + main loop) made the implementation clean and scalable. ✅ Day 103 complete — pieced together words like a linguistic puzzle master 🧩✨ Every big problem is just smaller words glued smartly together! 💬🔠 #LeetCode #DSA #Python #Recursion #DynamicProgramming #Strings #Memoization #WordProblems #100DaysOfCode #DailyCoding #InterviewPrep #GitHubJourney

Stop trying to memorize code. Start trying to understand it. When I first started coding, I thought mastery meant memorizing everything. Every syntax. Every function. Every little detail. So I’d spend hours staring at tutorials, trying to cram code into my head, line by line, hoping it would stick. But the truth? It didn’t. The moment I opened my notebook or editor, my mind off🥲 Then one day, it clicked. The real goal isn’t to remember the code. It’s to understand what the code is doing and why it works that way. Once I shifted my focus from memorizing to understanding, everything changed. I stopped seeing code as random lines and started seeing it as logic, flow, and purpose. And guess what? The more I understood the why, the easier the how became. So if you’re just starting out, don’t pressure yourself to know every syntax or library by heart. Instead, ask questions like: 👉 “What is this function trying to achieve?” 👉 “Why is this logic necessary here?” Understanding first makes memorizing natural not forced Your code doesn’t have to be perfect. Your journey doesn’t have to be fast. Just make sure every line you write makes sense to you. Because that’s how true mastery begins💪 #CodingJourney #LearnToCode #DataScience #MachineLearning #Python #GrowthMindset #TechLife

Patterns I hear it repeatedly, "Pick out the patterns." When solving coding problems this definitely rings true. Honestly it rings true in the world of nursing where I was originally from as well. When you sat down at the computer for your nursing license test it did not matter how many questions you practiced and how much of each medical problem you knew. That is not what got me or anyone else through. You have to realize the PATTERN. It was not always what they were asking, but how they were asking it. What details are they purposefully putting in the question or purposefully leaving out. Thinking out the problem, before looking at any answers provided to choose from. Very thankful for other coders who share what they have learned and what worked for them. I hope this post helps someone along their journey like it did me.

I have realized that good documentation and clear naming conventions often matter as much as the code itself. When we’re learning or working on fast-paced projects, it’s easy to skip these — but they quietly shape how teams collaborate and how future developers (including our future selves 😅) understand what’s going on. 💡 Why they matter: ✅ They make handovers smoother and reduce confusion. ✅ They help debug faster when something breaks. ✅ They turn messy projects into scalable, professional ones. Clear names and small comments can save hours of digging later. I’ve started following a simple rule: ✍️ “Code for humans first, machines second.” I’d love to hear from others — how do you handle documentation and naming in your projects? Any tips or conventions that work best for your team? 💬 #DataEngineering #LearningJourney #CareerGrowth #SQL #Python #SoftwareBestPractices

🚀 Day 41 / 100 — #100DaysOfLeetCode 💡 (2011) Final Value of Variable After Performing Operations (Easy) A nice warm-up problem that tests simple logic and string traversal. The challenge involves simulating increment and decrement operations and returning the final value. 🧩 Problem Overview You’re given an array of strings operations, where each string represents an operation on an integer X (initially 0). Each operation can be one of the following: "++X" or "X++" → increment X by 1 "--X" or "X--" → decrement X by 1 You must return the final value of X after performing all operations. ⚙️ Approach — Simple Iteration Used a counter initialized at 0 and iterated through the operations list. If an operation contains '-', decrement the counter. Otherwise, increment it. 📈 Complexities Time Complexity: O(n) — iterate once through all operations. Space Complexity: O(1) — only a counter variable used. ✅ Key Insight Even simple string-based problems can reinforce pattern recognition — identifying the core action (+ or -) and applying it efficiently. ✨ Takeaway Not every problem needs heavy logic. Sometimes, the beauty lies in simplicity — clean, readable, and optimal. #LeetCode #100DaysOfCode #Python #StringManipulation #ProblemSolving #Algorithms #CodingJourney #DeveloperGrowth

🚀 Day 31 of #100DaysOfCode — LeetCode + HackerRank Edition! Today’s challenge was all about tracking structure and resilience — decoding the longest valid parentheses substring in a given string. 🔗 Problem: longestValidParentheses(s) (LeetCode) 📌 Challenge: Given a string of '(' and ')', find the length of the longest well-formed (valid) parentheses substring. 🔍 Approach: → Used a stack to track indices of unmatched '(' characters → Introduced a base index to reset when encountering unmatched ')' → On each valid match, calculated the distance to the last unmatched index → Continuously updated the maximum valid length found so far 💡 What made it click: → Realized that tracking indices, not just characters, is key to measuring valid spans → Using stack[-1] after a pop gives the start of the current valid substring → Resetting with a base index ensures recovery after mismatches 📚 What I learned: ✅ Stack-based tracking is powerful for nested structures ✅ Index math reveals patterns that raw character matching misses ✅ Defensive coding (checking if stack is empty) prevents crashes and improves robustness ✅ Visual walkthroughs and guided hints make debugging intuitive and rewarding Have you tackled longestValidParentheses before? Did you go with dynamic programming, two-pass scanning, or stack-based logic like I did? Let’s swap strategies 💬 #Day30 #LeetCode #StackAlgorithms #ParenthesesMatching #Python #ProblemSolving #CleanCode #CodeEveryDay #LearnToCode #CodeNewbie #SoftwareEngineering #TechJourney #100DaysOfCode

