Mastering Python Strings: Types and Usage

Day 3 – Variable Scope in Python 📌 What is Variable Scope? Variable Scope = Where a variable can be accessed in a program. In simple words: Scope decides who can use the variable and where. 📏 Rules for Variable Scope Python follows the LEGB Rule when searching for a variable: 1️⃣ L – Local 2️⃣ E – Enclosing 3️⃣ G – Global 4️⃣ B – Built-in Python searches in this order. If not found → NameError 1️⃣ Local Scope 👉 Variable defined inside a function 👉 Accessible only inside that function def greet(): name = "prem" # Local scope print(name) greet() ❌ Cannot access outside: print(name) # NameError 2️⃣ Enclosing Scope 👉 When you have a function inside another function 👉 Inner function can access outer function variable example: def outer(): message = "Hi how are you" def inner(): print(message) # Enclosing scope inner() outer() 3️⃣ Global Scope 👉 Variable defined outside all functions 👉 Accessible everywhere (read access) x = 10 # Global scope def show(): print(x) show() 4️⃣ Built-in Scope 👉 Predefined names in Python Examples: print() len() sum() int() print("hello world") print(len("python")) Python finds these in Built-in scope. 🔥 Combined LEGB Example (Very Important) x = "Global" def outer(): x = "Enclosing" def inner(): x = "Local" print(x) inner() outer() Output: Local Why? Python search order: Local → Enclosing → Global → Built-in It finds "Local" first. 🏢 Where We Use Variable Scope in Industry? ✅ Backend API development → Local variables inside request handling ✅ Microservices → Global config variables ✅ AI projects → Enclosing scope for nested processing functions ✅ Data pipelines → Avoid global variables to prevent bugs ✅ Threading & async programming → Scope prevents data conflicts Good scope management = Clean architecture 🚀 LinkedIn Post (Ready to Copy & Post) Here’s your engagement-style post: 🔥 Day 3 of Python Mastery – Variable Scope & LEGB Rule Do you know how Python searches for variables? Python follows the LEGB rule: L → Local E → Enclosing G → Global B → Built-in Example: x = "Global" def outer(): x = "Enclosing" def inner(): x = "Local" print(x) inner() outer() Output → Local Because Python searches in this order: Local → Enclosing → Global → Built-in Understanding scope is crucial in: • Backend development • Microservices • AI systems • Async programming • Clean architecture design Bad scope management = Hidden bugs Good scope management = Production-ready code Learning step by step. Building strong fundamentals. more information follow Prem chandar #Python #BackendDevelopment #AI #FullStackDeveloper #FastAPI #Programming #SoftwareEngineering #MachineLearning #network #brand #love teach #student #social media

𝐂𝐨𝐫𝐞 𝐏𝐲𝐭𝐡𝐨𝐧 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 & 𝐀𝐧𝐬𝐰𝐞𝐫𝐬 | 𝐄𝐥𝐞𝐚𝐫𝐧 𝐈𝐧𝐟𝐨𝐭𝐞𝐜𝐡 Preparing for Python interviews? Here are some must-know Core Python interview questions every student should be confident with 👇 1. What is Python? Python is a high-level, interpreted, object-oriented programming language that is easy to learn and widely used for web development, data science, automation, and AI. 2. What is the difference between list and tuple? List: Mutable (can be changed) Tuple: Immutable (cannot be changed) Example: lst = [1, 2, 3] tup = (1, 2, 3) 3. What are Python variables? Variables are used to store data. Python does not require data type declaration. Example: x = 10 name = "Python" 4. What is None in Python? None represents no value or null value. It is often returned by functions that do not explicitly return anything. 