Learning Object-Oriented Programming with Python

Day 17 — Inheritance and Advanced OOP: Reusing and Extending Logic Good developers don’t rewrite code. They extend it. Inheritance allows one class to reuse the properties and methods of another. This is how large systems stay organized and scalable. Today you learned: • What inheritance is and why it matters • How to create a child class from a parent class • How to override methods • Using super() to access parent behavior • The idea of code reusability and hierarchy This is where object-oriented programming becomes powerful. Inheritance is used in: • Framework architectures • Large backend systems • Game engines • Scalable enterprise applications When you understand inheritance, you start designing systems instead of just writing features. Mini Challenge: Create a base class called Person with a method introduce(). Create a child class Student that inherits from Person and adds a new method study(). Instantiate both and test their behavior. Share your code in the comments. I’m sharing Python fundamentals — one focused concept per day. Built to transition you from beginner to structured developer thinking. Next up: Final Day — Bringing Everything Together with a Practical Mini Project. Working with multiple classes and navigating hierarchies becomes much easier in PyCharm by JetBrains, especially with its structure view and refactoring tools. Follow for the full Python series. Like • Save • Share with someone learning Python seriously. #Python #LearnPython #PythonBeginners #OOP #Inheritance #Programming #CodingJourney #Developer #Tech #JetBrains #PyCharm

🐍 I just put together a 20-page comprehensive Python Programming Guide — and I'm sharing it for free. Whether you're just starting out or leveling up your skills, this guide covers everything you need: ✅ Core Syntax, Variables & Data Structures ✅ Object-Oriented Programming & Inheritance ✅ Decorators, Generators & Async/Await ✅ Standard Library Deep Dive (26 modules) ✅ Data Science, ML & Web Development ✅ Testing Best Practices & CI/CD ✅ 11 Visual Diagrams for better understanding ✅ 20 Must-Know Best Practices Python continues to dominate across web development, data science, AI, and automation — and for good reason. Its readability, ecosystem, and community make it the most versatile language available today. I built this because I believe great learning resources should be accessible to everyone — from beginners writing their first script to engineers building production systems. 📥 Drop a comment or DM me and I'll send it your way. #Python #Programming #SoftwareDevelopment #DataScience #MachineLearning #LearningAndDevelopment #Tech #Coding #Developer #OpenSource

Writing code that works is the first step, but writing code that doesn't break when users make mistakes is what separates a beginner from a professional. This week, I focused on Exception Handling to make my applications "bulletproof." Instead of letting a program crash due to invalid inputs, I've implemented a robust "Try-Except" flow. Key takeaways from this stage: ✅ Defensive Programming: Anticipating potential runtime errors before they happen. ✅ The Try-Except-Pass Pattern: Creating clean, non-intrusive loops that guide users toward the correct input without breaking the flow. ✅ Modular Validation: Abstracting data validation into reusable functions to keep the main logic clean and readable. I refactored my previous projects into a more resilient structure, ensuring that only valid numeric data reaches the calculation engine. It’s all about creating a seamless user experience, even when things go wrong. Next stop: Exploring Python Libraries to extend my toolkit! 🚀 #Python #SoftwareDevelopment #Coding #CleanCode #ErrorHandling #VibeCoders #ProgrammingLogic

There have been many instances when I’ve had to implement code or an algorithm to solve a problem. As a result, I’d spend a lot of time understanding the problem, breaking it down into subproblems, and, with my growing knowledge of Python, visualising data structures and other components to complete the task. However, it is relatively easy to get through the design stage of software development because it involves less code and more brainstorming. At this stage, you develop ideas or methods you believe will solve the problem and outline a highly detailed, end-to-end structure and logic for the program. It is for this very reason that you’re sometimes fooled into thinking that the next stage, the development stage, would be just as straightforward as the design stage. The development stage is when you realise that most of the ideas you came up with don't work as expected, often forcing you back to the designing phase. As a result, you may need to discard some ideas and refine others, with the worst-case scenario being that you have to restart the entire project. In fact, you've probably already written hundreds of lines of code when your program suddenly crashes on line 397 because you're using a data structure incompatible with what you implemented on line 15. I’ve often found myself in similar, frustrating situations, with 4 days left to the project’s deadline, but this is what makes programming so addictive. No matter how exhausting it becomes, you’ll always find yourself back at your computer with renewed confidence that you will somehow find a solution to the given problem. #programming #algorithms #computerscience #coding #python #developer

💡 What if I told you even something as simple as a leap year can teach you how to think like a programmer? 🚀 Day 4 of my Python journey Today’s focus: ✅ Strings (understanding and manipulating text data) ✅ More practice on functions ✅ Solving a real problem: Leap Year Identification using if-else and functions Working with strings made me realize how important text processing is — from user inputs to real-world applications. But the highlight of my day was solving a leap year problem using logic and functions. It wasn’t just about getting the right answer — it was about breaking the problem down, thinking step by step, and structuring the solution clearly. Here’s the solution I built 👇 def is_leap_year(year): if (year % 4 == 0 and year % 100 != 0) or (year % 400 == 0): return True else: return False year = int(input("Enter a year: ")) if is_leap_year(year): print("Leap Year") else: print("Not a Leap Year") Every day, I’m starting to see a shift — from just writing code to actually thinking like a developer. Consistency is slowly building confidence, and each small concept is adding up. 💪 Now I want to learn smarter, not just harder 👇 👉 What are the best ways you improved your programming skills when you were starting out? 👉 Any tips, resources, or habits you would recommend? Would love to learn from your experience! #Python #CodingJourney #LearningInPublic #100DaysOfCode #Programming #StudentDeveloper #GrowthMindset

