Python Math Module for Square Roots and Factorials

Hi guys, I know it’s delayed—now let’s dig into Python again for this post! 💭 Day 3 with Python… something finally clicked. The errors didn’t stop. The confusion didn’t magically disappear. But today… I wrote something that actually worked. Not just print("Hello, World!") Not just fixing errors… 👉 I made decisions in my code. Using if...else, my program could finally think (at least a little 😄) “IF this happens → do this” “ELSE → do something else” And suddenly, coding didn’t feel like typing… It felt like logic coming to life. 💡 That’s when I realized: Programming isn’t about memorizing syntax. It’s about teaching a machine how to think step by step. Every small concept—conditions, loops, functions— They’re not just topics… They’re building blocks of something bigger. Today it’s simple decisions. Tomorrow? Maybe something powerful. ✨ Step by step… line by line… growth is happening. #Python #CodingJourney #Day3 #LearnToCode #Programming #DeveloperLife #LogicBuilding #TechGrowth 🚀

Today’s Python lesson was one of those “ohhh, so this is why programming feels so organized” moments. 🐍 Day 05 of my #30DaysOfPython journey was all about lists, and honestly, this topic felt like the first real step toward writing cleaner, more useful code. A list in Python is an ordered and mutable collection. It can hold different data types, and yes, it can even be empty. Here’s what I explored today: 1. Creating lists with [] and list() 2. Checking length with len() 3. Accessing items through indexing, slicing, and unpacking 4. Using in to check whether an item exists 5. Adding items with append() and insert() 6. Removing items with remove(), pop(), del, and clear() 7. Copying lists with copy() 8. Joining lists using + and extend() 9. Counting and locating items with count() and index() 10. Reversing with reverse() 11. Sorting with sort() and sorted() They are not just containers for values — they are one of the most practical ways to organize, update, combine, and manage data in Python. The fact that you can add, remove, slice, copy, reverse, and sort them makes them feel like a real data-handling tool rather than just a basic collection. Today reminded me that lists are one of the most useful structures in Python because they let you work with data in a very dynamic way. One more day, one more topic, one more layer of understanding. Github Link - https://lnkd.in/gUt9EfWs #Python #LearnPython #CodingJourney #30DaysOfPython #Programming #DeveloperJourney

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 biggest slowdown in my Python projects hasn’t been coding or debugging… it’s dependencies. ModuleNotFoundError imports not matching package names version conflicts works on one machine, breaks on another So I built PyHarmony 🚀 An open-source CLI tool to make Python dependency setup painless. What it does: ✅ Scans project imports ✅ Detects third‑party libraries ✅ Maps tricky imports to pip packages (sklearn → scikit-learn) ✅ Creates/uses virtual environments ✅ Installs missing packages ✅ Checks for broken dependencies ✅ Generates requirements.txt 👉 Try it now: https://lnkd.in/gBjPxbVx Next steps: Handle version conflicts better Notebook support Lock file support PyPI publishing Maybe a VS Code extension I’d love your thoughts: 👉 What’s the most frustrating dependency issue you’ve faced in Python? 👉 What should PyHarmony solve first? #Python #OpenSource #PyHarmony #DeveloperTools #PythonDevelopment #CLI #SoftwareDevelopment #BuildInPublic #DevTools #Programming #Automation #AI #DataScience #LearningByBuilding #TechProjects

💭 I still remember my first Python program… It was just one line: print("Hello, World!") Nothing fancy. No big achievement. But somehow… it felt powerful. Like I had just unlocked a new language—one that computers understand. At first, Python looked too simple. No complex syntax, no overwhelming rules… just clean, readable code. But that simplicity? That’s where the real magic was hiding. Slowly, “Hello World” turned into small scripts… Scripts turned into projects… And projects turned into confidence. 🐍 Python isn’t just a programming language. It’s a starting point. A gateway into AI, Data Science, Automation, Web Development, and so much more. And the best part? You don’t need to be a genius to start. Just curious enough to try. ✨ Every expert was once a beginner staring at a blinking cursor. So if you’ve been thinking about starting… This is your sign. #Python #CodingJourney #LearnToCode #Programming #TechStory #DeveloperLife #AI #DataScience #CareerGrowth🚀

🚀 DSA Journey – Day 2 | Conditional Logic, Ternary Operator & Pythonic Optimization Today’s DSA practice focused on improving conditional logic and writing cleaner Python code. 📌 Topics covered: Even / Odd number check Pass / Fail logic using marks Ternary operator any() for optimized conditions Basic list-based condition checking 🐍 Problem 1: Even or Odd Started with a normal if-else approach and then optimized it using a reusable function and ternary operator. def is_even(n): return n % 2 == 0 print("even" if is_even(8) else "odd") 💡 Key learning: The ternary operator helps write short and clean conditional expressions. Example format: value_if_true if condition else value_if_false 📌 Problem 2: Pass / Fail using marks I first solved it using brute-force loops and counters, then optimized it using Python’s built-in any() function. def is_pass(marks: list): return any(i >= 35 for i in marks) print("pass" if is_pass([77, 15, 17]) else "fail") ⚡ What I learned today Writing shorter and cleaner conditions Replacing loops with optimized built-in functions Better readability using ternary expressions Thinking in a more Pythonic way 🔗 GitHub Code: https://lnkd.in/g9-HTPUP Day by day, I’m focusing on improving both logic building and clean coding practices. #DSA #Python #CodingJourney #100DaysOfCode #ProblemSolving #GitHub #LearningInPublic

