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Introduction to Object-Oriented Programming in Python: Building Blocks of Code Structure and Reusability

 · 4 min · Pallavi Varandani

Discover the fundamentals of object-oriented programming in Python, where classes and objects are used to encapsulate data and behavior. Learn how to create classes, define methods, access attributes, and leverage the power of OOP for code organization and reusability.

Object Oriented Programming Python Intro

Object-Oriented Programming (OOP) is a powerful programming paradigm that allows you to structure your code by creating and defining classes and objects. Python, being an object-oriented programming language, provides robust support for implementing OOP concepts.

At the core of OOP is the idea of an object, which combines both state and behavior. The state represents the data or attributes of an object, while the behavior represents the operations or methods that the object can perform. In Python, a class serves as a blueprint for creating objects. You can think of a class as a generic version of an object that defines its structure and behavior.

To access the attributes and methods of an object’s class, you use the dot notation, where the syntax is object.attribute or object.method(). This allows you to interact with the object and manipulate its state or invoke its behavior.

When working with classes and objects in Python, you have access to some useful built-in functions and conventions. For example, you can use the type() function to determine the class of an object, the help() function to generate documentation for a class or object, and the dir() function to list all the attributes and methods available for a class or object.

Here’s an example of a basic class definition in Python:

class Customer:
    pass

In the above code, we define a class named Customer using the class keyword. The pass statement is used as a placeholder to indicate that the class doesn’t have any code yet. This class serves as a blueprint for creating customer objects.

To create an object from a class, you can use the class name followed by parentheses, like cust = Customer(). Here, cust is an object created using the Customer class.

To add methods to a class, you define them within the class definition. Methods are functions that operate on objects of the class. In Python, the first parameter of a method is conventionally named self, which refers to the object itself.

class Customer:
    def identify(self, name):
        print("I am a customer: " + name)

In the above code, we define a method named identify() within the Customer class. It takes two parameters: self (referring to the object) and name (a value provided as an argument). Inside the method, we print a message that includes the provided name.

To call a method of an object, you use the dot notation. For example:

cust = Customer()  # Create a customer object
cust.identify("Jane")  # Call the identify() method of the object

The output would be: I am a customer: Jane

The self parameter is essential in object-oriented programming as it acts as a reference to the object on which the method is called. When you call a method on an object, Python automatically handles passing the object itself as the first argument to the method. So, cust.identify("Jane") is equivalent to Customer.identify(cust, "Jane").

Attributes are the variables that store the state of an object. Encapsulation, one of the core principles of OOP, involves bundling data with the methods that operate on that data. In Python, you can define attributes within a class using the self keyword to refer to the object.

class Customer:
    def set_name(self, new_name):
        self.name = new_name

cust = Customer()  # Create a customer object
cust.set_name("Jane")  # Call the set_name() method
print(cust.name)  # Access the attribute

In the above example, we define

an attribute named name within the Customer class. The set_name() method takes a new_name argument and assigns it to the name attribute of the object. Later, we access the name attribute using cust.name and print its value, which would be “Jane” in this case.

By using classes and objects, you can organize your code into logical units, promote reusability, and implement complex systems with ease. Object-oriented programming, with its focus on encapsulation, inheritance, and polymorphism, provides a powerful and flexible approach to software development.

Python’s support for OOP, coupled with its simplicity and readability, makes it an excellent choice for implementing object-oriented designs and solving real-world problems in an elegant and maintainable way.