For Loop vs While Loop in Python: Understanding the Nuances

Just solved “Second Largest Digit in a String” on LeetCode — and here’s the simple approach I followed 👇 Instead of overcomplicating it, I focused on clean thinking + Python basics: 🔹 Converted the string into a set → removes duplicates instantly 🔹 Filtered only digits using isdigit() 🔹 Stored them as integers in a list 🔹 Sorted the list → easy access to largest & second largest 🔹 Edge case check: if less than 2 digits → return -1 💡 Key takeaway: Sometimes the most optimal solution isn’t about complex algorithms — it’s about using the right built-in tools smartly. 🚀 What I’m improving with each problem: • Writing cleaner logic • Thinking in steps instead of rushing • Handling edge cases early Consistency > Complexity. #LeetCode #DSA #Python #ProblemSolving #CodingJourney #100DaysOfCode

👉Day 81 – Diving Deeper into Randomness & Voice in Python 🧠✨ Today’s exploration added more exciting tools to my Python journey: 🔹 Random Module (Advanced Functions) – Practiced uniform(), choices(), and sample() to generate floating-point randomness, weighted selections, and unique subsets. These functions showed how randomness can be fine-tuned for simulations, games, and creative problem-solving. 🔹 Text-to-Speech with pyttsx3 – Learned how to install and use this library to convert text into voice. It was fascinating to see code literally speak back, opening doors to accessibility features, interactive applications, and fun projects. 🌱 Reflection – Randomness taught me that unpredictability can be controlled with precision, while text-to-speech reminded me that code can connect with people in more human ways. Together, they highlight how programming bridges logic and creativity. ⚡ Day 81 was about giving code a voice and mastering randomness with purpose — skills that make applications dynamic, interactive, and impactful. #Day81 #PythonLearning #RandomModule #pyttsx3 #CodingJourney #10000Coders #LearnInPublic #100DaysOfCode

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

Workflow Experiment Tracking using traintool #machinelearning #datascience #workflowexperimenttracking #traintool traintool is the easiest Python library for applied machine learning. It allows you to train off-the-shelf models with minimum code: Just give your data and the model name, and traintool takes care of the rest. https://lnkd.in/g4BhbTpw

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

Day 4/365: Counting Vowels and Consonants in a String 🔤🧠 Today I worked on a classic beginner-friendly problem in Python: counting how many vowels and consonants are present in a string. The logic I used was simple but powerful: 1. Start with a string (for example: "Hello"). 2. Loop through each character. 3. If the character is in the set of vowels (aeiouAEIOU), increase the vowel counter. 4. Otherwise, if it’s an alphabet and not a vowel, increase the consonant counter. 5. In the end, print the total number of vowels and consonants. What I liked about this exercise: It made me think carefully about conditions (if / elif) and how loops work. I learned why it’s important to handle only alphabetic characters, so spaces, commas, or digits don’t get counted as consonants by mistake. It’s a small step, but it builds the habit of thinking about edge cases and input validation. Day 4 done ✅ 361 more to go. If you have any interesting variations of this problem (like handling entire sentences or ignoring case and punctuation), share them with me—I’d love to try them out. #100DaysOfCode #365DaysOfCode #Python #LogicBuilding #StringManipulation #CodingJourney #LearnInPublic #AspiringDeveloper

💻 Solved a great problem today: Count Increasing Subarrays 🚀 Given an array, the task was to count all strictly increasing subarrays of size ≥ 2. 🔍 Approach I used: Broke the array into continuous increasing segments For each segment of length k, calculated subarrays using the formula: 👉 k(k-1)/2 Summed all results to get the final answer ⚡ Time Complexity: O(n) 📦 Space Complexity: O(n) 💡 This problem helped me understand how breaking a problem into patterns can simplify complex logic. Here’s my Python solution 👇 class Solution: def countIncreasing(self, arr): list2 = [] list2.append(arr[0]) list3 = [] for i in range(1, len(arr)): if arr[i-1] < arr[i] and arr[i] > 2: list2.append(arr[i]) else: list3.append(list2) list2 = [] list2.append(arr[i]) list3.append(list2) ans = 0 for i in list3: if len(i) > 1: ans += (len(i) * (len(i) - 1)) // 2 return ans 🔥 Always learning, always improving. #python #dsa #coding #problemSolving #programming #developers #learning

From “it works” to “it won’t break” While writing a code, Getting it to work is one thing, 𝗠𝗮𝗸𝗶𝗻𝗴 𝘀𝘂𝗿𝗲 𝗶𝘁 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗯𝗿𝗲𝗮𝗸 is another. price = products["Laptop"] This works fine… until the 𝗸𝗲𝘆 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗲𝘅𝗶𝘀𝘁 . That’s when the program crashes. So instead of assuming every piece of data is present, Its better to start thinking about what happens when it isn’t. In college projects, we often focus on making things work. In real-world scenarios, 𝗲𝗱𝗴𝗲 𝗰𝗮𝘀𝗲𝘀 matter just as much. 𝗗𝗮𝘆 𝟭𝟮/𝟯𝟬 #Python #LearningInPublic #Day12 #30DaysOfCode #SoftwareEngineering

Week 4 of #100DaysOfCode — done! 🎉 Last week I learned how to build classes. This week I learned how to make them talk to each other. Topics covered: 🧹 Inheritance → Superclass, subclass, base class — and what they actually mean → How Python finds attributes (spoiler: it walks up the chain) → Overriding methods — and extending them with super() → isinstance, issubclass, type — when to use which → Multiple inheritance + MRO (Method Resolution Order) 🏗️ Abstract Classes & Interfaces → ABC + @abstractmethod — enforcing a contract on subclasses → Duck typing — "if it has a speak() method, it speaks" → Subclassing built-ins (list, dict, iterator) → Mixins — plugging in behaviour without full inheritance I’ve structured my learning into notes and practical examples to better understand the concepts : https://lnkd.in/epaBymnJ #100DaysOfCode #Python #OOP #LearningInPublic #Programming

🚀 Day 16 of #100DaysOfCoding Today I worked on pattern problems using Python, focusing on nested loops and condition logic. 🔹 Built a hollow square pattern using while loops 🔹 Strengthened understanding of loop control (i, j iterations) 🔹 Learned how to apply conditions for borders vs inner spaces 🔹 Practiced dry run techniques to debug and visualize code execution 💡 Key Learning: Breaking a problem into rows and columns makes pattern questions much easier to solve. The real trick is identifying where to print values and where to skip. Consistency is slowly turning confusion into clarity 💪 #Python #Coding #DSA #Programming #LearningJourney #Consistency n = int(input()) i = 1 while(i <= n):   j = 1   while(j <= n):     if(i == 1 or i == n):       print("*", end="")     elif(j == 1 or j == n):       print("*", end="")     else:         print(" ", end="")       j += 1   print("")     i += 1