Welcome to the Python OOPs Tutorial repository! This is a comprehensive, step-by-step guide to mastering Object-Oriented Programming (OOPs) in Python. Whether you are a beginner or an intermediate Python developer, this tutorial will help you understand classes, objects, inheritance, encapsulation, polymorphism, and abstraction with practical examples.
Python OOPs allows you to represent real-world entities as objects. Using OOPs, you can organize your code in a modular, reusable, and maintainable way. This repository covers all the fundamental concepts of Python OOPs with clear examples and exercises.
Key Concepts Covered:
- Classes & Objects
- Attributes & Methods
- Constructor (
__init__) - Inheritance (single, multi-level, hierarchical)
- Encapsulation (private & protected attributes, getters/setters)
- Polymorphism (method overriding, operator overloading)
- Abstraction (abstract classes and methods)
| Notebook Name | Covered Topics | Reason |
|---|---|---|
01_Python_OOPs_Introduction.ipynb |
Basics of OOP, Key Concepts, Class vs Object | First notebook to introduce OOPs, perfect for beginners |
02_Classes_and_Objects.ipynb |
Creating classes, objects, constructors (__init__), attributes, methods |
Focused on practical creation and use of objects |
03_Inheritance.ipynb |
Single, multi-level, hierarchical inheritance, super() function, method overriding |
Dedicated to code reuse and inheritance concepts |
04_Encapsulation.ipynb |
Private/protected attributes, getter/setter, data hiding | Focused on data security and controlled access |
05_Polymorphism.ipynb |
Method overriding, operator overloading, dynamic typing | Flexible code behavior and reuse |
06_Abstraction.ipynb |
Abstract classes, abstract methods, abc module, enforcing implementation |
Focus on hiding complexity and interfaces |
07_OOPs_Summary_and_Examples.ipynb |
Consolidated examples of all OOPs concepts | Ideal for review and project practice |
- Code Reusability: Avoid duplication by using classes and inheritance.
- Modularity: Organize your code into logical, reusable units.
- Abstraction: Hide complex implementation details and show only essential functionality.
- Encapsulation: Secure data and control access with private/protected attributes.
- Polymorphism: Flexibly handle multiple object types using the same interface.
- Clone the repository:
git clone https://github.com/datascikhan/python-oops-tutorial.git