Object-oriented programming (OOP) is a widely used programming paradigm that reduces development times—making it easier to read, reuse, and maintain your code. OOP shifts the focus from thinking about code as a sequence of actions to looking at your program as a collection of objects that interact with each other. In this course, you’ll learn how to create classes, which act as the blueprints for every object in Python. You’ll then leverage principles called inheritance and polymorphism to reuse and optimize code. Dive in and learn how to create beautiful code that’s clean and efficient!
In this chapter, you'll learn what object-oriented programming (OOP) is, how it differs from procedural-programming, and how it can be applied. You'll then define your own classes, and learn how to create methods, attributes, and constructors
What is OOP? 50 xp
OOP termininology 100 xp
Exploring object interface 100 xp
Class anatomy: attributes and methods 50 xp
Understanding class definitions 100 xp
Create your first class 100 xp
Using attributes in class definition 100 xp
Class anatomy: the __init__ constructor 50 xp
Correct use of __init__ 50 xp
Add a class constructor 100 xp
Write a class from scratch 100 xp
Inheritance and polymorphism are the core concepts of OOP that enable efficient and consistent code reuse. Learn how to inherit from a class, customize and redefine methods, and review the differences between class-level data and instance-level data
Instance and class data 50 xp
Class-level attributes 100 xp
Changing class attributes 100 xp
Alternative constructors 100 xp
Class inheritance 50 xp
Understanding inheritance 100 xp
Create a subclass 100 xp
Customizing functionality via inheritance 50 xp
Method inheritance 100 xp
Inheritance of class attributes 100 xp
Customizing a DataFrame 100 xp
In this chapter, you'll learn how to make sure that objects that store the same data are considered equal, how to define and customize string representations of objects, and even how to create new error types. Through interactive exercises, you’ll learn how to further customize your classes to make them work more like standard Python data types.
Operator overloading: comparison 50 xp
Overloading equality 100 xp
Checking class equality 100 xp
Comparison and inheritance 100 xp
Operator overloading: string representation 50 xp
String formatting review 100 xp
String representation of objects 100 xp
Exceptions 50 xp
Catching exceptions 100 xp
Custom exceptions 100 xp
Handling exception hierarchies 100 xp
How do you design classes for inheritance? Does Python have private attributes? Is it possible to control attribute access? You'll find answers to these questions (and more) as you learn class design best practices.
Designing for inheritance and polymorphism 50 xp
Polymorphic methods 50 xp
Square and rectangle 100 xp
Managing data access: private attributes 50 xp
Attribute naming conventions 100 xp
Using internal attributes 100 xp
Properties 50 xp
What do properties do? 50 xp
Create and set properties 100 xp
Read-only properties 100 xp
Congratulations! 50 xp