5. What is the difference between == and is? == → compares values is → compares memory locations 6. What are mutable and immutable data types? Mutable: list, dict, set Immutable: int, float, string, tuple 7. What is a function in Python? A function is a block of reusable code that performs a specific task. Example: def add(a, b):   return a + b 8. What is a Python dictionary? A dictionary stores data in key–value pairs. Example: student = {"name": "John", "age": 20} 9. What is len() function? len() returns the number of elements in a sequence. Example: len([1, 2, 3]) # Output: 3 10. What is slicing in Python? Slicing is used to extract a part of a sequence. Example: text = "Python" print(text[1:4]) # yth 11. What is OOP? OOP (Object-Oriented Programming) is a programming approach based on classes and objects. Main principles: Encapsulation Inheritance Polymorphism Abstraction 12. What is inheritance? Inheritance allows a class to reuse properties and methods of another class. 13. What is break and continue? break → exits the loop continue → skips current iteration 14. What is a module in Python? A module is a file containing Python code (functions, variables, classes). Example: import math 💡 These questions are commonly asked in freshers & junior developer interviews. At Elearn Infotech, we focus on concept clarity + real interview preparation, not just syntax. 👉 Want more Python interview questions, quizzes, and polls? Comment PYTHON below 👇 #ElearnInfotech #PythonInterview #CorePython #LearnPython #PythonTraining #Freshers #SoftwareTraining #Coding #ITCareers #SkillUp

🐍 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗶𝗻𝗴 𝗣𝘆𝘁𝗵𝗼𝗻 𝘄𝗶𝘁𝗵 𝗮 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗹𝗼𝗴𝗶𝗰-𝗯𝗮𝘀𝗲𝗱 𝗽𝗿𝗼𝗴𝗿𝗮𝗺 I built a small Python program that simulates a railway ticket booking system using basic Python concepts. 𝗧𝗵𝗶𝘀 𝘀𝗰𝗿𝗶𝗽𝘁: Takes user input (name, age, gender) Handles invalid input using try-except Automatically generates a PNR number Assigns berths using the random module Applies conditional logic to decide ticket price and berth preference based on age and gender 💡 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝘂𝘀𝗲𝗱 𝗶𝗻 𝘁𝗵𝗶𝘀 𝗽𝗿𝗼𝗴𝗿𝗮𝗺: User input handling Exception handling (try / except) Conditional statements (if-elif-else) Random number generation Real-world rule-based logic Building small projects like this really helps in understanding how Python works beyond syntax — especially decision-making and flow control. 𝗛𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝗰𝗼𝗱𝗲 👇 ''' import random name=input("enter your name : ") try: age = int(input("Enter your age: ")) except ValueError: print("Invalid age entered. Please enter a number.") exit() Gender=input("enter your gender : ") berths = ["Lower", "Middle", "Upper", "Side Lower", "Side Upper"] assigned_berth = random.choice(berths) pnr = random.randint(1000000000, 9999999999) print(f"PNR Number: {pnr}") if age >= 80: assigned_berth = "Lower" else: assigned_berth = random.choice(berths) if age >=80 and age<100: print(f"your gender is :{Gender}") if Gender=='male': print("price is 200") print(f"your berth is : {assigned_berth}") else: print("price is 150") print(f"your berth is : {assigned_berth}") elif age<80 and age>=60: print(f"your gender is :{Gender}") if Gender=='male': print("price is 500") print(f"your berth is : {assigned_berth}") else: print("price is 450") print(f"your berth is : {assigned_berth}") elif age<60 and age>=30: print(f"your gender is :{Gender}") if Gender=='male': print("price is 2000") print(f"your berth is : {assigned_berth}") else: print("price is 1500") print(f"your berth is : {assigned_berth}") else: print(f"your gender is :{Gender}") if Gender=='male': print("price is 20") print(f"your berth is : {assigned_berth}") else: print("price is 15") print(f"your berth is : {assigned_berth}") ''' 📌 Still learning, experimenting, and improving every day. Would love feedback or suggestions to make this code cleaner or more efficient! #Python #LearningPython #Programming #CodeNewbie #PythonProjects #DeveloperJourney #AIForTechies #TechLearning