🚀 Understanding Classes & Objects in Programming (Python) When starting with Object-Oriented Programming (OOP), two concepts form the foundation: Classes and Objects. Let’s break it down in a simple way 👇 🔹 Class A class is like a blueprint or template. It defines the properties (variables) and behaviors (functions) that an object will have. 👉 Example: Think of a Car A class defines what a car can have (color, speed) and can do (drive, stop). 🔹 Object An object is a real instance of a class. It represents something tangible created using the class blueprint. 👉 Example: A red car, a blue car — both are objects of the "Car" class. 💻 Simple Python Example: class Car: def __init__(self, color): self.color = color def drive(self): print(f"The {self.color} car is driving") # Creating objects car1 = Car("Red") car2 = Car("Blue") car1.drive() car2.drive() ✨ Key Takeaways: ✔ Class = Blueprint ✔ Object = Instance of class ✔ Helps organize code better ✔ Makes programs reusable and scalable Understanding classes and objects is the first step towards mastering OOP and building real-world applications. #Python #Programming #OOP #Coding #Learning #Developers

How do you actually learn #Python? Mark Smith breaks it down into 3 core ideas: 1. Start by copying At the beginning, you need guidance. Tutorials, books, and exercises help you understand how code is structured. 2. Move quickly to building This is where real learning happens. • Start small • Recreate simple tools • Work on projects you care about You don’t learn programming by consuming content – you learn it by writing code. 3. Learn from others Read code, follow experienced developers, and learn how real projects are written. ❌ Avoid common mistakes: - When you let AI write code, you stop learning. - When you try to learn everything at once, you risk burning out. - When you obsess about avoiding errors, you lose a major part of the process. ✅ What actually helps: - Breaking problems into small pieces. - Building early, even if it’s messy. - Learning gradually (including tools like Git). - Using AI to assist, not replace thinking. The key idea: You don’t learn programming by consuming content. You learn it by writing code. 👉 Watch the full talk: https://lnkd.in/ex9yu4TM

I didn’t just “learn Python” — I forced myself to prove it by working tougher over the past few weeks Instead of jumping from one tutorial to another, I sat down and actually built things. No shortcuts, no skipping — just writing code, breaking it, fixing it, and repeating. So I turned everything into a structured repository: notes + concepts + working programs + mini projects. 📚 What this included: • Core fundamentals (variables, strings, numbers) • Control flow (if-else, operators, logic building) • Loops and iteration (including nested logic) • Functions and arguments • How Python actually runs (interpreter → bytecode → execution) 💻 What I ended up building: • 🔢 A menu-driven calculator • 💰 An interest + tax calculation system • 🔐 A password strength checker • 🎯 A number guessing game • 🎓 A full CLI-based student management system (CRUD) The interesting part? At the start, even small logic felt confusing. By the end, I was comfortably structuring full programs. Not because I “finished a course” — but because I kept writing code until things started making sense. 🔗 Here’s everything I built: [ https://lnkd.in/grknB8p6 ] This is just the beginning. Next step: build something bigger and less comfortable. #Python #Programming #BuildInPublic #CodingJourney #StudentDeveloper #GitHub #LearnToCode #SoftwareDevelopment

Stop writing "Scripts." Start building "Tools." 🛠️ Day 5 of my Python journey was a total shift in perspective. I moved away from long, rambling lines of code and started learning the power of Functions and Loops. Here’s how I’m cleaning up my logic: 🔹 The Def Storage: I learned that def doesn't actually run code—it stores it. It’s like writing a recipe and putting it in a drawer. It only "cooks" when you call it by name. This is the secret to DRY (Don't Repeat Yourself) programming. 🔹 Some functions just do something (like printing to a screen), while others calculate and return a value to be used later. Learning to capture that Return Value is what makes code truly powerful. - My favorite takeaway? Functions should be like paragraphs. They should capture one complete thought. If the logic gets too complex, it’s time to break it into chunks. This makes code readable for humans, not just machines. 🔹 The Loop Introduction: I dipped my toes into Infinite Loops (the dangerous ones), Definite Loops, and the magic of break and continue. It’s all about controlling the flow—knowing when to keep going and when to get out. Python isn't just a language; it’s a way of organizing chaos. #Python #SoftwareEngineering #CleanCode #LearningInPublic #Functions #CodingLogic

🚀 Master Python from Basics to Advanced — Simplified Notes 📘 If you're starting your coding journey or revising Python, these handwritten-style notes are a goldmine! Here’s what you’ll learn 👇 🔹 Python Fundamentals * High-level, interpreted & object-oriented language * Simple, readable & cross-platform 🔹 Variables & Data Types * Integers, Floats, Strings, Booleans * Dynamic typing & naming conventions 🔹 Operators * Arithmetic, Comparison & Logical operators * Assignment & Membership operators 🔹 Control Flow * if-else, elif conditions * Real-world decision-making logic 🔹 Loops * for loop & while loop * break & continue statements 🔹 Functions * Function creation & arguments * Return values & reusable code 🔹 Data Structures * Lists (append, remove, slicing) * Tuples (immutable & fast) * Dictionaries (key-value pairs) * Sets (unique elements & operations) 💡 Bonus: Setup guide + Your first Python program (Hello World!) These notes cover everything from basics to core concepts in a clean, beginner-friendly way. Perfect for students, beginners, and quick revision! 📂 Source: 🔥 Save this for later & start building with Python today! 👉 Follow Abhay Tripathi for more tech updates, coding materials, and daily programming insights! #Python #Programming #Coding #Developer #LearnToCode #PythonBasics #SoftwareDevelopment #Tech #CodingJourney #Developers #100DaysOfCode #AI #DataStructures