🚀 Day 52 of #100DaysOfCode — Leetcode + HackerRank Edition! Today’s challenge was all about bringing order to chaos — merging overlapping intervals into clean, non-overlapping ranges 🗂️✨ 🧩 def merge(self, intervals: List[List[int]]) -> List[List[int]]: — Combine overlapping intervals into a simplified list 📌 Challenge: → Implement a function to merge overlapping intervals → Avoid brute-force approaches that check every pair → Optimize for clarity and performance 🔍 Approach: → First, sort intervals by their start time → Keep track of the last merged interval (prev[0]) → If the current interval overlaps, extend the end boundary → Otherwise, add it as a new interval 💡 What made it click: → Realized sorting upfront makes merging straightforward → Saw how prev[1] = max(prev[1], interval[i][1]) elegantly handles overlaps → Practiced dry runs with examples like: [[1,3],[2,6],[8,10],[15,18]] → [[1,6],[8,10],[15,18]] 📚 What I learned: ✅ Why sorting is the key to simplifying interval problems ✅ How greedy merging avoids unnecessary comparisons ✅ How to handle edge cases like single intervals or fully nested ranges Ever felt like your calendar was a mess of overlapping meetings? This algorithm is the perfect organizer 🗓️😎 Let’s swap dry runs, edge cases, and interval insights 💬 #Day51 #Leetcode #Python #MergeIntervals #GreedyAlgorithm #DryRun #LearnInPublic #CodeNewbie #TechJourney #100DaysOfCode #DSA

"Day 4 was a masterclass in efficiency! I condensed three days of focused learning into one morning block, and the results are significant: 1. DSA Pattern Confirmation: The morning block focused on confirming the Two-Pointer technique by successfully implementing solutions for three key problems: #26 (Remove Duplicates): Implemented the standard Overwrite Pointer. #27 (Remove Element): Implemented the efficient Swap-to-End technique. #80 (Remove Duplicates II): Implemented the advanced Look-Back Pointer, confirming the ability to handle complex constraints. This work locks in the core O(n) time / O(1) auxiliary space rule for array manipulation, establishing a solid foundation for future algorithmic challenges. 2. Project Pivot: Architecture and Git Flow 1. The focus immediately shifted to application architecture setup: I successfully defined, implemented, and verified the foundational User class in Python. This essential data model is the first structural component for the future Flask backend. 2. Crucially, I initiated my first professional Git feature branch (feature/oop-model). All new project architecture code is now separated from the main branch, ensuring a clean, professional, and stable development history. The project foundation is now secure, and the next step is integrating this model into the application's structure. #DSA #Python #OOP #GitFlow #SoftwareEngineering #ProjectDevelopment"

Excited to share my Python-based Library Management System, a simple yet efficient project designed to provide quick access to book details and improve basic library operations. 🔹 🎯 Objective: To build a console-based system that displays book information such as name, author, publishing year, price, and a short description — helping users easily browse through available books. 🧩 Key Features: 🔹 Interactive menu-driven interface for smooth user experience 🔹 Dynamic book lookup using user input 🔹 Displays detailed book information — author, year, price, and synopsis 🔹 Includes error handling for invalid inputs 🔹 Option to continue or exit the system anytime ⚙️ Technologies Used: Python (Core Programming, Conditional Statements, Functions, Loops) Text-based Interface for simple user interaction 📘 Project Highlights: 🔹 Reinforced concepts of function-based modular programming 🔹 Improved understanding of user input handling and data structuring 🔹 Focused on writing clean, reusable, and readable code 💡 This project was a great way to strengthen my Python fundamentals while building something practical and interactive. It reflects my interest in combining logic, structure, and creativity to develop functional solutions. 🙏 Special Thanks: To SkillCircle™ and Ms. Sheetal Gupta for continuous guidance and mentorship throughout this analytical journey. I’d love to hear your feedback! SkillCircle™ Sheetal Gupta Shivam Ahuja #Python #Programming #ProjectShowcase #LibraryManagementSystem #SoftwareDevelopment #Coding #PythonProjects #LearningByDoing