As I go deeper into Python, I’m realizing that learning to code isn’t just about writing lines of syntax - it’s about learning how to organize information, ask better questions, and think in structures. This phase of my journey introduced me to Data Structures & Functions, and one concept stood out immediately: 𝐁𝐞𝐲𝐨𝐧𝐝 𝐕𝐚𝐫𝐢𝐚𝐛𝐥𝐞𝐬: 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐢𝐧𝐠 𝐋𝐢𝐬𝐭𝐬. I like to think of a variable as a single grocery bag - it can only hold one item at a time. A list, on the other hand, is a shopping trolley. It holds multiple items, keeps them organized, and lets you access any item whenever you need it. In Python, lists are written using 𝒔𝒒𝒖𝒂𝒓𝒆 𝒃𝒓𝒂𝒄𝒌𝒆𝒕𝒔 [], with items separated by commas. Simple syntax, powerful idea. Suddenly, I wasn’t just working with single values - I was managing collections of data. 𝐈𝐧𝐝𝐞𝐱𝐢𝐧𝐠: 𝐓𝐡𝐞 “𝐙𝐞𝐫𝐨 𝐑𝐮𝐥𝐞” (𝐓𝐡𝐞 𝐏𝐚𝐫𝐭 𝐓𝐡𝐚𝐭 𝐓𝐫𝐢𝐩𝐬 𝐄𝐯𝐞𝐫𝐲𝐨𝐧𝐞 𝐔𝐩) One of the first mindset shifts was understanding indexing. In Python, counting doesn’t start at 1 - it starts at 0. That means: The first item in a list is at index 0 The second item is at index 1 The third is at index 2, and so on It feels strange at first, but it’s non-negotiable in most programming languages. To access any item, you simply place the index inside square brackets after the list name. Once this clicks, lists suddenly feel predictable and logical. 𝐒𝐥𝐢𝐜𝐢𝐧𝐠: 𝐆𝐞𝐭𝐭𝐢𝐧𝐠 𝐚 𝐂𝐡𝐮𝐧𝐤 𝐨𝐟 𝐃𝐚𝐭𝐚. Indexing lets you grab one item, but slicing is where things get really interesting. Slicing allows you to extract a range of items from a list. I imagine it like cutting a sandwich — you decide where to start cutting and where to stop, and Python hands you that section neatly. Even better, Python offers slicing shortcuts. These shorthand patterns make your code cleaner, faster to write, and easier to read. It’s one of those moments where you realize programmers value efficiency just as much as correctness. 𝐌𝐨𝐝𝐢𝐟𝐲𝐢𝐧𝐠 𝐋𝐢𝐬𝐭𝐬: 𝐁𝐞𝐜𝐚𝐮𝐬𝐞 𝐃𝐚𝐭𝐚 𝐂𝐡𝐚𝐧𝐠𝐞𝐬 Unlike some data structures, lists are mutable — meaning they can change after creation. You can add items, remove them, rearrange them, or update values entirely. Python makes this easy with built-in list methods and functions that handle common operations. Instead of reinventing the wheel, you focus on the logic and let Python do the heavy lifting. 𝐌𝐨𝐝𝐢𝐟𝐲𝐢𝐧𝐠 𝐋𝐢𝐬𝐭𝐬: 𝐁𝐞𝐜𝐚𝐮𝐬𝐞 𝐃𝐚𝐭𝐚 𝐂𝐡𝐚𝐧𝐠𝐞𝐬 This was a big “𝒂𝒉𝒂” moment. List comprehension provides a concise and elegant way to create new lists from existing ones. Instead of writing multiple lines with loops and conditionals, you can express your intent in one clean, readable line. It shifts your thinking from “how do I do this step by step?” to “what do I want to create?”. What I’m learning is that Python isn’t just teaching me syntax - it’s teaching me how to structure data, reason logically, and write code that scales.

I finally understood why Python works — not just how to write it. Today I stopped memorizing syntax and started learning programming from first principles. Here’s what clicked 👇 --- 1️⃣ Functions are not code blocks A function is a mapping: Input → Transformation → Output The real difference I learned: - "print()" → produces a side effect - "return" → produces a value That single distinction explains why many beginner programs “run” but cannot be reused. --- 2️⃣ Scope (this confused me for weeks) Variables don’t belong to a file. They belong to a namespace. Python searches variables in a fixed