Pavithra M’s Post

Python Tip – Day 6: Make Your Loops Cleaner with enumerate() Ever used range(len()) to get both index and value in a loop? There’s a better and more Pythonic way , use enumerate()! Here’s a quick example: x = [1, 2, 3, 4, 5, 6] s = 0 for i in enumerate(x): print(i[0], i[1]) enumerate() returns both the index and value as a tuple! That’s why i[0] gives the index and i[1] gives the list element. Try unpacking it directly for cleaner code: for index, value in enumerate(x): print(index, value) enumerate() improves readability and makes your code look more professional. Keep your loops clean and efficient! #Python #30DaysOfpythonCode #PythonTips #CodingJourney #LearnPython #CodeBetter

Python Day 5 Tip: Difference Between append() and extend() Both are used to add elements to a list , but they work differently! # Example list1 = [1, 2, 3] list1.append([4, 5]) print(list1) #output is [1, 2, 3, [4, 5]] list1 = [1, 2, 3] list1.extend([4, 5]) print(list1) #output is [1, 2, 3, 4, 5] 1) append() adds the entire object as a single element. 2) extend() adds each element from the iterable individually. Tip: Use append() for single items and extend() for adding multiple items at once. #Python #30DaysOfpythonCode #PythonTips #Coding #FullStackDeveloper #LearnPython #PythonLearning

Problem: LeetCode 98 — Validate Binary Search Tree In this video, we solve the “Validate Binary Search Tree” problem using a Depth-First Search (DFS) approach in Python. We check whether a binary tree satisfies the BST property where every node’s left subtree contains only values less than the node, and every right subtree contains only values greater than the node. Approach: We use recursion with lower and upper bounds (low and high) to ensure each node’s value stays within valid limits as we traverse the tree. Topics Covered: Depth-First Search (DFS) Binary Tree validation logic Recursion in Python Complexity: Time: O(n) - We only visit each node once Space: O(h) - where h is the height of the tree If you’d like to see more walkthroughs like this, subscribe to my channel I’m posting new LeetCode and Python videos pretty often! Original Video: https://lnkd.in/ep82Uf9A #LeetCode #LeetCode98 #ValidateBinarySearchTree #ValidateBST #BinarySearchTree #Python #DFSTraversal #DepthFirstSearch #Recursion #CodingInterview #InterviewPrep #SoftwareEngineering #DataStructures #Algorithms #BinaryTree #PythonCoding #LeetCodePython #ProblemSolving #TechnicalInterview #Programming #DeveloperCommunity #CodeNewbie #100DaysOfCode #CodingChallenge #LearnToCode

Day 41 – Scope in Python: Local vs Global Variables Ever got a “NameError” and wondered why Python couldn’t find your variable? 🤔 It’s all about Scope — where a variable lives and breathes. x = 10 # Global variable def show(): x = 5 # Local variable print("Inside function:", x) show() print("Outside function:", x) 🧩 Output: Inside function: 5 Outside function: 10 ➡️ Local variables exist only inside the function. ➡️ Global variables exist everywhere. Use them wisely — globals are powerful but can cause confusion if overused. 👉 Tip: Prefer local scope for clean and bug-free code. #Python #Coding #Learning #100DaysOfCode #PythonTips

PYTHON JOURNEY..Day - 9/50 TOPIC : Logical Operators in Python Logical operators are used to combine conditional statements and make smarter decisions in our code. There are 3 Logical Operators: 1. and → Returns True if both conditions are true 2. or → Returns True if any one condition is true 3. not → Reverses the result (True → False, False → True) Example: a = 10 b = 5 c = 15 # AND operator print(a > b and a < c) # True # OR operator print(a > b or a > c) # True # NOT operator print(not(a > b)) # False Output: True True False Quick Tip: Use logical operators to combine multiple conditions in loops or if-statements — they make your code cleaner and smarter! --- #Python #50DaysOfCode #PythonLearning #LogicalOperators #LearnPython #LinkedInLearning

Python programm to reverse number using class as below: #Defining python class class Number_Reverse: # Initializing the number in class object     def __init__(self, num):         self.num = num # define class method to perfor reverse the number      def reverse_num(self):         return int(str(self.num)[::-1]) # Creating class object and calling reverse_num method if __name__ == "__main__":     num = 123456789 # Defining the class object     t = Number_Reverse(num)     print(t.reverse_num())

🚀 Day 18 of my #100DaysOfCode Journey – Exploring Python Modules 🐍 Today’s focus was on Python Modules, both built-in and custom! Here’s what I practiced: ✅ Standard Library (math module) – Calculated square root, factorial, and rounded pi value. ✅ Random Module – Generated random choices and shuffled lists dynamically. ✅ Custom Module – Created my own calculator.py with add() and sub() functions, then imported it into the main file. 💡 Key Takeaway: “Modules make Python more powerful, organized, and reusable — write once, use everywhere!” #Python #100DaysOfCode #Modules #LearningJourney #SoftwareDevelopment #CodingEveryday #Math #Random #CustomModules #CodeNewbie

🚀 Day 18 of my #100DaysOfCode Journey – Exploring Python Modules 🐍 Today’s focus was on Python Modules, both built-in and custom! Here’s what I practiced: ✅ Standard Library (math module) – Calculated square root, factorial, and rounded pi value. ✅ Random Module – Generated random choices and shuffled lists dynamically. ✅ Custom Module – Created my own calculator.py with add() and sub() functions, then imported it into the main file. 💡 Key Takeaway: “Modules make Python more powerful, organized, and reusable — write once, use everywhere!” #Python #100DaysOfCode #Modules #LearningJourney #SoftwareDevelopment #CodingEveryday #Math #Random #CustomModules #CodeNewbie

💡 Confusing Yet Powerful Python String Methods Simplified! Ever been confused between capitalize() and title()? Or wondered what casefold() actually does differently from lower()? 😅 I’ve put together a quick cheat sheet of Python string methods that often trip people up complete with examples and outputs! Perfect for beginners and anyone brushing up for interviews or projects. 🚀 #Python #Coding #DataScience #PythonTips #LearnPython #Programming #PythonDeveloper #CodeNewbie #WomenInTech #MachineLearning #CheatSheet #PythonStringMethods #DataAnalyst #Developers #TechLearning

🐍 Day 17 of My #50DaysOfPython Challenge 🔗 Task: Find Common Elements Between Two Lists Today’s task was all about exploring the power of sets in Python. This helped me understand how sets simplify comparing data, removing duplicates, and finding common elements efficiently. 💡 What I Learned: 🔹 How to take multiple list inputs using .split() 🔹 How to convert lists into sets for faster operations 🔹 Using intersection() to find shared values between sets 🔹 Converting sets back to lists for cleaner output 🧠 Example: Input: List 1 → 1 2 3 4 5 List 2 → 4 5 6 7 8 Output: Common elements: ['4', '5'] 🧰 Concepts Covered: ✅ List and Set Conversion ✅ Intersection Operation ✅ Data Comparison Logic ✅ Duplicate Removal #Python #CodingChallenge #LearningInPublic #50DaysOfPython #ProgrammingJourney