Implemented Stack using Queue in Python

🗓 Day 10 / 100 – #100DaysOfLeetCode 📌 Problem 3228: Maximum Number of Operations to Move Ones to the End The task was to determine the maximum number of operations needed to move all '1's in a binary string to the end, given specific operation rules. 🧠 My Approach: Traversed the string while keeping track of the total count of '1's seen so far. Whenever a '10' pattern appeared, added the current count of '1's to the total operations. This ensured that each move was counted optimally without unnecessary shifts or recomputation. ⏱ Time Complexity: O(n) 💾 Space Complexity: O(1) 💡 Key Learning: This problem reinforced the value of pattern-based logic and prefix counting — powerful techniques for problems involving strings or sequences. It also highlighted how thinking in terms of transitions (1→0) can simplify seemingly tricky problems. Ten days down, ninety to go 🚀 #100DaysOfLeetCode #LeetCodeChallenge #Python #ProblemSolving #Strings #LogicBuilding #DataStructures #Algorithms #DSA #CodingJourney #CompetitiveProgramming #SoftwareEngineering #LearningInPublic #DeveloperJourney #TechStudent #CodingCommunity #CareerGrowth #CodeEveryday #Optimization #KeepLearning #Programming

🔥 Day 24 String Patterns & Prefix Power 💪 Today’s DSA session was all about smart scanning and pattern precision decoding strings from both ends like a pro 🧠 🔹 LeetCode 1903 Largest Odd Number in a String We learned to scan from right to left to grab the largest possible odd substring mastering substring slicing and number logic in one go. A simple yet powerful trick in string + math hybrid problems ⚡ 🔹 LeetCode 14 Longest Common Prefix We revisited a classic finding the common thread across multiple strings! Perfect practice for pattern alignment and character-wise comparisons 🧩 💡 Strings may look simple but they hide some of the most elegant problem-solving patterns in all of coding. What’s your go-to trick when solving string questions slicing, pointers, or brute force? 👇 #Day24 #100DaysOfCode #LeetCode #StringProblems #CodingJourney #ProblemSolving #DSA #LearnToCode #TechCommunity #Python #Programming #CodingChallenge #DSA90WithSUUMIT #DSA90 #FullStack #Strings #DEV

🚀 Day 54 of #100DaysOfCode Solved LeetCode Problem 2011. Final Value of Variable After Performing Operations ✅ This problem tests simple yet essential programming logic — understanding how pre/post increment and decrement operations affect variable states. Given a list of operations like ["--X", "X++", "++X"], the goal is to compute the final value of X after applying all updates sequentially. 💡 Key Insight: Each operation (++X, X++) increases the value by 1, while (--X, X--) decreases it by 1. The implementation can be efficiently handled in O(n) time by iterating through the operations once. ⚙️ Result: Runtime: 0 ms ⚡ Beats 100% of Python submissions Memory Usage: 17.76 MB (Beats 60.70%) Another step forward in improving my algorithmic problem-solving and code optimization skills 💪 #LeetCode #Python #100DaysOfCode #CodingJourney #ProblemSolving #DailyPractice #TechLearning #MythylyCodes

🚀 Day 4 – LeetCode Problem Solving Journey 💻 Today’s challenge was “Merge Sorted Array” (LeetCode #88) — a classic array manipulation problem that helps improve understanding of two-pointer techniques and in-place merging. Problem: You are given two sorted arrays, nums1 and nums2, and the task is to merge them into a single sorted array, stored inside nums1. Example: Input: nums1 = [1,2,3,0,0,0], m = 3 nums2 = [2,5,6], n = 3 Output: [1,2,2,3,5,6] 🧠 Concept Used: Two-pointer approach starting from the end Comparison and in-place insertion Time Complexity: O(m + n) Space Complexity: O(1) Learning how to handle in-place data modification efficiently is a key step in mastering DSA! #LeetCode #Day4 #ProblemSolving #DSA #CodingJourney #100DaysOfCode #Python #Programming #DevelopersCommunity #SoftwareEngineering #LearningInPublic #CareerGrowth

🗓 Day 14 / 100 – #100DaysOfLeetCode 📌 Problem 1437: Check If All 1’s Are at Least K Places Away The goal was to determine whether every pair of consecutive 1s in the array is separated by at least k zeros. 🧠 My Approach: Traversed the array while tracking the index of the previous 1. On encountering a new 1, checked the distance from the last one. If the gap was smaller than k, the condition failed instantly. This single-pass logic keeps the solution efficient and clean. 💡 Key Learning: This problem reinforced the importance of index tracking and using simple arithmetic comparisons to validate structural constraints. It’s a great reminder that not all problems require heavy algorithms — sometimes, clarity and careful traversal are enough for an optimal solution. Small steps forward build strong reasoning over time 🚀 #100DaysOfLeetCode #LeetCodeChallenge #Python #ProblemSolving #LogicBuilding #Arrays #Algorithms #DataStructures #DSA #CompetitiveProgramming #CodingJourney #SoftwareEngineering #LearningInPublic #DeveloperJourney #TechStudent #CareerGrowth #CodeEveryday #CodingCommunity #KeepLearning #Programming #TechCareer

