karthik A.’s Post

📌 Problem: 1679. Max Number of K-Sum Pairs 💡 Approach: First, sort the array to efficiently apply the two-pointer technique. Initialize two pointers: one at the start (left) and one at the end (right). If the sum equals k, we found a valid pair → increment count and move both pointers If the sum is greater than k, move the right pointer to reduce the sum If the sum is smaller than k, move the left pointer to increase the sum Continue until both pointers meet. ⚙️ Key Insight: Sorting enables efficient pair finding Two-pointer approach avoids checking all pairs (O(n²)) Greedy selection ensures maximum number of operations ⏱️ Time Complexity: O(n log n) (due to sorting) 📦 Space Complexity: O(1) (ignoring sorting space) 📚 What I learned: Two-pointer technique on sorted arrays Optimizing pair problems from brute force to efficient solutions #LeetCode #DSA #Algorithms #Coding #ProblemSolving #Python #TwoPointers #Greedy #InterviewPreparation #CodingJourney

Day 3/30 – NumPy operations with image I developed an Image Editor web app where most of the image processing is powered by NumPy. 🌐 Live App: https://lnkd.in/gBf2rK7U GitHub: https://lnkd.in/gxENJ_3C Key things I learned: 🔹 NumPy for Image Processing – Images are just arrays (pixels) – Applied operations like brightness, contrast, negative using array math – Used slicing for crop, flip, rotate – Created effects like grayscale, sepia, vignette using matrix operations 🔹 Real-time Transformations – Converted images (Base64 ↔ NumPy array) – Applied filters and returned processed images through APIs 🔹 Advanced Processing – Blur (Gaussian filter), edge detection (Sobel) – Sharpening using array differences This project helped me understand how powerful NumPy is for real-world image manipulation. #NumPy #Python #Flask #ImageProcessing #WebDevelopment #LearningByDoing

My thesis was stuck. A matrix had the wrong shape and I had no idea why. I could have printed the entire dataset to find the error. I did not. Instead I used Python's debugger. One breakpoint. One look at the intermediate state. Wrong dimensions. Found in seconds. That moment changed how I work. Not because debugging saved my thesis. But because it taught me something I still use every day: You do not need to see all the data to understand what is wrong. You just need to see the right data at the right moment. Since then, every time a pipeline breaks or a model behaves unexpectedly, I reach for the debugger first. Not print statements. Not guesswork. A breakpoint. An intermediate result. A clear answer. Debugging is not a last resort. It is the fastest way to understand what your code is actually doing. What is your go-to strategy when something breaks unexpectedly? #Python #Debugging #DataScience #MachineLearning #FreelanceDataScientist

🚀 Day 38 of My Problem Solving Journey Today I solved the problem: Valid Parentheses. 🔹 Implemented an approach using string replacement to repeatedly remove valid pairs like "()", "{}", and "[]". 🔹 Learned how to simplify the problem by eliminating balanced brackets step by step. 🔹 Practiced working with string manipulation and loop conditions. 🔹 Understood how this problem can also be solved efficiently using a stack-based approach. 💡 Key takeaway: By continuously removing valid pairs, we can check if the string becomes empty. However, using a stack is a more optimal and scalable solution for this problem. 📌 Example: Input: "()" Output: true Input: "(]" Output: false This problem improved my understanding of stacks, string operations, and pattern matching techniques. On to the next challenge! 💪🔥 #Day38 #CodingJourney #Python #ProblemSolving #DataStructures #Algorithms #LeetCode

🚀 Day 39 / 100 – Problem Solving Challenge Today I worked on the Minimum Window Substring problem — a classic and highly important interview question in string and sliding window concepts. 📌 Problem Statement: Given two strings s and t, the task is to find the smallest substring of s such that it contains all characters of t (including duplicates). If no such substring exists, return an empty string. 💡 Approach Used: Built a frequency map for string t Used a brute-force approach to check every possible substring of s For each substring, maintained a frequency map and validated if it satisfies all characters of t Updated the result whenever a smaller valid window was found ⚙️ Time Complexity: O(n² × k) (inefficient for large inputs, but good for understanding the concept) 📚 Key Learnings: Importance of frequency maps in substring problems How brute-force window expansion works Understanding why optimized sliding window is needed for real-world efficiency #100DaysOfCode #ProblemSolving #Python #CodingJourney #Algorithms #SlidingWindow #LearningByDoing

