[Python OOP Cheat Sheet] A Simple Overview of Object-Oriented Programming

Q: What’s the object-oriented way to become wealthy?
A: Inheritance.

Your vocabulary determines the reality of your life.

In this article, I have compiled the most important terms and concepts of object-oriented programming in Python. My goal was to create the best Python OOP cheat sheet that shows them in one place. Well — here it is:

You can get a printable PDF version here:

Before we dive in the code from the Python OOP cheat sheet, let’s swipe through the most important OOP concepts in this Instagram post:

So let’s study the code!

class Dog:

    # class attribute
    is_hairy = True

    # constructor
    def __init__(self, name):
        # instance attribute
        self.name = name

    # method
    def bark(self):

bello = Dog("bello")
paris = Dog("paris")



class Cat:

    # method overloading    
    def miau(self, times=1):
        print("miau " * times)

fifi = Cat()

"miau "

"miau miau miau miau miau "

# Dynamic attribute
fifi.likes = "mice"

# Inheritance
class Persian_Cat(Cat):
    classification = "Persian"

mimi = Persian_Cat()
"miau miau miau "


Class: A blueprint to create objects. It defines the data (attributes) and functionality (methods) of the objects. You can access both attributes and methods via the dot notation.

Object (=instance): A piece of encapsulated data with functionality in your Python program that is built according to a class definition. Often, an object corresponds to a thing in the real world. An example is the object “Obama” that is created according to the class definition “Person”. An object consists of an arbitrary number of attributes and methods, encapsulated within a single unit.

Instantiation: The process of creating an object of a class.

Method: A subset of the overall functionality of an object. The method is defined similarly to a function (using the keyword “def”) in the class definition. An object can have an arbitrary number of methods.

Method overloading: You may want to define a method in a way so that there are multiple options to call it. For example for class X, you define a method f(…) that can be called in three ways: f(a), f(a,b), or f(a,b,c). To this end, you can define the method with default parameters (e.g. f(a, b=None, c=None).

Attribute: A variable defined for a class (class attribute) or for an object (instance attribute). You use attributes to package data into enclosed units (class or instance).

Class attribute (=class variable, static variable, static attribute): A variable that is created statically in the class definition and that is shared by all class objects.

Dynamic attribute: An “->instance attribute” that is defined dynamically during the execution of the program and that is not defined within any method. For example, you can simply add a new attribute neew to any object o by calling “o.neew = “.

Instance attribute (=instance variable): A variable that holds data that belongs only to a single instance. Other instances do not share this variable (in contrast to “->class attributes”). In most cases, you create an instance attribute x in the constructor when creating the instance itself using the self keywords (e.g. self.x = ).

Inheritance: Class A can inherit certain characteristics (like attributes or methods) from class B. For example, the class “Dog” may inherit the attribute “number_of_legs” from the class “Animal”. In this case, you would define the inherited class “Dog” as follows: “class Dog(Animal): …”

Encapsulation: Binding together data and functionality that manipulates the data.

If you have understood these terminologies, you can follow maybe 80% of the discussions about object-oriented programming (I LOVE the pareto principle: 80% of the learning in 20% of the time).

Where to go from here?

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Are you tired of coding tiny Python projects for yourself? Do you want to have a real-world impact with your Python projects? Step up to the next level in Python and master this Object-Oriented Python course!

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