Day 14 🔥 — Python Problem Solving Practice Continuing my daily coding journey, today I focused on nested loop problems and improving my understanding of how to handle data step by step. Today’s practice helped me become more clear about how loops work inside loops and how to control them properly. Problems Practiced: • Transpose of a Matrix (columns becomes rows) • Unique Pair Combinations from a List • Common Characters Between Two Strings Concepts Practiced: • Nested loops (loop inside loop) • Working with 2D data (rows and columns) • Avoiding duplicate pairs using index logic • Comparing elements step by step • Understanding how data flows inside loops Today’s learning made me realize that nested loops are not difficult if we think in a simple way: “for each element, check with others”. This thinking is helping me solve problems more confidently without copying code. venubabu vajja 10000 Coders Rudra Sravan kumar #Python #ProblemSolving #CodingPractice #10KCoders #DeveloperJourney

🚀 Day 14 of My Python Learning Journey Yesterday’s session was all about strengthening my understanding of loops and data type conversions — and honestly, it helped me connect multiple concepts together. 🔹 What I learned: How for loops work with range(start, end, step) Generating sequences like even numbers using step values Converting between data types: String → int, list, tuple Int → string, float List ↔ tuple, tuple → list List of tuples → dictionary Reversing a string using loops and slicing Checking for palindrome strings Writing logic to identify even and odd numbers 🔹 Key takeaway: Understanding loops deeply makes problem-solving much easier. Small tasks like reversing a string or checking palindrome really build strong logic 💡 📌 Practiced multiple mini problems to strengthen fundamentals and improve coding confidence. Consistency is starting to pay off — one step closer to becoming a better developer 🚀 #Python #LearningJourney #Coding #100DaysOfCode #Programming #DeveloperGrowth Codegnan BhanuTeja Garikapati

🚀 Python Journey — Day 15 | Advanced List Logic with Functions Today I continued practicing functions by solving more advanced list-based logical problems. Problems I solved : • Find second largest number in a list • Find second smallest number in a list • Copy elements from one list to another • Print all prime numbers from a list • Replace all zero values with a given number • Check whether all elements in a list are same • Find frequency of all elements in a list • Flatten a nested list into a single list • Split a list into even and odd lists • Find pairs of elements with a given sum • Remove all odd numbers from a list • Remove all even numbers from a list • Multiply all list elements by a fixed number • Find difference between maximum and minimum values • Check whether a list is empty I implemented these problems using functions, loops, and conditional logic to strengthen my understanding of advanced list manipulation and structured problem solving. Thanks to Rudra Sravan kumar sir for the guidance and continuous support. Learning daily and getting more confident On to Day 16 #Python #PythonDeveloper #LogicBuilding #10000Coders #Coding #LearningJourney #ProblemSolving #CodeEveryDay #KeepLearning

🚀 Day 14 – Mastering Python Comprehensions & Lambda Functions 🔥 Today I explored one of the most powerful and Pythonic concepts – List Comprehension, Dictionary Comprehension & Lambda Functions. This session helped me understand how to write clean, concise, and efficient code by replacing traditional loops with smarter approaches. 🔹 List Comprehension ✔ Creating lists in a single line ✔ Using conditions (if, if-else, if-elif-else) ✔ Nested loops & flattening lists 🔹 Dictionary Comprehension ✔ Efficient key–value creation ✔ Filtering & conditional mapping ✔ Transforming and combining data 🔹 Lambda Functions ✔ Anonymous functions for quick operations ✔ Used with map(), filter(), sorted() ✔ Applying conditions & real-time logic 📦 Advanced Applications: ✔ Nested comprehensions for complex structures ✔ Conditional logic handling inside expressions ✔ Filtering prime numbers using optimized logic ✔ Writing clean and optimized Python code 💡 This topic made me realize how important it is to: • Write readable and optimized code • Think in a Pythonic way • Solve problems efficiently in real-world scenarios 🙏 A special thanks to my mentor Nallagoni Omkar for the continuous guidance and clear explanations. ➡️ Next Topic: Advanced Python Concepts / Class, Objects(OOPS) 🚀 #Python #ListComprehension #DictionaryComprehension #LambdaFunction #LearningJourney #DataScience #Programming #PythonDeveloper #Coding