Big O Notation: Efficient Coding for Scalable Tech

200 LeetCode Problems I recently crossed the milestone of solving 200 problems on LeetCode, all implemented in Python. Working through Easy, Medium, and Hard challenges has helped me strengthen my coding skills, improve problem‑solving strategies, and gain confidence across different areas. Some of the key lessons from this journey include: 1. Using Python tools like Counter, defaultdict, and cmp_to_key effectively. 2. Implementing permutation problems and generating powersets with itertools.combinations. 3. Handling 32‑bit integer range constraints when required. 4. Applying binary search in creative ways — from rotated arrays to math problems like sum of squares. 5. Elegant tricks such as matrix transpose in one line with zip(*matrix). 6. Tackling 3Sum/4Sum using two‑pointer techniques and duplicate handling. 7. Leveraging prefix sums for problems like Push Dominoes and subarray challenges. 8. Using float('inf') and float('-inf') for boundary conditions. 9. Managing time and space complexity trade‑offs more effectively. Through these 200 problems, I’ve worked across: 1. Math & Number Theory (powers, squares, integer ranges) 2. Strings (palindromes, anagrams, permutations, custom sorting) 3. Arrays & Searching (binary search, rotated arrays, prefix sums, subarrays) 4. Hashing & Frequency (Counter, defaultdict, frequency maps) 5. Design & Implementation (HashMap, HashSet, Randomized set, TinyURL) 6. Classic Interview Problems (3Sum, 4Sum, Kth largest, Trapping Rain Water, Median of Two Sorted Arrays) This milestone is a reminder that consistent practice builds intuition, resilience, and confidence. Along the way, I’ve analyzed my progress and realized that I need to put more focus on prefix sums and subarray problems to strengthen my skills further. #LeetCode #PythonProgramming #ProblemSolving #Algorithms #DataStructures #CodingJourney #InterviewPreparation #ContinuousLearning #SoftwareEngineering #Learning #LogicalThinking

The loop was supposed to stop when the user typed 0. It never did. They used while count < 10 but forgot count += 1. Condition stayed True forever. One line: the increment. I wrote a beginner guide that clears up infinite loops and the three keywords: ✅ What is an infinite loop? (while True, or condition never changes) ✅ break — exit the loop now (e.g. user enters 0 to quit) ✅ continue — skip this iteration, go to the next (e.g. skip multiples of 3) ✅ pass — do nothing (placeholder when a block can't be empty) ✅ break vs continue, and when we want while True + break ✅ Summary and next steps ~5 min read. No fluff. https://lnkd.in/g-xZTtcv #Python #Programming #Coding #Beginners #LearnToCode #InfiniteLoop #Break #Continue #Pass #WhileLoop #Practice #Tech #SoftwareDevelopment #CodingTips

🚀 Day 9 of #100DaysOfCode — Finding the Sum of the Smallest Numbers in Python Today I explored two different approaches to solve a simple but important problem: 👉 Find the sum of the smallest N numbers in a list ✅ Approach 1: Pythonic & Efficient numbers = [5, 2, 9, 1, 7] n = 2 result = sum(sorted(numbers)[:n]) print(result)🔹 How it works: sorted(numbers) → sorts the list[:n] → picks the smallest n elementssum() → adds them up💡 Clean, readable, and perfect for most use cases. ✅ Approach 2: Manual Logic (Without Built-ins) arr = [5, 2, 9, 4, 3, 5] N = 2 total = 0 data = len(arr) for k in range(N): min_index = 0 for i in range(1, data): if arr[i] < arr[min_index]: min_index = i total += arr[min_index] arr[min_index] = float('inf') print("Sum of smallest", N, "numbers:", total)🔹 How it works: Repeatedly finds the smallest elementAdds it to totalMarks it as used (by setting to infinity)💡 Great for understanding core logic and algorithm design 🔍 Key Takeaways ✔️ Built-in functions save time and reduce complexity ✔️ Manual approach helps strengthen problem-solving skills ✔️ Always balance readability vs control 💬 Best Comment Insight “Don’t just learn shortcuts — understand what’s happening under the hood. That’s where real growth happens.” #Python #CodingJourney #30DaysOfCode #LearnToCode #Programming #Developers #ProblemSolving #PythonBasics

🔥 Day 54 of #100DaysOfCode 📌 Solved: Sort an Array (LeetCode 912) Today’s problem was all about mastering sorting fundamentals without using built-in functions — a real test of understanding core algorithms. 💡 Problem Insight: We are given an array of integers and need to sort it in ascending order with O(n log n) time complexity. 👉 This rules out simple approaches like Bubble Sort or Selection Sort ❌ 👉 Forces us to use efficient algorithms like: ✔️ Merge Sort ✔️ Quick Sort ⚙️ Approach I Used: Merge Sort 🔹 Divide the array into halves 🔹 Recursively sort both halves 🔹 Merge them in sorted order 🚀 Key Learnings: ✅ Divide & Conquer strategy ✅ Importance of time complexity ✅ Writing sorting logic from scratch (no shortcuts!) ✅ Handling edge cases while merging arrays 📊 Result: ✔️ Accepted ✅ ⏱️ Runtime: 999 ms 💾 Memory: Optimized #Day54 #LeetCode #DSA #Python #CodingJourney #100DaysOfCode #ProblemSolving #Tech #Developers #Learning