order: Local → Enclosing → Global → Built-in (LEGB rule) The most interesting part: "nonlocal" lets a child function modify its parent function’s variable without turning it into a global variable. Now closures finally make sense. --- 3️⃣ Recursion (the big breakthrough) Recursion is NOT a loop alternative. It is: «solving a big problem by delegating a smaller version of the same problem to yourself.» Two rules: • Base case (stop condition) • Recursive case (smaller problem) When printing numbers 10 → 1, the secret is not repetition. It is the call stack. Python stores unfinished function calls and resolves them in reverse order. That is why recursion prints backwards when unwinding. This was my “aha moment”. --- 4️⃣ Control statements - "break" → terminate loop - "continue" → skip iteration - "pass" → structural placeholder Simple — but critical for writing predictable programs. --- 5️⃣ Yield (Generators) The most powerful concept today. "return" → ends a function "yield" → pauses a function A generator does lazy evaluation: it creates values only when requested. Meaning: a list stores all values in memory a generator streams values one-by-one. This is why large-data pipelines in data science prefer generators. --- Today I realized: Coding is not typing instructions. Programming is controlling state and execution flow. Tomorrow I’m starting recursion problems: factorial, Fibonacci, and tracing the call stack manually. --- If you struggled with recursion or "yield" before, what was the exact point where it didn’t click? I’d genuinely like to know 👇 #Python #LearnInPublic #CodingJourney #ComputerScience #100DaysOfCode #DataScienceJourney #ProgrammingBeginners #Developers #TechLearning

🚀 𝗔𝗻 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝘁𝗼 𝗣𝘆𝘁𝗵𝗼𝗻 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀 (𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿-𝗙𝗿𝗶𝗲𝗻𝗱𝗹𝘆) Python functions are one of the most powerful building blocks in programming. If you’ve ever seen a math function like 𝘇 = 𝗳(𝘅, 𝘆), you already understand the idea. In Python, a 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻 is a reusable, named block of code that performs a specific task. Python gives us many built-in functions like 𝗹𝗲𝗻(), and we can also create our own 𝘂𝘀𝗲𝗿-𝗱𝗲𝗳𝗶𝗻𝗲𝗱 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀. 🔑 𝗪𝗵𝘆 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀 𝗠𝗮𝘁𝘁𝗲𝗿 Functions make your code: • 𝗥𝗲𝘂𝘀𝗮𝗯𝗹𝗲 (𝗗𝗥𝗬 𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲): Write once, use many times. • 𝗠𝗼𝗱𝘂𝗹𝗮𝗿: Break large problems into smaller, manageable pieces. • 𝗔𝗯𝘀𝘁𝗿𝗮𝗰𝘁: Hide complexity behind simple, readable interfaces. 🧠 𝗗𝗲𝗳𝗶𝗻𝗶𝗻𝗴 𝗮 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻 Functions are defined using the 𝗱𝗲𝗳 keyword: Ex: 𝗱𝗲𝗳 𝗴𝗿𝗲𝗲𝘁(𝗻𝗮𝗺𝗲): 𝗽𝗿𝗶𝗻𝘁(𝗳"𝗛𝗲𝗹𝗹𝗼, {𝗻𝗮𝗺𝗲}!") Call it using: 𝗴𝗿𝗲𝗲𝘁("𝗣𝘆𝘁𝗵𝗼𝗻𝗶𝘀𝘁𝗮") 📌 𝗣𝗮𝗿𝗮𝗺𝗲𝘁𝗲𝗿𝘀 𝘃𝘀 𝗔𝗿𝗴𝘂𝗺𝗲𝗻𝘁𝘀 • 𝗣𝗮𝗿𝗮𝗺𝗲𝘁𝗲𝗿𝘀 → variables in the function definition • 𝗔𝗿𝗴𝘂𝗺𝗲𝗻𝘁𝘀 → actual values passed during function calls 🎯 𝗣𝗮𝘀𝘀𝗶𝗻𝗴 𝗔𝗿𝗴𝘂𝗺𝗲𝗻𝘁𝘀 • 𝗣𝗼𝘀𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗮𝗿𝗴𝘂𝗺𝗲𝗻𝘁𝘀: Order matters • 𝗞𝗲𝘆𝘄𝗼𝗿𝗱 𝗮𝗿𝗴𝘂𝗺𝗲𝗻𝘁𝘀: Clear, readable, order doesn’t matter Ex: 𝗰𝗮𝗹𝗰𝘂𝗹𝗮𝘁𝗲_𝗰𝗼𝘀𝘁(𝗶𝘁𝗲𝗺="𝗯𝗮𝗻𝗮𝗻𝗮𝘀", 𝗾𝘂𝗮𝗻𝘁𝗶𝘁𝘆=𝟲, 𝗽𝗿𝗶𝗰𝗲=𝟬.