Python OOP: Classes, Inheritance, and Design Patterns
Object-oriented programming in Python is flexible by design. You can write simple classes that group data with behavior, or build complex hierarchies with descriptors, metaclasses, and protocol-based design. The key is knowing which tools to reach for and when composition beats inheritance.
This path covers OOP from the ground up: defining classes, understanding __init__ and self, choosing between class methods and static methods, designing with composition vs inheritance, and using descriptors for attribute control.
Classes and Objects
6 articlesPython Classes and Objects Explained
Understand the class keyword, __init__, self, instance attributes, and methods -- the building blocks of object-oriented Python.
Python Class Example: Complete Guide
Building classes from scratch -- attributes, methods, __init__, __repr__, and organizing behavior around data.
What Is __init__ in Python?
How the constructor works, self explained, initialization vs creation, and common __init__ patterns.
Python OOP Methods Explained
Instance methods, class methods, static methods, and dunder methods -- when to use each and why.
classmethod vs staticmethod in Python
Side-by-side comparison with practical examples showing when each decorator is the right choice.
What Are Attributes in Python?
Instance vs class attributes, attribute lookup order, __dict__, and dynamic attribute patterns.
Design and Architecture
5 articlesComposition vs Inheritance in Python
Why composition is often preferred, when inheritance makes sense, and refactoring from one to the other.
Python Descriptor Protocol
How descriptors power properties, class methods, and attribute access -- the mechanism behind Python's data model.
Python Descriptor Protocol and Attribute Lookup
The full attribute lookup chain: instance dict, class dict, descriptors, __getattr__, and MRO resolution.
Procedural Python Guide
When procedural style beats OOP, and how to write clean procedural code that doesn't need classes.
Python Is Multi-Paradigm: OOP, Procedural, and Functional
How Python supports multiple programming paradigms and how to choose the right one for your problem.