Python - 3 Deep Dive Part 4 Oop

Python 3: Deep Dive (Part 4 - OOP) course by Fred Baptiste is an advanced exploration of object-oriented programming (OOP) in Python. Unlike introductory courses, it focuses on the internal mechanics of the language, explaining not just

to use classes, but how Python implements them under the hood. Core Curriculum Topics Classes and Instances

: Understanding the relationship between class objects and instance objects, including class-level data and function attributes. Methods and Binding python 3 deep dive part 4 oop

: Deep dive into how methods are bound to instances and the mechanics behind Method Types : Detailed differentiation and use cases for static methods Properties and Decorators : Using the

decorator, as well as read-only, computed, and deletable properties. Polymorphism and Special Methods : The role of "Dunder" (double underscore) methods like , arithmetic operators, and rich comparisons. Single Inheritance Python 3: Deep Dive (Part 4 - OOP)

: Exploring how inheritance works, overriding and extending methods, and delegating to parent classes using Descriptors : An in-depth look at the descriptor protocol ( __delete__ ) and its relationship to properties. Metaprogramming : High-level concepts including metaclasses , class decorators, and the Advanced Features : Coverage of for memory optimization and the use of enumerations Course Structure & Materials Python 3: Deep Dive (Part 4 - OOP) - Udemy

__dict__ and Attribute Storage

When you instantiate a class, Python typically creates a __dict__ attribute for the instance. This is a standard Python dictionary mapping attribute names to values. The Implication: This allows for extreme dynamism

class Simple:
    pass
s = Simple()
s.x = 10
print(s.__dict__) 
# Output: 'x': 10

• The Implication: This allows for extreme dynamism. You can add attributes to an instance at runtime that were never defined in the class body.
• The Cost: Dictionary lookups consume more memory and CPU than static offsets in languages like C++.

The MRO

The MRO determines the order in which base classes are searched when executing a method. You can inspect it using ClassName.mro().

class A: pass
class B(A): pass
class C(A): pass
class D(B, C): pass
print(D.mro())
# Output: [D, B, C, A, object]

The rule is: Children come before parents, and the order of appearance in the base class list is preserved.

3. Jupyter Notebook Format

• All code is in well-organized Jupyter notebooks (included). You can run, modify, and break things as you follow along.
• Interactive exercises with solutions (not just multiple choice—actual coding).