Understanding Python Inheritance: A Quick Guide

“Python Day-3 — Mastering Lists, Tuples, and Dictionaries” > Built my foundation in Python data structures today. <> Learned string for string manipualtion as like len and indexing <> Practiced lists for dynamic storage and slicing. <> Learned tuples for fixed data. <> Explored dictionaries for key-value mapping — perfect for real-world datasets. Understanding how to store and organize data efficiently is step one in data science. #Python #DataStructures #Programming #DataScience

📒 Learning Log: Python's Lambda and map() Functions Today's study session on #DataCamp was a deep dive into Python's lambda functions and the powerful map() function. Here's what I learned: 🔹 Lambda Functions: These are small, anonymous (nameless) functions. I now see them as "disposable" tools, perfect for a one-time use, especially when passing a simple function as an argument to another function. 🔹 The map() Function: map() is a highly efficient way to apply a function to every item in an iterable. Excited to use these concepts to write more efficient and "Pythonic" code. #Python #DataScience #LearningJournal

🐍 Exploring the id() Function in Python — Understanding How Objects Live in Memory! Today, I learned about one of Python’s simplest yet most interesting built-in functions: id(). This function returns the unique identity (or memory address) of an object — helping us understand how Python stores and manages data internally. 🔍 What I learned: ✔️ Every variable in Python is actually a reference to an object in memory. ✔️ id() shows where that object is stored. ✔️ If two variables have the same ID, they point to the same object. ✔️ This is especially useful for understanding mutable vs immutable data types in Python. Learning this helped me see Python from a deeper perspective — not just how code works, but how Python thinks behind the scenes. A huge thanks to Talal Ahmed for explaining this concept so clearly and making it easy to understand the internal mechanics of Python. 🙌 #Python #Programming #LearningJourney #PythonBasics #idFunction #TechSkills #SMIT #AgenticAI

🚀 Day 7 of my 30-Day Python Mastery Challenge! Today, I explored Lists — one of the most powerful and flexible data structures in Python. Lists allow you to store multiple items, modify them easily, and handle complex data with simplicity. Here’s a quick example I practiced today: fruits = ["apple", "banana", "mango"] fruits.append("orange") print(fruits) Key Takeaways: Lists are ordered and mutable. You can add, remove, or modify elements easily. They’re widely used in data storage and processing. 💪 Next up → Day 8: Tuples in Python #Day7 #Python #LearnToCode #CodingJourney #PythonForBeginners #PythonLists #100DaysOfCode #JaswanthLearnsPython #PythonProgramming #PythonChallenge #DevOps #LearningJourney

🐍 Day 2 of my 30-Day Python Mastery Challenge! Today I explored variables and data types — the building blocks of Python. 💻 I learned how to store, modify, and convert data types like integers, floats, strings, and booleans. Example snippet: name = "Jaswanth" age = 23 print("My name is", name, "and I am", age, "years old.") 🧠 Key Takeaways: • Variables store values for later use • Python automatically detects data types • Type conversion helps combine different data forms Next up → Day 3: Operators in Python! ⚙️ #Day2 #Python #CodingJourney #LearnToCode #PythonForBeginners #100DaysOfCode #JaswanthLearnsPython #PythonForDevops #Coding #PythonProgramming

💻 Exploring Python’s zip() Function! 🐍 In this snippet, I used the zip() function to combine multiple lists — names, marks, and departments — into a single dictionary. It’s a simple yet powerful way to handle grouped data efficiently. 📘 Concepts used: ➡️ zip() function ➡️ Type conversion using dict() ➡️ Nested zipping for multiple lists Always fun to see how Python makes data handling so elegant and readable! ✨ #Python #Coding #Programming #Learning #DataHandling #zipfunction @10000coders @batula venkata narayana

PYTHON JOURNEY - Day 16 of 50 !! TOPIC : The else Clause in Loops Did you know? Python loops can have an else block — and it’s not what most people think! The else part in a loop runs only when the loop completes normally (without a break). --- Example 1 — With for Loop for i in range(1, 6): print(i) else: print("Loop completed successfully ") Output: 1 2 3 4 5 Loop completed successfully --- Example 2 — Using break for i in range(1, 6): if i == 3: break print(i) else: print("Loop completed successfully ") Output: 1 2 The else block didn’t execute because the loop was broken early. --- Quick Tip: Use the loop else to handle cases when a loop ends naturally, like searching for an item — if not found, execute the else. --- #Python #LearnPython #ForLoop #WhileLoop #PythonBasics #Coding #PythonTips #LinkedInLearning

File handling in python Day 46 – Reading a File in Python Most data you’ll ever process lives in files — text, CSVs, logs, configs, you name it. Let’s start with reading a file 👇 # sample.txt content: # Hello Python Learner! file = open("sample.txt", "r") content = file.read() print(content) file.close() 🧠 Output: Hello Python Learner! ✅ Tip: Always close your file after reading to free up system resources. (Or better yet, use with open() — coming next!) 👉 Have you ever tried reading a large file in Python? #Python #FileHandling #100DaysOfCode #Learning

🐍𝐖𝐡𝐚𝐭 𝐈 𝐥𝐞𝐚𝐫𝐧𝐞𝐝 𝐭𝐨𝐝𝐚𝐲: The difference between 𝐢𝐬 and == in python and how one tiny detail can change your program’s logic. A while back, I wrote code that compared two lists: a = [1, 2, 3] b = [1, 2, 3] print(a == b) # True print(a 𝐢𝐬 b) # False At first, I couldn’t understand why one was True and the other False. Then it clicked 💡 == checks if values are equal. 𝐢𝐬 checks if both variables point to the 𝐬𝐚𝐦𝐞 𝐨𝐛𝐣𝐞𝐜𝐭 𝐢𝐧 𝐦𝐞𝐦𝐨𝐫𝐲. They looked identical, but Python knew the difference. 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲: Use == when comparing data, and 𝐢𝐬 when checking object identity (like 𝐢𝐬 𝐍𝐨𝐧𝐞). Tiny lessons like this remind me how deep Python really is. 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧: What’s a small Python concept that once confused you but now feels obvious? #Python #LearningInPublic #Programming #DailyLearning #DataScience #CareerGrowth