Stop confusing Loops, Iterables, and Iterations. 5️⃣ simple way to remember: 1️⃣ Iteration: Doing the same task over and over. One round = one iteration. 2️⃣ Loop: The code block that performs those repeated tasks. 3️⃣ Iterable: Anything you can loop over (like a list of numbers or words). 4️⃣ While loop: “Keep doing this as long as the condition is true.” 5️⃣ Logical operators: and, or, not → decide when loops should continue or stop. 💡 Pro tip: Think of a while loop as a music playlist: It keeps playing songs (iterations) Stops when you press break Skips a song with continue Python loops = your automation superpower. Master them, and repetitive tasks won’t stand a chance! #Python #Coding #DataAnalytics #LearnToCode #Automation #ProgrammingTips #GoogleDataAnalytics #GrowWithGoogle

I recently started reading The Pragmatic Programmer by Andrew Hunt and David Thomas, and one idea stuck with me: "Learn at least one new language every year." So I decided to try it out and started learning Rust. And it immediately felt different. Coming from Python, I'm used to moving fast - writing code, trying ideas, iterating quickly. Rust slowed me down in a good way and made me think about things I usually ignore: Memory. Ownership. Lifetimes. What my code actually does under the hood. This made me realize that different languages train us to think in completely different ways. In this AI era where writing code is easier than ever, the real advantage isn’t speed. It’s depth of understanding. Curious - which language changed the way you think the most? #Programming #RustLang #ThePragmaticProgrammer #LearningInPublic

🚀 Learning in public — and humbled every step of the way. A week ago, I set up Visual Studio Code, integrated Claude Code, and connected GitHub. Felt unstoppable. Felt like a developer. Then reality checked in. 😅 Turns out, having the tools doesn't mean you know how to use them. I quickly realized I was building on a shaky foundation — I needed to go back to basics and learn Python properly. And honestly? It makes complete sense. Python is the de facto language of AI and machine learning. If you want to understand, build, or even just talk to the tools shaping the future — Python is the starting point, not an afterthought. So here I am. Back to basics. Variables, loops, functions, libraries. Not a step backward — hopefully a step in the right direction. 🐍 The journey matters more than looking like you've arrived. #Python #LearningToCode #AIJourney #ClaudeCode #VSCode #GitHub #100DaysOfCode #GrowthMindset #AI #BackToBasics

Stop writing out massive lists by hand. 🛑 ⠀ If you want a computer to count to 1,000, beginners often try to store every single number in memory: [0, 1, 2, 3, ... 999, 1000] ⠀ That's a massive memory hog. 😫 ⠀ Professional Python developers build automated "robots" using `for` loops and the `range()` function. ⠀ Think of `range()` not as a static list, but as a tiny, highly efficient ticket dispenser. It generates numbers *one at a time*, exactly when the loop asks for the next one. 🎟️💡 ⠀ You can even control the exact sequence using (Start, Stop, Step): ⠀ for countdown in range(10, 0, -1): print(countdown) print("Lift Off! 🚀") ⠀ This snippet counts down from 10 to 1, stepping backwards, and takes almost zero memory—whether you're counting from ten or ten million. ⠀ Want bite-sized "aha!" moments like this delivered daily? ⠀ Try PyDaily's free Demo Mode. Access Days 1-3 of our real student portal instantly—no signup, no email required. ⠀ 👇 Experience the lessons and interactive quizzes yourself: https://lnkd.in/ducXvs-y ⠀ #Python #CodingBootcamp #LearnToCode #DataStructures #TechEducation #PyDaily

People ask "how can 750 lines do what LangChain does in 60,000?" The answer: it can't do everything LangChain does. But it does everything you actually need. And you understand every line.

✅ Day 90 of 100 Days LeetCode Challenge Problem: 🔹 #476 – Number Complement 🔗 https://lnkd.in/gzE6gM7d Learning Journey: 🔹 Today’s problem focused on finding the complement of a number by flipping its binary bits. 🔹 I first converted the integer to its binary representation using bin(num)[2:]. 🔹 Then, I created a helper function to flip each bit: • '0' → '1' • '1' → '0' 🔹 After generating the flipped binary string, I converted it back to an integer using int(..., 2). 🔹 Returned the final complemented value. Concepts Used: 🔹 Binary Representation 🔹 Bit Manipulation 🔹 String Traversal 🔹 Base Conversion Key Insight: 🔹 The complement operation is essentially a bitwise NOT, but only within the significant bits of the number (ignoring leading zeros). 🔹 Converting to binary simplifies the flipping logic for beginners. Complexity: 🔹 Time: O(log n) 🔹 Space: O(log n) #LeetCode #Algorithms #DataStructures #CodingInterview #100DaysOfCode #Python #ProblemSolving #LearningInPublic #TechCareers