𝟳𝟰) 🔄 𝗥𝗲𝘁𝘂𝗿𝗻𝗶𝗻𝗴 𝗩𝗮𝗹𝘂𝗲𝘀 Functions can: • Cause side effects (e.g., printing) • Or return values using 𝗿𝗲𝘁𝘂𝗿𝗻 (recommended) If no value is returned, Python returns 𝗡𝗼𝗻𝗲. Functions can also return multiple values as tuples. ⚙️ 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀 • 𝗗𝗲𝗳𝗮𝘂𝗹𝘁 𝗮𝗿𝗴𝘂𝗺𝗲𝗻𝘁𝘀: Make parameters optional • *𝗮𝗿𝗴𝘀 & **𝗸𝘄𝗮𝗿𝗴𝘀: Handle variable numbers of arguments • 𝗔𝘃𝗼𝗶𝗱 𝗺𝘂𝘁𝗮𝗯𝗹𝗲 𝗱𝗲𝗳𝗮𝘂𝗹𝘁 𝗮𝗿𝗴𝘂𝗺𝗲𝗻𝘁𝘀: Use None as a safe pattern 🧾 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 • 𝗗𝗼𝗰𝘀𝘁𝗿𝗶𝗻𝗴𝘀: Explain what your function does, its inputs, and outputs • 𝗧𝘆𝗽𝗲 𝗵𝗶𝗻𝘁𝘀: Improve readability and catch bugs early (not enforced at runtime) ⏳ 𝗔𝘀𝘆𝗻𝗰 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀 (𝗤𝘂𝗶𝗰𝗸 𝗜𝗻𝘁𝗿𝗼) Defined with 𝗮𝘀𝘆𝗻𝗰 𝗱𝗲𝗳, used for I/O-heavy tasks like APIs or file reads, allowing efficient non-blocking execution. ✅ 𝗙𝗶𝗻𝗮𝗹 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆 Functions help you write 𝗰𝗹𝗲𝗮𝗻, 𝗿𝗲𝗮𝗱𝗮𝗯𝗹𝗲, 𝗿𝗲𝘂𝘀𝗮𝗯𝗹𝗲, 𝗮𝗻𝗱 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 Python code. Mastering them is a major milestone in your Python journey. If you’re learning Python or data analytics—this is a skill you’ll use every single day. 💬 𝗪𝗵𝗮𝘁 𝗰𝗼𝗻𝗰𝗲𝗽𝘁 𝗵𝗲𝗹𝗽𝗲𝗱 𝘆𝗼𝘂 𝗺𝗼𝘀𝘁 𝘄𝗵𝗲𝗻 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀? #Python #LearnPython #Coding #DataAnalytics #Upskilling #Programming

Python Explained, From Zero to “Why Everyone Uses It” If you’ve heard “Learn Python” a thousand times and still wondered what exactly Python is and why it’s everywhere, this post is for you. What is Python? Python is a high-level, interpreted programming language designed to be: Easy to read Easy to write Powerful enough for real-world systems Its philosophy is simple: “Write less code, do more work.” That’s why beginners love it, and experts rely on it. 🧩 What Can Python Be Used For? Python isn’t limited to one domain. It’s a general-purpose language, used in: 🌐 Web Development (Django, Flask, FastAPI) 📊 Data Analysis & Visualization (Pandas, NumPy, Matplotlib) 🤖 AI & Machine Learning (TensorFlow, PyTorch, Scikit-learn) 🧠 Deep Learning & NLP (Transformers, spaCy, OpenAI tools) 🕸️ Web Scraping & Automation (Selenium, BeautifulSoup) ☁️ Cloud, DevOps & Scripting 🎮 Game Development & Simulations If there’s data, logic, or automation involved, Python fits. What Does Python “Contain”? Python’s real strength comes from its ecosystem: 📦 Standard Library (file handling, networking, math, JSON, threading) 🧩 Third-party packages (pip, PyPI = millions of ready-made tools) 🏗️ Frameworks for almost everything 🌍 Massive community (answers exist before questions are asked) ✍️ Python Basic Syntax (Why It’s So Friendly) Python looks close to plain English: name = "Usama" if name == "Usama": print("Welcome to Python") Key ideas: No curly braces {} No semicolons ; Indentation defines logic Code is readable even for non-programmers This lowers cognitive load, you focus on thinking, not syntax. How Should You Learn Python? A smart learning path looks like this: 1️⃣ Core Basics Variables, data types Conditions & loops Functions Lists, dictionaries, tuples 2️⃣ Intermediate Concepts Modules & packages File handling Error handling OOP (classes & objects) 3️⃣ Choose a Direction Web → Django / FastAPI Data → Pandas / NumPy AI → ML, DL, NLP Automation → Scripts, bots 4️⃣ Build Projects Small → Real → Useful Projects matter more than certificates. ⚖️ Why Python Over Other Languages? Compared to Java, C++, or C#: ✅ Less boilerplate ✅ Faster development ✅ Huge library support ✅ Beginner-friendly ✅ Cross-platform ❌ Slightly slower execution (usually irrelevant) Python optimizes developer time, not just machine time, and that’s priceless. Why Python Dominates AI? Python is the language of AI because: Most AI research is published in Python All major ML/DL libraries are Python-first Easy integration with C/C++ for performance Perfect for experimentation and iteration AI moves fast — Python keeps up. Python is not just a programming language. It’s a tool for thinking, building, automating, and scaling ideas. If you want: A strong foundation Career flexibility A future-proof skill Python is one of the best places to start.

