Optimizing Binary Addition with Python's Built-in Function

This was a very good beginner-friendly problem that helped me understand matrix traversal and indexing concepts clearly. 🔹 I learned how to: ✔ Work with 2D arrays (matrices) ✔ Access primary and secondary diagonals ✔ Calculate sums efficiently ✔ Use absolute difference in a practical problem The problem required calculating the absolute difference between the sums of the two diagonals of a square matrix. It strengthened my logical thinking and confidence in handling matrix-based questions. As a beginner, solving problems like this gives me motivation to keep improving every day. 🚀 Consistency + Practice = Growth 💪 #HackerRank #Matrix #Python #ProblemSolving #CodingJourney #BeginnerProgrammer #Consistency

Two-pointer technique in action! This solution finds the closest pair from two sorted arrays whose sum is nearest to a target x — all in O(n + m) time. 🔹 No nested loops 🔹 Optimal pointer movement 🔹 Simple logic, powerful result A great example of how understanding patterns beats brute force every time. Perfect for coding interviews and real-world problem solving 🚀 #Python #DSA #Algorithms #TwoPointers #CodingInterview #ProblemSolving #SoftwareEngineering

🔢 Exploring the change of numbering base 🧪 🤔 Thinking about binary numbers, I went back to the question of change of numbering base. In fact, I recently found out that the python function ìnt()`admits an optional argument that is interpreted as the basis in the representation we are introducing, and the function returns the decimal representation. For example: int('a', base=16) # returns 10 int('f', base=16)  # returns 15 I wanted to write a function that allows us to transform the numerical basis not just to decimal, but from binary to octal... or whatever you want. Interestingly, the algorithm that it occurs to me has to transform to decimal base as a middle step. 🤯 I wrote a whole post about it in my blog, the code is there with some explanations. Find the link 🔗 in the first comment. #mathematics #numbers #fun #python #binary #ternary #decimal #hexadecimal #octal ... and more!!!

Just wrapped up an implementation that counts all square submatrices with a given sum using 2D prefix sums. 🧮 🔍 What’s happening here? Build a prefix sum matrix to enable O(1) submatrix sum queries Iterate over all possible square sizes and positions Check each square’s total efficiently without recomputing sums ⚡ This approach dramatically improves performance compared to brute force and is a powerful technique for grid-based problems in interviews and competitive programming. 📌 Key concepts: #Python #Algorithms #DataStructures #PrefixSum #ProblemSolving #CodingInterview

🚀 Day 54 of #100DaysOfCode 🧩 Problem: Minimum Number of Flips to Make the Binary String Alternating Today I solved an interesting problem involving string manipulation, rotations, and sliding window techniques. 💡 Key Idea: An alternating binary string can only follow two patterns: • "010101..." • "101010..." Since the problem allows rotating the string (moving the first character to the end), the trick is to consider all rotations efficiently. 🔑 Optimization Trick: Instead of rotating the string repeatedly, we can concatenate the string with itself ("s + s") and use a sliding window of size "n" to simulate all rotations. Then we compare each window with both alternating patterns and count the minimum flips required. ⚡ Concepts Used • Sliding Window • Greedy Thinking • String Pattern Matching • Optimization Trick ("s + s" rotation) 💻 Language: Python This problem was a great exercise in thinking about string rotations and pattern mismatches efficiently in O(n) time. 📈 Consistency is the key to improving problem-solving skills! #LeetCode #CodingChallenge #Python #DataStructures #Algorithms #ProblemSolving #100DaysOfCode

