Python String Concatenation with F-strings

Solved 𝗟𝗖 𝟮𝟲𝟰𝟬 · Find the Score of All Prefixes of an Array (Medium) First glance at the problem? Skimmed it, saw "prefix" and some operation on elements — 𝗮𝘀𝘀𝘂𝗺𝗲𝗱 𝗶𝘁 𝘄𝗮𝘀 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗹𝗶𝗸𝗲 𝘀𝗾𝘂𝗮𝗿𝗶𝗻𝗴. Wrote code. Wrong answer. Read the statement properly this time. Turns out conver[i] = arr[i] + max(arr[0..i]) — each element gets added to the 𝗿𝘂𝗻𝗻𝗶𝗻𝗴 𝗺𝗮𝘅 up to that index. The score of a prefix is just the sum of its conversion array. Track 𝗺𝗮𝘅_𝘀𝗼_𝗳𝗮𝗿 as you iterate, add it to the current element, accumulate into score. 𝗢𝗻𝗲 𝗽𝗮𝘀𝘀, 𝗱𝗼𝗻𝗲. Day 39 — #1000DaysOfLearning #DSA #LeetCode #Python #1000DaysOfLearning #LearningInPublic

🐍 Week 17 – Refining My Python Skills 🐍 This was a shorter week due to some personal commitments, but I focused on implementing the quicksort algorithm. Like last week with merge sort, I wanted to deeply understand how quicksort works. Here are the key concepts I worked on: - Implemented a separate partition function to split around a pivot. In my approach, I used three buckets (left, middle, right) to handle duplicates more cleanly and avoid unnecessary comparisons. - Created a quick_sort function to implement the main algorithm, recursively sorting the partitions until the base case was met. After practicing merge sort, quicksort felt more intuitive, and the concepts connected more easily. In Week 18, I plan to practice implementing the Luhn Algorithm. #Python #CodingJourney #LearningInPublic

Day 119 Same problem family, new constraint — but now it feels easier. #Day119 🧩 40. Combination Sum II How today went: • Very similar to Combination Sum • First step: sort the array • Move to i + 1 (each element used once) • Skip duplicates to avoid repeating combinations Key idea: 👉 No reuse of same element 👉 Handle duplicates carefully What I realized: Once you understand the base pattern, variants like this become much easier. Backtracking is starting to feel natural now. #LeetCode #DSA #Python #Backtracking #Recursion #LearningInPublic #Consistency

Day 109 Backtracking patterns are repeating again — and that’s a good sign. #Day109 🧩 78. Subsets How today went: • Used recursion to explore all elements • At each step, decide to include or skip the current element • Append current subset → explore → then pop to backtrack • Move to the next index and repeat What I’m noticing: Subsets is one of the cleanest backtracking patterns: → choose → explore → undo Another revision day, but clarity is improving. Consistency continues. #LeetCode #DSA #Python #Backtracking #Recursion #LearningInPublic #Consistency

📌 Problem: Merge Strings Alternately 💡 Approach: Used a simple two-pointer / iteration technique to merge both strings character by character. First, iterate up to the minimum length of both strings and append alternately. Then, append the remaining characters from the longer string. ⚙️ Key Insight: Handle unequal string lengths separately Avoid index out-of-bounds by iterating till min(len(word1), len(word2)) ⏱️ Time Complexity: O(n + m) 📦 Space Complexity: O(n + m) merg 📚 What I learned: String manipulation efficiently Handling edge cases when lengths differ #LeetCode #DSA #Coding #ProblemSolving #Python #SoftwareDevelopment #CodingJourney

Python Clarity Series – Episode 24 Topic: Late Binding in Loops (Functions) ⚠️ Advanced pitfall: Late binding in loops funcs = [] for i in range(3): funcs.append(lambda: i) for f in funcs: print(f()) Output: 2 2 2 ❗ 👉 Expected: 0 1 2 👉 Got: same value 💡 Reason: Lambda captures variable, not value. 💡 Fix: funcs.append(lambda i=i: i) 💡 Rule: Default arguments capture current value. This is a classic interview trap. #PythonAdvanced #CodingPitfalls #DeveloperLevel #python #clarity

Day 102 Backtracking patterns are starting to repeat. #Day102 🧩 90. Subsets II How today went: • Similar to the basic Subsets problem • Key difference: handling duplicates • Sorting the array is important • While iterating, skip duplicates to avoid repeating subsets What clicked: Backtracking becomes easier when you: • Recognize the base pattern • Add constraints like duplicate handling Same structure, new rule. That’s how patterns build. #LeetCode #DSA #Python #Backtracking #Recursion #LearningInPublic #Consistency

Day 121 Backtracking with clear rules makes things simple. #Day121 🧩 22. Generate Parentheses How today went: • Tracked two values: open and close • Add '(' when open < n • Add ')' when close < open • Build the string step by step using recursion What clicked: It’s all about following the rules: → never let close exceed open → keep building valid sequences Backtracking here is clean: add → recurse → backtrack Simple logic, strong pattern. #LeetCode #DSA #Python #Backtracking #Recursion #LearningInPublic #Consistency

🚀 Day 44 of My Coding Journey Today I explored Python Regular Expressions and learned how to find the start and end indices of substrings, even when they overlap! 🔍 💡 Key Takeaways: ✨ start() and end() help locate exact positions of matches ✨ Regular finditer() doesn’t capture overlapping patterns ✨ Using lookahead (?=...) allows us to detect overlapping matches 📌 Example: String: aaadaa Substring: aa Output: (0, 1) (1, 2) (4, 5) 🔥 This was a great reminder that small details (like overlapping cases) can make a big difference in problem-solving. Consistency is key — one step every day! 💙 #Day44 #CodingJourney #Python #Regex #ProblemSolving #LearningEveryday #Consistency

Day 7 of my Python learning journey: Today I focused on classic array and string patterns, and tried to keep solutions clean and efficient. What I solved: Two Sum using brute-force and hash map Valid Palindrome with two pointers Move Zeros with an in-place two-pointer approach Container With Most Water in O(n) Big takeaway: Correctness first, clarity second, optimization third. Small design choices, like in-place updates vs extra arrays, really affect code quality. GitHub link: https://lnkd.in/gGPw8_js #Python #ProblemSolving #Algorithms #TwoPointers #LearningInPublic #CleanCode