OOP vs POP: C vs Python Examples

🚀 Master Logic Building in Python – 6 Phases, Multiple Levels I’m excited to start a new series where we’ll break down the art of logic building in Python into 6 structured phases are follows: 👉Phase 1 – Conditional Thinking (If–Else, Boolean Logic) 👉Phase 2 – Looping & Patterns (Iteration & Flow) 👉Phase 3 – Recursion (Thinking in self- reference) 👉Phase 4 – Basic Arrays(Iterative Logical Thinking) 👉Phase 5 – Strings (Basic Logic Building ) 👉Phase 6 – Mixed Logical Challenges (Applied Reasoning) Whether you’re a beginner or looking to refine your problem-solving mindset, this series will guide you through practical approaches to think, design, and code smarter. ⭕Starting with Phase 1: Level 1🔥 🐱Github : https://lnkd.in/gkKSJKDb #Python #LogicBuilding #CodingMindset #LearningSeries #Learning #Everyday #Coding #Programming

Python Jan 11th's Class – Concepts Covered In one of our recent Python classes, we focused on building strong fundamentals through practical coding exercises. The session covered: 🔹 Arithmetic Operations using Functions Implemented basic operations like addition, subtraction, and multiplication Explored two approaches: Using a single function with conditional logic Using separate functions for each operation with menu-driven input Improved understanding of functions, user input, and control flow (if-elif-else) 🔹 Split Bill Program Designed programs to divide a total bill among friends Practiced multiple approaches using: Functions Integer division String formatting (format() and f-strings) Learned how to write cleaner and reusable code 🔹 Pattern Programming with Loops Created different patterns using nested for loops: Right-angle triangle Reverse right-angle triangle Square pattern Pyramid pattern Strengthened logic building, loop control, and output formatting This class helped me gain confidence in functions, loops, and problem-solving using Python. Step by step, turning logic into code 🚀 #Python #PythonProgramming #Functions #Loops #PatternPrograms #CodingPractice #LearningByDoing Pooja Chinthakayala

🚀 Day 37/100 | #100DaysOfCode 🐍🎮 Python Learning Journey — Going Deeper into Theory After learning Python basics, core concepts, and building projects like Snake Game and Brick Game, I realized the next important step is not building more projects, but understanding Python at a deeper level. Here’s what I’m focusing on now 👇 🧠 Understanding Python Internals • How Python executes code step by step • How memory is allocated and managed 🏗 Object-Oriented Programming (OOP) • Writing structured and reusable code • Understanding how real-world logic fits into classes 🛠 Error Handling & Debugging • Handling errors properly instead of ignoring them • Learning how to debug and fix issues logically 💡 Big realization: Projects helped me build confidence. But theory is helping me build clarity. Today felt less about writing new code and more about understanding why my code works 🧠 Learning continues — one layer deeper 🚀 #Python #100DaysOfCode #LearningInPublic #PythonDeveloper #Programming #DeveloperJourney #Consistency

[paid content] A deep dive into #objectorientedprogramming with #python: I read "Python Object-Oriented Programming" from Steven F. Loft and Dusty Phillips, a book that helps readers develop strong object-oriented design and architectural thinking in Python. Of course it starts with the basics of #OOP but ultimately spends a lot of its roughly 500 pages explaining common and advanced #designpatterns in Python, such as decorator, flyweight or abstract factory. This targeting of both beginners and advanced programmers makes it likely that not every section is relevant depending on your level, though. I like the emphasis on clean code: type checking, testing and efficient code are repeatedly encouraged throughout the book. Concepts are theoretically motivated and then of course gradually demonstrated with practical code examples. Each chapter concludes with summary and excercises. Grab your copy at Packt Publishing. https://lnkd.in/duQb8ghC

