How to Solve the 2011 LeetCode Challenge in Python

🚀 LeetCode #1526: Minimum Number of Increments on Subarrays to Form a Target Array Today I tackled an interesting Greedy Algorithm problem that really tests your ability to spot patterns and simplify complex logic. 🧩 Problem Brief: We start with an array of zeros and can increment any subarray by 1 in one operation. The goal is to form the target array using the minimum number of operations. 💡 Key Insight: Instead of simulating every operation, focus on how much each element increases compared to the previous one; each increase represents new operations needed. ⚙️ Formula: operations = target[0] + Σ(max(0, target[i] - target[i-1])) 🧠 Complexity: Time: O(n) Space: O(1) 🎯 Takeaway: Hard problems often become simple once you recognize the pattern behind the process. #LeetCode #Python #DSA #Coding #ProblemSolving #GreedyAlgorithm #LearningEveryday

LeetCode 90-Day Challenge – Day 78 Problem: Find Peak Element Difficulty: Medium Problem: We need to find a peak element in an array, an element that is strictly greater than its neighbors. If multiple peaks exist, returning the index of any one of them is valid. Conceptually, nums[-1] and nums[n] are considered negative infinity, so edge elements can also be peaks. The challenge is to achieve this in O(log n) time. Solution approach: This problem can be efficiently solved using binary search. At each step, we check the middle element and compare it with its right neighbor. If the middle element is smaller than the next one, it means the peak lies on the right half; otherwise, the peak is on the left half. By continuously narrowing down the range, we find a peak element in logarithmic time. #LeetCode #90DaysOfCode #Python #LinkedInChallenge #CodingJourney #ProblemSolving #LeetCodeChallenge

Day 31 / 100 – Add Strings (LeetCode #415) Today’s challenge was all about simulating manual addition without using any built-in integer conversions. Given two numbers as strings, the task was to return their sum — also as a string. This problem really emphasized the importance of breaking problems into small, logical steps rather than relying on shortcuts. 🔍 Key Learnings Recreated the digit-by-digit addition process using ASCII values. Practiced handling carry-over efficiently while iterating backward. Strengthened my understanding of string manipulation and arithmetic logic. 💭 Thought of the Day True problem-solving isn’t about using built-ins — it’s about understanding how things work underneath. Today reminded me that mastery grows when we rebuild the basics from scratch, not when we avoid them. 🔗 Problem Link: https://lnkd.in/gHMt9vj9 #100DaysOfCode #Day31 #LeetCode #Python #ProblemSolving #StringManipulation #Algorithms #DataStructures #CodingChallenge #CodeEveryday #TechGrowth #LearningJourney

🗓 Day 13 / 100 – #100DaysOfLeetCode 📌 Problem 1513: Number of Substrings With Only 1s The task was to count how many substrings in a binary string consist only of consecutive 1s. 🧠 My Approach: Identified continuous blocks of '1' in the string. For each block of length k, calculated the number of valid substrings using the formula: k × (k + 1) / 2 Summed these counts across all segments of consecutive 1s. This avoids checking all substrings individually and keeps the solution efficient and clean. 💡 Key Learning: This problem reinforces the value of recognizing sequences and using mathematical formulas to simplify substring counting. It’s a reminder that many problems can be solved much faster when we look for structure instead of brute force. One more problem, one more pattern learned 🚀 #100DaysOfLeetCode #LeetCodeChallenge #Python #ProblemSolving #Strings #Algorithms #MathInCoding #LogicBuilding #DataStructures #DSA #CompetitiveProgramming #CodingJourney #SoftwareEngineering #LearningInPublic #DeveloperJourney #TechStudent #CareerGrowth #CodeEveryday #CodingCommunity #KeepLearning

💡 Day 37 of 100 — Minimum Operations to Convert All Elements to Zero (#LeetCode 3542) Today’s problem was an interesting one short in code, but deeper in logic. It was one of those problems where the intuition slowly unfolds as you play with examples. 🧠 What I figured out This problem is all about monotonic stacks a pattern that helps you process elements in increasing or decreasing order efficiently. The key idea: Every time the current number is greater than what’s on top of the stack, it represents a new “operation” needed. By maintaining a non-decreasing stack, you avoid unnecessary repetitions and count exactly when new operations are required. 💻 My thought process At first, I tried to simulate each operation directly which got messy. Then I realized this could be solved cleanly using a stack that tracks when a new increase appears in the sequence. Every rise means one more operation, and when numbers fall, you just pop from the stack. 📊 Complexity: Time — O(n) Space — O(n) 💬 Reflection This one reminded me how often elegant ideas hide in short problems. It’s not about long code it’s about clarity of thought. Sometimes, a single stack can tell the whole story. #100DaysOfLeetCode #Day37 #LeetCodeJourney #Coding #ProblemSolving #Python #DSA

🔍 Day 44 DSA Challenge – Problem #33: Search in Rotated Sorted Array 📌 Problem Statement: Given a sorted array nums that may have been rotated at an unknown pivot, find the index of a target value. Return -1 if the target doesn’t exist. The solution must run in O(log n) time. ⚙️ How I Solved It: Applied a modified binary search: Identify which half (left or right) is sorted. Narrow the search to the half where the target could exist. Repeat until the target is found or search space is exhausted. 📊 Performance Stats: ⏱ Runtime: 0 ms (⚡ beats 100%) 💾 Memory: 12.65 MB (beats 42.49%) ✅ Testcases Passed: 196 / 196 🧠 Key Takeaway: Understanding array properties like rotation and leveraging binary search ensures optimal search performance in logarithmic time. #LeetCode #BinarySearch #RotatedArray #Problem33 #Python #DSA #100DaysOfCode #CodingJourney

#96day of #100DaysOfCode 🌱 LeetCode 109: Convert Sorted List to Binary Search Tree Today’s challenge was about building balance — literally! Given a sorted linked list, we need to convert it into a height-balanced BST 🌳 🧠 Key Idea: The middle element of the list becomes the root. Left half forms the left subtree, right half forms the right subtree. Use slow–fast pointers to find the middle efficiently. 📈 Complexity: Time: O(n log n) Space: O(log n) (recursion stack) 💬 Learning: Balance matters — in trees, in code, and in life 🌿 Sometimes, the middle point creates the strongest foundation. #LeetCode #DSA #BinarySearchTree #LinkedList #CodingChallenge #Python #Algorithm #LeetCodeDaily #100DaysOfCode

💻 Day 59 of #100DaysOfCode Solved LeetCode Problem 1716: Calculate Money in Leetcode Bank (Easy) 🏦 This problem involves a weekly incremental saving pattern — each Monday starts with a higher base deposit, and daily savings increase sequentially throughout the week. 🔹 Concepts Applied: Arithmetic Progression (AP) Modular division for week/day tracking Mathematical optimization (O(1) solution) ✅ Runtime: 0 ms — Beats 100% ✅ Memory: 17.94 MB This problem highlights how mathematical patterns can simplify what initially seems iterative into an elegant constant-time formula. #LeetCode #CodingJourney #Python #ProblemSolving #100DaysOfCode #MathematicsInProgramming #CodeOptimization #LearningEveryday