🚀 Day 41 of #100DaysOfDSA Solved LeetCode Problem #70 – Climbing Stairs 🪜✨ 📌 Problem Insight: You are climbing a staircase with n steps, and you can take either 1 step or 2 steps at a time. The task is to find the number of distinct ways to reach the top. A classic problem that beautifully introduces Dynamic Programming concepts! 💡 Key Learnings: Understood how this problem relates to the Fibonacci sequence. Practiced iterative DP optimization — using only two variables instead of an array. Learned how to recognize recurrence relations in real problems. Time complexity: O(n) Space complexity: O(1) 📌 Approach (short): Each step can be reached either from (n−1) or (n−2) → ways(n) = ways(n-1) + ways(n-2) 👉 Dynamic Programming problems show that thinking ahead pays off — one step at a time 🧠💪 #LeetCode #DSA #ProblemSolving #100DaysChallenge #Day41 #CodingJourney #Python #DynamicProgramming

🧠 Day 44 / 100 – Product of Array Except Self (LeetCode #238) Today’s challenge was all about computing an array where each element is the product of all numbers except itself — without using division. This one teaches prefix and suffix logic beautifully. The trick is to build two running products: One from the left (prefix) One from the right (suffix) Then combine both to get the final result. No division needed, no nested loops — just clean, efficient logic. 🔍 Key Learnings Use prefix and suffix multiplications for O(n) time complexity. Avoid division to handle zero cases efficiently. Think about how to reuse partial results rather than recomputing them. 💭 Thought of the Day Efficiency comes from rethinking the obvious. Instead of brute-forcing every combination, using prefix and suffix logic shows how planning ahead can simplify everything. Each day, I’m learning to design solutions, not just write them. 🔗 Problem Link: https://lnkd.in/gbGfa4dd #100DaysOfCode #Day44 #LeetCode #Python #Arrays #PrefixSum #ProblemSolving #Algorithms #DataStructures #EfficientCoding #CodeEveryday #LearningJourney #TechGrowth #CleanCode

🚀 Day 87/100 of the #100DaysOfCode Challenge! #Day87 of #100Dayscodingchallenge:Today's focus was on mastering control flow and precision with nested loops in Python. I tackled a series of classic pattern problems that are fantastic for understanding logical structuring and boundary conditions. The Challenge: Build hollow geometric patterns using only for loops and conditional statements. Patterns Solved: ✅ Hollow Pyramid: A test of symmetry and managing increasing spaces. ✅ Hollow Right-Angled Triangle: Focusing on the first and last elements of each row. ✅ Inverted Hollow Pyramid: The reverse logic of its upright counterpart. ✅ Hollow Diamond: Combining the logic of both the standard and inverted pyramids for a complex, symmetrical shape. These exercises are more than just printing stars; they're about sharpening problem-solving skills, breaking down complex problems into manageable steps, and writing efficient, clean code. It's a powerful reminder that solid fundamentals in loops and conditionals are the building blocks for more advanced algorithms. Check out the code snippet in the comments! 👇 #Nxtwave #ccbp #intensive #Python #Programming #CodingChallenge #Algorithms #ProblemSolving #SoftwareDevelopment #LearnToCode #CodeNewbie #Developer #ProgrammingPatterns

🗓 Day 4 / 100 – #100DaysOfLeetCode 📌 Problem 728: Self Dividing Numbers The task was to find all numbers in a given range that are self-dividing — i.e., numbers that are divisible by each of their digits and contain no zero. 🧠 My Approach: Iterated through the range of numbers. Checked each digit of a number to ensure: It’s non-zero. The original number is divisible by that digit. Collected all numbers that satisfied both conditions. ⏱ Time Complexity: O(n × d) — where d is the number of digits in each number. 💾 Space Complexity: O(1) 💡 Key Learning: This problem strengthened my understanding of digit-wise iteration and conditional logic — simple concepts that are essential for handling number-based and math-intensive problems efficiently. Small problems like these build the habit of writing clean, readable, and logical code — one step closer each day 🚀 #100DaysOfLeetCode #LeetCodeChallenge #Python #ProblemSolving #LogicBuilding #Programming #DataStructures #Algorithms #DSA #CodingJourney #CodingChallenge #CodeEveryday #LearningInPublic #CompetitiveProgramming #DeveloperJourney #TechStudent #CareerGrowth #CodingCommunity #KeepLearning

✅Day 83 of #100DaysOfLeetCode 1.📌Problem: Find the Pivot Integer Given a positive integer n, find the pivot integer 𝑥 such that the sum of all elements between 1 and 𝑥 inclusively equals the sum of all elements between 𝑥 and n inclusively. Return the pivot integer 𝑥. If no such integer exists, return -1. 2.🟢 Difficulty: Easy 3.📍Topic: Arithmetic & Basic Reasoning 4.🎯 Goal: Identify the integer x where the sum of numbers before and after (including) 𝑥z are equal for a given range.image.jpg 5.🧠Key idea: Approach 1: Find the total sum of numbers from 1 to n using 𝑛(𝑛+1). Incrementally compute the prefix sum from 1 up to 𝑖 and compare it with the suffix sum from 𝑖 to n. If prefix sum equals suffix sum for any i, that 𝑖 is the pivot integer; otherwise, return -1. #LeetCode #100DaysOfCode #CodingChallenge #Programming #DataStructures #Algorithms #CodingJourney #LearningJourney #GrowthMindset #ProblemSolving #DeveloperCommunity #Python #Java #SoftwareEngineering #TechCareersbest