Jitendra Kumar’s Post

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

Get ready for a new 'Technically Speaking' episode, part 2 of the Mocking Responsibly series is live now! Our teammate Matt explores specialized mocking using the Python responses library. The walk-through compares this approach with general-purpose mocking, showing how tool-specific mocks can reduce coupling between tests and implementation details while allowing safer refactoring. Check it out here: https://lnkd.in/gDmBEpcP #UnitTesting #Python #SoftwareEngineering

Day 33/100 – #100DaysOfCode 🚀 Solved LeetCode #1480 – Running Sum of 1d Array (Python). Today I practiced prefix sum logic to compute the running sum of an array. Approach: 1) Initialize an empty list to store the running sum. 2) Maintain a variable sum = 0. 3) Traverse the array and keep adding each element to sum. 4) Append the updated sum to the result list. 5) Return the final running sum array. Time Complexity: O(n) Space Complexity: O(n) Understanding prefix sums helps solve many array problems efficiently 💪 #LeetCode #Python #DSA #Arrays #PrefixSum #ProblemSolving #100DaysOfCode

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

Day 6 of my Build in Public journey 🚀 Here’s what I focused on today 👇 💻 Python • Revised sets and learned about what a frozenset is • Learned how arrays work in Python (array module, NumPy arrays) • Read how list comprehensions work 🌐 HTML • Learned how to use images in web pages • Explored forms and how they work • Started with web accessibility basics #BuildInPublic #100DaysOfCode #LearningInPublic #Consistency

Day 19 of #100DaysOfPython Today was about instances, state, and higher-order functions. I built a Turtle Race Game using Python’s turtle module. I created multiple turtle instances, each with its own color and position, then made them race using random movement speeds until one wins. This project helped me understand: How different instances can be created from the same class How each instance maintains its own state (position, movement, etc.) How to use functions in a more flexible way when controlling behavior It was a fun way to see objects come to life and interact on the screen. Starting to think more in terms of objects and behavior, not just lines of code. #100DaysOfCode #100DaysOfPython #Python #OOP #PythonProjects #TurtleGraphics #LearningToCode #CodingJourney #BuildInPublic

This challenge introduces lambda functions, which are small anonymous functions written in a single line. They are useful when you need a simple function for a short task without formally defining it using def. THE ANSWER IS: A(7) #Python #LambdaFunction #PythonChallenge #LearningInPublic #CodingJourney

If you’re starting out with Python and wondering how long the journey will take, this guide breaks down what progress really looks like at each stage. https://lnkd.in/gnqhiqqp

Sofie is one of the few people that knows how to make great PRs, if you want to get into open source, learn from her. 👩🏫

Day 20/100 – #100DaysOfCode 🚀 Solved LeetCode #448 – Find All Numbers Disappeared in an Array (Python). Today I worked on an array problem to find all the numbers in the range [1, n] that are missing from the given array. Approach: 1) Convert the array into a set for quick lookup. 2) Traverse numbers from 1 to n. 3) Check if each number exists in the set. 4) If not present, add it to the result list. 5) Return the final list of missing numbers. Time Complexity: O(n) Space Complexity: O(n) Learning how sets help in fast lookup and simplify problems 💪 #LeetCode #Python #DSA #Arrays #HashSet #ProblemSolving #100DaysOfCode