Here are Python programs using while loop for the Number Programs shown in your image. --- ✅ 1. Check whether a number is even or odd n = int(input("Enter number: ")) while True: if n % 2 == 0: print("Even") else: print("Odd") break --- ✅ 2. Sum of numbers between m and n m = int(input("Enter m: ")) n = int(input("Enter n: ")) s = 0 i = m while i <= n: s += i i += 1 print("Sum =", s) --- ✅ 3. Product of numbers between m and n m = int(input("Enter m: ")) n = int(input("Enter n: ")) p = 1 i = m while i <= n: p *= i i += 1 print("Product =", p) --- ✅ 4. Count numbers from m to n m = int(input("Enter m: ")) n = int(input("Enter n: ")) count = 0 i = m while i <= n: count += 1 i += 1 print("Count =", count) --- ✅ 5. Swap two numbers (using third variable) a = int(input("Enter a: ")) b = int(input("Enter b: ")) while True: temp = a a = b b = temp break print("a =", a, "b =", b) --- ✅ 6. Swap two numbers (without third variable) a = int(input("Enter a: ")) b = int(input("Enter b: ")) while True: a = a + b b = a - b a = a - b break print("a =", a, "b =", b) --- ✅ 7. Square of a number n = int(input("Enter number: ")) while True: print("Square =", n*n) break --- ✅ 8. Cube of a number n = int(input("Enter number: ")) while True: print("Cube =", n*n*n) break --- ✅ 9. Factorial using while n = int(input("Enter number: ")) fact = 1 i = 1 while i <= n: fact *= i i += 1 print("Factorial =", fact) --- ✅ 10. Factors of a number n = int(input("Enter number: ")) i = 1 while i <= n: if n % i == 0: print(i, end=" ") i += 1 --- ✅ 11. Fibonacci series using while n = int(input("Enter terms: ")) a, b = 0, 1 i = 1 while i <= n: print(a, end=" ") c = a + b a = b b = c i += 1 --- ✅ 12. Power (x^n) using while x = int(input("Enter base: ")) n = int(input("Enter power: ")) result = 1 i = 1 while i <= n: result *= x i += 1 print("Result =", result) --- ✅ 13. Reverse a number n = int(input("Enter number: ")) rev = 0 while n > 0: digit = n % 10 rev = rev * 10 + digit n //= 10 print("Reverse =", rev) --- ✅ 14. Extract digits (reverse order) n = int(input("Enter number: ")) while n > 0: print(n % 10, end=" ") n //= 10 --- If you want, I can also provide: ✅ Pattern programs using while ✅ Java versions ✅ Simple student version (very short) ✅ Interview version ✅ All programs PDF ✅ More number programs Just tell me 👍

Here are important Python interview questions and answers. 1. What is Python? Answer: Python is a high-level, interpreted, object-oriented programming language known for its simple syntax and readability. It is used in web development, data science, automation, AI, and scripting. 2. What are Python’s key features? Answer: Easy to learn and read Interpreted language Dynamically typed Object-oriented Large standard library Platform independent 3. What is the difference between List and Tuple? Answer: List Tuple Mutable (can change) Immutable (cannot change) Uses [] Uses () Slower Faster Example: [1,2,3] Example: (1,2,3) 4. What is the difference between == and is? Answer: == compares values. is compares memory location (object identity). Example: a = [1,2] b = [1,2] print(a == b) # True print(a is b) # False 5. What is a Dictionary in Python? Answer: A dictionary stores data in key-value pairs. Example: student = {"name": "Keerthi", "age": 24} 6. What are Python data types? Answer: int float str list tuple set dict bool 7. What is a function in Python? Answer: A function is a block of code that performs a specific task. Example: def add(a, b): return a + b 8. What is OOP in Python? Answer: Object-Oriented Programming is a programming style based on objects and classes. Main concepts: Encapsulation Inheritance Polymorphism Abstraction 9. What is the difference between append() and extend()? Answer: append() adds one element. extend() adds multiple elements. Example: a = [1,2] a.append([3,4]) # [1,2,[3,4]] a.extend([3,4]) # [1,2,3,4 10. What is Exception Handling? Answer: It is used to handle runtime errors using try, except, finally. Example: try: print(10/0) except ZeroDivisionError: print("Error occurred") 11. What is Lambda Function? Answer: A small anonymous function written in one line. Example: square = lambda x: x*x 12. What is PEP 8? Answer: PEP 8 is Python’s style guide that explains how to write clean and readable Python code.