Polymorphism in Python: Flexible Code

Solved the Largest Number from Array problem using a greedy approach with custom sorting in Python. Key insight: compare a+b vs b+a instead of normal numeric sorting. Time Complexity: O(n log n). Strengthening my understanding of comparators, string manipulation, and algorithmic thinking through consistent practice. #geekstreak60 #npci #DSA #Python #ProblemSolving #GreedyAlgorithm #CodingPractice #AlgorithmicThinking

Solved the Largest Number from Array problem using a greedy approach with custom sorting in Python. Key insight: compare a+b vs b+a instead of normal numeric sorting. Time Complexity: O(n log n). Strengthening my understanding of comparators, string manipulation, and algorithmic thinking through consistent practice. #geekstreak60 #npci #DSA #Python #ProblemSolving #GreedyAlgorithm #CodingPractice #AlgorithmicThinking

LeetCode #105 – Construct Binary Tree from Preorder and Inorder Traversal | Python Implementation I implemented a recursive divide-and-conquer approach that exploits traversal properties to rebuild the tree. Core Insight: Preorder gives root order, inorder gives left/right boundaries. Their intersection uniquely determines tree structure. Each recursive call isolates the correct subsequences for subtree reconstruction. Time: O(n²) due to slicing and index lookup | Space: O(n) recursion depth + slices #LeetCode #DataStructures #Python #BinaryTree #DivideAndConquer #TreeReconstruction #CodingInterview #SoftwareEngineering

This problem explores how list comprehensions can both filter and transform data in a single line. The condition selects specific elements from the list, and the expression then applies an operation to those selected values. Understanding this helps write cleaner and more Pythonic code. THE ANSWER IS; (B) #Python #ListComprehension #PythonChallenge #LearningInPublic #CodingJourney

LeetCode #230 – Kth Smallest Element in a BST | Python Implementation I implemented an iterative inorder traversal using a stack to find the kth smallest element without building the entire sorted list. Core Insight: Iterative inorder traversal with early termination avoids O(n) space for storing all values. The stack simulates recursion while the counter enables stopping exactly at k. Time: O(h + k) where h = tree height | Space: O(h) for stack #LeetCode #DataStructures #Python #BinarySearchTree #InorderTraversal #Stack #CodingInterview #SoftwareEngineering

Can you predict the final value of x? This example shows how try, except, continue, and break affect the execution flow inside a Python loop. #Python #PythonProgramming #Coding #LearnPython

Day 37 of #100DaysOfCode 🚀 Built a Sorting Algorithm Visualizer using Python and Tkinter. It visually demonstrates how Bubble Sort works by animating the comparisons and swaps step by step. A fun way to understand algorithmsms, sometimes seeing the logic move makes learning much clearer. #Python #DSA #Algorithms #Tkinter #LearningInPublic #100DaysOfCoding

In this problem, the variable inside the function is local, even though it has the same name as the global variable. Updating x inside the function does not affect the global x. This shows how Python handles variable scope and shadowing. Understanding this avoids many hidden bugs in real projects. THE AMSWER IS : B (10) #Python #Scope #Functions #AdvancedPython #LearningInPublic

Longest Common Span with Equal Sum in Two Binary Arrays: Reduced the problem using a difference array + prefix sum + hashmap, converting it into a longest zero-sum subarray pattern. Time Complexity: O(n) Small optimizations. Stronger fundamentals. Consistency compounds. #geekstreak60 #npci #DataStructures #Algorithms #ProblemSolving #Python #CodingJourney

LeetCode #104 – Maximum Depth of Binary Tree | Python Implementation I implemented a recursive DFS approach that calculates tree depth by taking the maximum of left and right subtree depths plus one for the current node. Core Insight: Depth calculation decomposes naturally into subproblems. Each node's depth is determined by its deepest child, making recursion the cleanest solution with minimal code. Time: O(n) | Space: O(h) where h = tree height (recursion stack) #LeetCode #DataStructures #Python #BinaryTree #Recursion #DFS #CodingInterview #SoftwareEngineering