Day 43 of LeetCoding everyday until I get a J-O-B: Check If a String Contains All Binary Codes of Size K. If K = 2, the possible codes are 00, 01, 10, 11. We need to prove every combination exists inside our string. The Noob Trap: Generating all $2^k$ combinations upfront to cross them off. If K = 20, you need over a million strings. You just blew up your RAM. The Senior Fix: Math & Sliding Windows 1. The Math Filter: For a string to even physically fit all combinations, its length must be at least 2^k + K - 1. If it's shorter? Instant return False. Just like my job applications. 2. The Set: We slide a window of size K across the string, dumping every slice into a Python Set (which automatically vaporizes duplicates). 3. The Check: At the end, we check if len(seen) == (1 << k). (We use a Bitwise Left Shift because we are elite). See more: https://lnkd.in/gUki2imQ #LeetCode #Python #DataStructures #Engineering #TechHumor

Just solved “First Matching Character From Both Ends” 🚀 💡 My approach (simple & efficient): Instead of overcomplicating it, I used a two-pointer mindset without explicitly creating two pointers. Loop through the string from the start For each index i, compare: s[i] (from the front) s[n - i - 1] (from the back) The moment both match → return the index If no match → return -1 ✨ This works because we're checking symmetry from both ends in a single pass (O(n)) with O(1) space. Sometimes the best solutions aren’t fancy — they’re just clean and intuitive. 🔥 Consistency > Complexity. Small wins like this build strong problem-solving instincts. #LeetCode #DSA #Python #CodingJourney #ProblemSolving #TechGrowth #CodeDaily #WomenInTech #FutureEngineer #100DaysOfCode #KeepBuilding

Day 5 of #14DaysOfPython Completed Strings (core + advanced) and consolidated everything in one place. Strings are a major part of problem solving — most questions are based on text manipulation. Concepts Covered: Indexing and slicing Traversing using loops (for, while) Built-in methods: lower(), upper(), strip(), replace() ASCII basics using ord() and chr() String immutability Concatenation and repetition Membership operators (in, not in) String comparison Advanced methods: split(), join(), find(), count() String formatting (f-strings) Escape characters Validation methods: isalpha(), isdigit(), isalnum() Problems practiced: Palindrome check Reverse a string Count vowels and consonants Remove spaces Anagram check Character frequency Remove duplicate characters First non-repeating character Key takeaway: Most string problems follow the same pattern — iterate through characters, apply conditions, and keep track of counts. Understanding this pattern makes complex problems easier to solve. Strings topic completed. Moving to next. #HackerRank #Python #ProblemSolving #CodingJourney #Developer #LearningInPublic #codegnan

🚀 Another LeetCode Problem Solved: Palindrome Number! 🔗 Check out my solution: https://lnkd.in/dwDMqXXn 💡 Problem Overview Given an integer x, determine whether it is a palindrome — meaning it reads the same forward and backward. (LeetCode) Examples: ✔ 121 → Palindrome ❌ -121 → Not a palindrome ❌ 10 → Not a palindrome 🧠 My Approach (Digit Reversal) Instead of converting the number to a string, I used a mathematical approach: Extract digits using % 10 Reverse the number step by step Compare reversed number with original ⚙️ Key Learnings ✔ Strong understanding of number manipulation ✔ Importance of handling edge cases (negative numbers, trailing zeros) (leet-solution.com) ✔ Practicing clean and efficient logic ⏱️ Complexity • Time Complexity: O(log n) • Space Complexity: O(1) 🔥 Why this problem matters Even though it’s an “easy” problem, it builds: Logical thinking Problem-solving fundamentals Confidence for bigger challenges #LeetCode #DSA #Python #CodingJourney #ProblemSolving #100DaysOfCode

Just shipped a new feature in my VS Code extension, CallFlow Tracer: automatic trace summarization. Performance traces usually give raw data, not answers. This feature turns complex call graphs into clear, actionable insights with one click. Identifies the slowest functions Shows exact time impact (percentages) Highlights bottleneck modules Suggests next optimization steps Provides complete trace statistics No more manually analyzing hundreds of nodes or guessing where the issue is. You get a clean summary of what to fix and why. Available now on the VS Code Marketplace — search “CallFlow Tracer”. What’s one performance insight you wish tools gave you automatically? #Python #VSCode #DeveloperTools #PerformanceOptimization #OpenSource