Python’s Oops is the main reason so many tech companies around the world demand their employees know how to code with python. The developer’s quest for knowledge never ends, and every year more know-how is required to stay competitive.
In this article, you will learn about python’s state-of-the-art programming paradigm. It doesn’t matter what language you have expertise in, as object-oriented programming concepts will give you a new understanding of code structure and software architecture.
We will show you the basics of Oops in Python, and we hope this inspires you along your programming journey to learn more and try newer and more efficient ways to code.
What is Object-Oriented Programming?
Object-oriented programming (Oop) is a building method used by a wide spectrum of developers, and a useful paradigm when working with large and complex projects. It is the current paradigm in the programming world, and it doesn’t seem like that will change any time soon.
To understand this development path first we need to define objects. Think about an object as a unit of a system, a system where every part has a fundamental task.
For example, you can think of the human body as a system where every organ is an object. The final result of the sum of all the objects is a functional and healthy human being.
In object-oriented programming, every object must work efficiently so that together they can get the desired task done. Each object contains data and behavior, the two parameters that define how that object works.
In Object-oriented programming, a class is a blueprint from which the objects are created. Each class provides attributes and methods to work with, and you can have many different objects created with the same class. Don’t worry if this doesn’t make sense yet! We promise the examples will make it easier.
When you define a class you also build a data structure. Each class can have unique methods, which are functions that give us convenient behaviors to use in our code.
Once you have defined the class, each object created is an extra instance that contains the variables we defined in the blueprint. Think of it like this: in the real world, we have the class “human”, and each person is an instance of that class whose variables are derived from that class.
So this all sounds good, but how do we build a class? To begin, let’s think of many people, each one of which has many attributes such as name, age, job, etc. A class is a great way to organize each person, and you can assign attributes without any real limits.
We can create a class by using a keyword and the attributes assigned as variables with the proper indentation. You can print every attribute individually or in groups, and then use this information for further development. In essence, we create a class by defining its attributes and then derive objects from that class that has those attributes already built into them.
Let’s see how the syntax for creating a class works:
That’s it, very simple. We just created a class named Person with the pass keyword. Pass is a placeholder indicating where the code will eventually go, allowing you to run the code without errors.
The class is already defined and working. However, it still does not contain any properties, so let’s add some:
The __init__ method is a fundamental tool when we define properties or attributes. It allows you to create a new class instance. Additionally, the __init__ method defines the initial state of an object with the parameters available in the class.
For reasons we won’t go into here, the first parameter should always be a variable called self. Bear in mind: indentation is very important when working with python and Oop systems. The __init__ method must be indented four spaces, and the body where variables are defined must have eight spaces of indentation.
Now, let’s establish an important distinction when working with attributes. Class attributes are the name of those attributes that are the same for each class and their value is defined with the __init__ method. Inversely, when you call the __init__ method for building a new object any attribute created is called an instance attribute.
Why? Well, these attributes are specific to a particular instance of a class. Using our example, for the Person class, all objects have name and age properties, but the values of these parameters could be different in each Person instance.
In this example, the class attribute defines a global value (species) for all the objects created with this class.
The syntax for a class attribute is very simple. Just make sure to define the attribute before the __init__ method and indent four spaces. Also, always remember to assign an initial value.
Objects are an everyday topic for any programmer. A string like “Hello, world” is an object. A number or an array is also an object.
In other words, any entity with a state and a behavior associated with it is an object. Integers, floating-point numbers, and dictionaries are typical objects when coding with Python.
Three core principles define an object. Its identity: a unique name used to relate it with other objects and functions. Next, its state, which is all the attributes and properties stored in an object. Finally, the behavior, which consists of the methods that work with that unique object, and how it responds to the other functionalities available in your code.
For example, an object Person would have an identity determined by its name. The attributes would be age, hobbies, and job. A behavior of that Person would be any action they can implement.
Code Example: Methods, Class, and Instance Attributes
Now, let’s see a code example:
In the code above we have combined all the attributes and the class method to create a fairly complex object. Now, we have a Person class with some properties and actions that we can extend to add different things to our code.
Inheritance and Polymorphism in Python’s Oops
When a class takes the properties and methods of another class, we call this process inheritance. The class that inherits is called the child class, and of course, the parent class is the one that conceives its attributes.
You can modify, override or delete inherited attributes when working with the child class, without affecting the parent. This process can save us a ton of time and is very useful when we need a slightly different version of a class.
Polymorphism is another useful feature when working with classes. It allows us to reuse functions of a parent class in any child class we like. Making use of polymorphism is a great way to reduce the length of our code and make it adaptable to any situation.
Any function we take from other objects works as any other function, you just need to assign the right parameters. Therefore, combining inheritance and polymorphism is an interesting practice for optimizing your code.
Encapsulation in Python’s Oops
Let’s talk about one last big concept related to Object-oriented programming.
Encapsulation is a safety concept and a fundamental practice for the correct functioning of any Oop system. It basically consists of sorting the data into separate units, such that this data is only accessible with the right keywords.
This is a convenient way to prevent the accidental modification of important data in any software.
For example, a class is an encapsulated unit. The information on its attributes, functions, and methods is only accessible through the class. Objects work the same way: if you want to change the information inside the object, you need to call a specific method.
What Are the Advantages of Object-Oriented Programming?
In short, object-oriented Programming is the ideal way to build a model of real objects interacting with each other, organized for efficiency and controlled development. We’ve already seen a portion of the features and the possibilities it offers.
With Oops, we can design and work with complex information and then use this data to build any functionalities we desire. We can define how an object gets built, how it works, and what behaviors it gets.
While another common paradigm such as procedural programming structures a program linearly (with poor adaptability), with Oop the ramification for functionality is endless. This is, along with the extreme adaptability it offers, one of the main benefits of working with oops.
Python Oops Concepts Explained, With Examples
The fundamental takeaway is that object-oriented programming structures and processes data in a non-linear, adaptable, and expandable way. This increases its efficiency and makes programming languages that are based on oop more accessible.
Now you know about tools like classes and objects that will help you build any programs you can think of. Also, learning about concepts like inheritance and encapsulation will add a lot of value to the way you treat your code.
These are professional tools that get more and more complex with every new concept you learn. However, learning the basics will always ensure you have a strong foundation to build on. If you need any further information, you should check out Python’s official documentation!
Now, it’s time to code and try all these concepts. Good luck!
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