🚀 Day 1 – DSA Series Two Sum (LeetCode) Starting my DSA problem-solving series with the classic Two Sum problem, implemented in Python. 🧠 Problem Statement Given an integer array nums and an integer target, return the indices of the two numbers such that they add up to the target. Constraints: • Exactly one valid solution exists. • The same element cannot be used twice. • The answer can be returned in any order. Example: nums = [2, 7, 11, 15], target = 9 Output: [0, 1] Because 2 + 7 = 9. 💡 Approach Implemented I used the nested loop (brute force) approach: • Iterate through each element • Check all remaining elements • Return indices when sum equals target ⏱ Complexity Analysis Time Complexity: O(n²) Space Complexity: O(1) Even for a well-known problem, breaking it down step by step helps strengthen logical thinking and reinforces core fundamentals before jumping to optimized solutions. I’ll be solving and sharing one DSA problem daily -focusing on clarity, approach, and complexity analysis. Let’s build consistency. 🚀 #DSA #LeetCode #Python #Algorithms #ProblemSolving #SoftwareEngineering #CodingJourney

Today’s practice was focused on String and List Manipulation using Slicing. This session helped me understand how powerful slicing is in Python and how it can simplify many problems without using loops. Programs practiced today include: 🔹 Reverse a given string using slicing 🔹 Print every alternate character from a string 🔹 Extract the middle three characters from a string 🔹 Reverse a list of integers using slicing (without loops or built-in reverse functions) 🔹 Remove the first and last characters from a string using slicing Key learnings from today’s session: • Understanding slicing syntax: start : stop : step • Using negative indexing for reversing sequences • How [::-1] works internally • Extracting specific portions of strings efficiently • Writing clean and shorter code without unnecessary loops • Strengthening fundamentals in string and list operations Today’s practice showed me how Python provides elegant solutions for common problems. Instead of writing long logic with loops, slicing makes the code simpler and more readable. Step by step, improving both logic and code efficiency. Grateful for the continuous guidance and support from the #10kcoders team. #Day32 #Python #StringManipulation #ListOperations #Slicing #LogicBuilding #ProgrammingJourney #Consistency

Solved the Continuous Subarray Sum problem on LeetCode using an optimized prefix sum and hashing approach. The solution checks whether a continuous subarray of size ≥ 2 has a sum divisible by k. By tracking remainders of prefix sums in a dictionary, the algorithm efficiently detects valid subarrays in O(n) time complexity. ✅ 102 / 102 test cases passed ⚡ Runtime: 46 ms (Beats 96.15%) 💻 Language: Python This problem strengthened my understanding of prefix sums, modular arithmetic, and hash map optimization techniques commonly used in algorithmic problem solving and technical interviews. #LeetCode #Python #Algorithms #DataStructures #CodingInterview #ProblemSolving

🚀 Day-66 of #100DaysOfCode 📊 NumPy Practice – Image Matrix Manipulation Today I simulated a grayscale image using NumPy and performed a simple brightness adjustment. 🔹 Concepts Practiced ✔ Random matrix generation ✔ Array arithmetic operations ✔ Pixel value clipping using np.clip() ✔ Understanding image data as matrices 🔹 Key Learning Images in computer vision are essentially NumPy matrices, where each element represents a pixel intensity. NumPy makes it easy to manipulate these values efficiently. Exploring how NumPy connects with image processing and computer vision 📸✨ #Python #NumPy #DataScience #ComputerVision #MachineLearning #100DaysOfCode

🚀 Day 42 / 200 – Minimum Window Substring (Hard) Solved LeetCode 76 – Minimum Window Substring today! 💪 This problem was a great test of Sliding Window + HashMap concepts. The challenge was to find the smallest substring that contains all characters of another string (including duplicates). 🔎 Key Learnings: Mastered the two-pointer (left & right) sliding window technique Used frequency counters to track required characters Optimized window shrinking to ensure minimum length Improved understanding of handling duplicate character constraints ✅ 268 / 268 test cases passed ⚡ Runtime: 75 ms 🐍 Language: Python Problems like this strengthen real-world problem-solving skills and improve optimization thinking. Consistency > Motivation. 200 Days. No excuses. 💯 #Day42 #200DaysChallenge #LeetCode #Python #DataStructures #Algorithms #SlidingWindow #ProblemSolving #CodingJourney