Solved HackerRank Python String Substring Count Challenge

Day 37 / #120DaysOfCode – LeetCode Challenge ✅ Problem Solved: • Search a 2D Matrix 💻 Language: Python 📚 Key Learnings: • Applied Binary Search on a 2D matrix • Learned how to treat matrix as a flattened sorted array • Practiced converting 1D index → 2D index (row, col) • Improved understanding of search space reduction • Strengthened logarithmic time complexity (O(log n)) thinking Better logic → Faster execution 🚀 🔗 LeetCode Profile: https://lnkd.in/gbeMKcv5 #LeetCode #Python #DSA #BinarySearch #Algorithms #CodingJourney #Consistency #120DaysOfCode

Day 39 / #120DaysOfCode – LeetCode Challenge ✅ Problem Solved: • Integer to Roman 💻 Language: Python 📚 Key Learnings: • Learned how to map numerical values to symbolic representations • Used greedy approach for optimal conversion • Understood importance of ordered value-symbol pairing • Practiced handling special subtraction cases (IV, IX, XL, etc.) • Improved skills in writing structured and readable logic Consistency + Logic = Growth 🚀 🔗 LeetCode Profile: https://lnkd.in/gbeMKcv5 #LeetCode #Python #DSA #Algorithms #CodingJourney #Greedy #120DaysOfCode

📌 Problem: Reverse Vowels of a String 💡 Approach: Used the two-pointer technique to reverse only the vowels in the string. Initialize one pointer at the beginning and one at the end. Move both pointers inward until vowels are found, then swap them. Continue this process until both pointers meet. ⚙️ Key Insight: Use a set for fast vowel lookup (O(1)) Two-pointer approach avoids extra space for storing vowels separately ⏱️ Time Complexity: O(n) 📦 Space Complexity: O(n) (due to string → list conversion) 📚 What I learned: Efficient string manipulation using two pointers Optimizing lookups with hash sets #LeetCode #DSA #Algorithms #Coding #ProblemSolving #Python #TwoPointers #InterviewPreparation #CodingJourney

Day 28 / #120DaysOfCode – LeetCode Challenge 🚀 Consistency is building momentum 💯 Today’s focus was on String Processing and Frequency Counting, using Python’s built-in tools for efficient solutions. ✅ Problem Solved: • Most Common Word 💻 Language: Python 📚 Key Learnings: • Used regex (re.findall) to extract words cleanly • Applied Counter to count word frequency efficiently • Learned how to handle case-insensitive strings • Filtered out unwanted words using conditions Clean code + built-in functions = powerful solutions 🚀 Every day improving step by step 💪 🔗 LeetCode Profile: https://lnkd.in/gbeMKcv5 #LeetCode #Python #DSA #Strings #Regex #ProblemSolving #CodingJourney #Consistency #120DaysOfCode

Day 60/100 — #100DaysOfCodingChallenge 60 days in… consistency is slowly turning into a habit now. 🔹 Python (DSA) Solved Search a 2D Matrix — used binary search by treating the matrix like a flattened sorted array. It was a nice reminder of how powerful binary search can be when applied smartly. 🔹 SQL Did some light practice to keep concepts fresh and maintain the streak. #Python #SQL #DSA #LeetCode #Day60 #100DaysOfCode #LearningInPublic #Consistency

Python Clarity Series – Episode 25 Topic: Mutable vs Immutable Function Behavior 📌 Why did my list change after function call? def modify(lst): lst.append(100) a = [1, 2] modify(a) print(a) Output: [1, 2, 100] 👉 Lists are mutable → changes reflect outside Now: def modify(x): x = x + 10 a = 5 modify(a) print(a) Output: 5 👉 Integers are immutable → no change outside 💡 Rule: Mutable → changes persist Immutable → changes don’t This confusion causes logic errors. #PythonBasics #FunctionConcepts #StudentClarity #python #clarity

Day 45 / #120DaysOfCode – LeetCode Challenge ✅ Problem Solved: • Maximum Distance Between Two Different Colors 💻 Language: Python 📚 Key Learnings: • Applied greedy observation-based approach • Learned to compare elements with first and last values • Avoided unnecessary nested loops → kept solution O(n) • Improved thinking in terms of distance maximization • Reinforced writing simple and efficient code Not every problem needs complexity — smart thinking matters 💯 🔗 LeetCode Profile: https://lnkd.in/gbeMKcv5 #LeetCode #Python #DSA #Greedy #Algorithms #CodingJourney #120DaysOfCode

Python Series — Day 3 🧠 Let’s level it up a bit 👇 What will be the output of this code? def modify_list(lst): lst.append(4) a = [1, 2, 3] modify_list(a) print(a) Options: A. [1, 2, 3] B. [1, 2, 3, 4] C. Error D. None Think carefully 👀 (Hint: It’s not about functions… it’s about how Python handles data) Drop your answer 👇 Answer tomorrow 🚀 #Python #CodingChallenge #LearningInPublic #DataEngineering #Tech

In 𝗙𝗮𝘀𝘁𝗔𝗣𝗜, 𝗿𝗲𝘁𝘂𝗿𝗻 𝘁𝘆𝗽𝗲 and 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗲_𝗺𝗼𝗱𝗲𝗹 describe the success body: a single Pydantic model, or a list of that model—whatever the handler returns on a normal 2xx. When a lookup fails or a rule is broken, you raise 𝗛𝗧𝗧𝗣𝗘𝘅𝗰𝗲𝗽𝘁𝗶𝗼𝗻 so the client gets a proper 𝟰𝘅𝘅 𝘀𝘁𝗮𝘁𝘂𝘀 and a 𝗱𝗲𝘁𝗮𝗶𝗹 𝗽𝗮𝘆𝗹𝗼𝗮𝗱. That is separate from the return type, because raise is not return. 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗲_𝗺𝗼𝗱𝗲𝗹 defines how the 𝘀𝘂𝗰𝗰𝗲𝘀𝘀 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗲 is built and documented; HTTPException is how you answer with an error without faking a 200. 👉 Detailed breakdown here: https://lnkd.in/gcySJqZX 👉 Code Here: https://lnkd.in/gyf4663s #FastAPI #Python #API #BackendDevelopment #SoftwareEngineering #Pydantic #OpenAPI

Today I worked on an interesting string problem — counting how many times a substring appears in a string without using built-in methods like count(). At first, it seemed straightforward… until I realized an important twist 👇 👉 Built-in count() does not handle overlapping substrings So I implemented a manual sliding window approach: 🔹 Traverse the string from left to right 🔹 Extract substrings using slicing 🔹 Compare each slice with the target substring 🔹 Increment count when a match is found 💡 Example: String → ABCDCDC Substring → CDC There are 2 occurrences, not 1 — because overlapping is allowed. This small problem helped me understand: How string slicing works internally Why built-in functions aren’t always sufficient The importance of handling edge cases like overlapping 🧠 Key takeaway: Sometimes writing logic manually gives deeper insight than relying on shortcuts. Learning step by step and enjoying the process 🔥 #Python #CodingJourney #100DaysOfCode #ProblemSolving #DataStructures #Learning