This text is part of a Real Python tutorial by David Amos.
Object-oriented programming (OOP) in Python helps you structure your code by grouping related data and behaviors into objects. You start by defining classes, which act as blueprints, and then create objects from them. OOP simplifies modeling real-world concepts in your programs and enables you to build systems that are more reusable and scalable.
By the end of this lesson, you’ll understand that:
- Object-oriented programming in Python involves creating classes as blueprints for objects. These objects contain data and the methods needed to manipulate that data.
- You create an object in Python by instantiating a class, which involves calling the class name followed by parentheses.
What Is Object-Oriented Programming in Python?
Object-oriented programming is a programming paradigm that provides a means of structuring programs so that properties and behaviors are bundled into individual objects.
For example, an object could represent a person with properties like a name, age, and address and behaviors such as walking, talking, breathing, and running. Or it could represent an email with properties like a recipient list, subject, and body and behaviors like adding attachments and sending.
Put another way, object-oriented programming is an approach for modeling real-world things, like cars, as well as relations between things, like companies and employees or students and teachers. OOP models real-world entities as software objects that have some data associated with them and can perform certain operations. Note that the real-world entities can include abstract concepts that humans use in the real world.
Jargon Warning: Coming next are some complex terms that you don’t need to understand fully for now. Read them, but don’t dwell on these definitions
OOP also exists in other programming languages and is often described to center around the four pillars, or four tenants of OOP:
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Encapsulation allows you to bundle data (attributes) and behaviors (methods) within a class to create a cohesive unit. By defining methods to control access to attributes and its modification, encapsulation helps maintain data integrity and promotes modular, secure code.
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Inheritance enables the creation of hierarchical relationships between classes, allowing a subclass to inherit attributes and methods from a parent class. This promotes code reuse and reduces duplication.
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Abstraction focuses on hiding implementation details and exposing only the essential functionality of an object. By enforcing a consistent interface, abstraction simplifies interactions with objects, allowing developers to focus on what an object does rather than how it achieves its functionality.
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Polymorphism allows you to treat objects of different types as instances of the same base type, as long as they implement a common interface or behavior. Python’s duck typing make it especially suited for polymorphism, as it allows you to access attributes and methods on objects without needing to worry about their actual class.
In this lesson you’ll take a practical approach to understanding OOP in Python. But keeping these four concepts of object-oriented programming in mind may help you to remember the information that you gather.
The key takeaway is that objects are at the center of object-oriented programming in Python. In other programming paradigms, objects only represent the data. In OOP, they additionally inform the overall structure of the program.
How Do You Define a Class in Python?
In Python, you define a class by using the class keyword followed by a name and a colon. Then you use .__init__() to declare which attributes each instance of the class should have:
class Employee:
def __init__(self, name, age):
self.name = name
self.age = age
But what does all of that mean? And why do you even need classes in the first place? Take a step back and consider using built-in, primitive data structures as an alternative.
Primitive data structures—like numbers, strings, and lists—are designed to represent straightforward pieces of information, such as the cost of an apple, the name of a poem, or your favorite colors, respectively. What if you want to represent something more complex?
For example, you might want to track employees in an organization. You need to store some basic information about each employee, such as their name, age, position, and the year they started working.
One way to do this is to represent each employee as a list:
kirk = ["James Kirk", 34, "Captain", 2265]
spock = ["Spock", 35, "Science Officer", 2254]
mccoy = ["Leonard McCoy", "Chief Medical Officer", 2266]
There are a number of issues with this approach.