Day 12 — Python Learning Journey Today I learned about Modules in Python — a powerful way to organize code and reuse functionality. 🔹 What I learned: • What modules are and why we use them • How to import modules (import, from…import, alias) • Using built-in modules like math and random • Creating my own custom module • Understanding name == "main" • Benefits of modular programming — clean, reusable, and maintainable code 🔹 Practice: ✔ Wrote programs using math functions ✔ Generated random numbers ✔ Created a simple custom module and imported it Every day I’m getting more confident in structuring Python programs. Excited to keep building! 🚀 #PythonLearning #Day12 #Modules #CodingJourney #LearningInPublic

📅 Day 4/30 – Advanced Object-Oriented Programming in Python Today, I went deeper into advanced OOP concepts to understand how complex Python applications are designed and maintained. Topics covered today: • Abstraction • Polymorphism • Abstract classes and methods • Multiple inheritance • Method Resolution Order (MRO) • super() keyword 📚 Learning resource used: • HackerBytez – https://lnkd.in/gzKTANVt Step by step, turning concepts into confidence 💪 Ready for Day 5 🚀 #Day4 #PythonChallenge #30DaysOfPython #AdvancedOOP #PythonOOP #LearningInPublic #CodingJourney #ComputerScience #StudentLife

🔹 Deep Dive into Object-Oriented Programming in Python I recently implemented and revised core OOP principles in Python by building multiple structured class-based examples covering real-world patterns. Here’s what I worked on: 🔐 Encapsulation 🧬 Inheritance 🏷 Class & Static Methods 🧮 Polymorphism & Operator Overloading ⚙️ Property Decorator 🧩 Real-world Modeling This hands-on implementation reinforced how Python internally handles: Strong OOP fundamentals are critical for writing scalable backend systems, APIs, and production-grade applications. Continuously refining core concepts. 🚀 #Python #OOP #SoftwareEngineering #BackendDevelopment #100DaysOfCode

🚀 Day 2/30 – Python OOPs Challenge 💡 Class and Object in Python Yesterday we learned what OOP is. Today let’s understand the core building blocks: Class and Object. 🔹 What is a Class? A class is a blueprint or template. It defines what an object will have and do. 🔹 What is an Object? An object is a real instance created from a class. 🔹 Simple Example: ``` class Car: def start(self): print("Car is starting") car1 = Car() car1.start() ``` 🔹 Real-life analogy: - Class → Car design (blueprint) - Object → Actual car on the road One class can create multiple objects. 📌 Key takeaway: - Class = Blueprint - Object = Real thing made from blueprint 👉 Day 3: __init__() constructor in Python (coming tomorrow) 👍 Like | 💬 Comment | 🔁 Share 📍 Follow me to learn Python OOP step by step #Python #OOP #LearningInPublic #30DaysOfPython #CodingJourney

I just delivered a session on Python: Design, Philosophy, and Engineering Foundations. Instead of jumping straight into frameworks, we explored: • Why Python was created • The philosophy behind its design • How Python actually runs (bytecode & VM) • Why readability scales engineering teams • How OOP principles shape real systems Understanding Python beyond syntax changes how you build software. When you understand the why behind the language, you write clearer, more scalable code. I’ve shared the presentation below for anyone who wants to deepen their fundamentals. Python is easy to start. But mastering it requires understanding its design. #Python #SoftwareEngineering #BackendDevelopment #OOP #TechEducation #Django #RwandaTech

Day 4 of My Tech Story 💻 What I’ve Learned So Far in Python (Beginner Friendly) 💻 Python is a high-level programming language, which means it’s designed to be easy for humans to read and write. We use Python as a way to communicate with the computer — giving it instructions on what to do. For example, when we write: print("Hello World") We are telling the computer to display the words “Hello World” on the screen. Let’s break it down: print() → This is a command that tells the computer to show something as output "Hello World" → The words inside the quotation marks are called a string (just text) So Python reads this as: 👉 “Print the text inside the quotes.” And just like that, you’ve given your first instruction to a computer! 🎉 Every program, app, or system is built from simple instructions like this — one line at a time. #RisewithTechCrush ‎#Tech4Africans ‎#LearningwithTechCrush #MyTechStory #PythonForBeginners #WomenInTech #DataScienceJourney