Q: What’s the object-oriented way to become wealthy?
A: Inheritance. 😒
Your vocabulary determines the reality of your life.
In this tutorial, I have compiled the most essential 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:
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:
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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): print("Wuff") bello = Dog("bello") paris = Dog("paris") print(bello.name) "bello" print(paris.name) "paris" class Cat: # method overloading def miau(self, times=1): print("miau " * times) fifi = Cat() fifi.miau() "miau " fifi.miau(5) "miau miau miau miau miau " # Dynamic attribute fifi.likes = "mice" print(fifi.likes) "mice" # Inheritance class Persian_Cat(Cat): classification = "Persian" mimi = Persian_Cat() print(mimi.miau(3)) "miau miau miau " print(mimi.classification)
Before we dive into the vocabulary, here’s an interactive Python shell:
Exercise: Create a new class Tiger that inherits from the parent class Cat and add a custom method!
Let’s dive into the Vocabulary!
OOP Terminology in Python
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,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 = ... ).
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 OOP terms, you can follow most of the discussions about object-oriented programming. That’s the first step towards proficiency in Python!
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Where to Go From Here?
Enough theory, let’s get some practice!
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Practice projects is how you sharpen your saw in coding!
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While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.
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