Object-Oriented Programming (OOP) is a programming paradigm where different components of a computer program are modeled after real-world objects. An object is anything that has some characteristics and can perform a function.
Consider a scenario where you have to develop a Formula 1 car racing game using the object-oriented programming approach. The first thing you need to do is to identify real-world objects in the actual Formula 1 race. What are the entities in a Formula 1 race that have some characteristics and can perform any function? One of the obvious answers to this question is the car. A car can have characteristics like engine capacity, make, model, manufacturer, and so on. Similarly, a car can be started, stopped, accelerated and so on. A driver can be another object in a Formula 1 race. A driver has a nationality, age, gender, and so on, and he can perform functionalities like driving the car, moving the steering or changing the transmission.
Just like in this example, in object-oriented programming we will create objects for the corresponding real-world entity.
It is important to mention here that object-oriented programming is not a language-dependent concept. It is a general programming concept and most of the modern languages, such as Java, C#, C++, and Python, support object-oriented programming. In this article, we will see a detailed introduction to Object-Oriented Programming in Python, but before that, we will see some of the advantages and disadvantages of object-oriented programming.
Pros and Cons of OOP
Following are some of the advantages of object-oriented programming:
- Object-oriented programming fosters reusability. A computer program is written in the form of objects and classes, which can be reused in other projects as well.
- The modular approach used in object-oriented programming results in highly maintainable code.
- In object-oriented programming, every class has a specific task. If an error occurs in one part of the code, you can rectify it locally without having to affect other parts of the code.
- Data encapsulation (which we will study later in the article) adds an extra layer of security to the program developed using the object-oriented approach.
Though object-oriented programming has several advantages as discussed, it has some downsides as well, some of which have been enlisted below:
- Detailed domain knowledge of the software being developed is needed in order to create objects. Not every entity in software is a candidate for being implemented as an object. It can be hard for newbies to identify this fine line.
- As you add more and more classes to the code, the size and complexity of the program grows exponentially.
In the next section, we will see some of the most important concepts of object-oriented programming.
As the name suggests, object-oriented programming is all about objects. However, before an object can be created we need to define the class for the object.
A class in object-oriented programming serves as a blueprint for the object. A class can be considered as a map for the house. You can get an idea of what the house looks like by simply seeing the map. However, a class itself is nothing. For instance, a map is not a house, it only explains how the actual house will look.
The relationship between a class and object can be understood by looking at the relationship between a car and an Audi. An Audi is actually a car. However, there is no such thing as a car only. A car is an abstract concept, it is actually implemented in the form of Toyota, Ferrari, Honda, etc.
class is used in order to create a class in Python. The name of the class follows the
class keyword, followed by the colon character. The body of the class starts on a new line, indented one tab from the left.
Let's see how we can create a very basic class in Python. Take a look at the following code:
# Creates class Car class Car: # create class attributes name = "c200" make = "mercedez" model = 2008 # create class methods def start(self): print ("Engine started") def stop(self): print ("Engine switched off")
In the example above, we create a class named
Car with three attributes:
car class also contains two methods:
Earlier, we said that a class provides a blueprint. However, to actually use the objects and methods of a class, you need to create an object out of that class. There are few class methods and attributes that can be used without an object, which we will see in the later section. For now, just keep in mind that by default, we need to create an object of a class before we can use its methods and attributes.
An object is also called an instance; therefore, the process of creating an object of a class is called instantiation. In Python, to create an object of a class we simply need to write the class name followed by opening and closing parenthesis.
Let's create an object of the
Car class that we created in the last section.
# Creates car_a object of Car class car_a = Car() # Creates car_b object of car class car_b = Car()
In the script above, we created two objects of the car class:
car_b. To check the type of the objects we created, we can use the
type method and pass it the name of our object. Execute the following script:
In the output, you will see:
Which says that the type of
car_b object is a class
At this point we've created our class and the corresponding objects. Now is the time to access class attributes and call class method using the class object. To do so, you simply have to write the object name, followed by dot operator and the name of the attribute or the method that you want to access or call, respectively. Take a look at the following example:
In the script above, we call the
start() method via the
car_b object. The output will be as follows:
Similarly, you can access an attribute using the following syntax:
In the output, you will see the value of the
model attribute, as shown below:
In the previous section, we saw how we can create objects of a class and can use those objects to access the attributes of a class.
In Python, every object has some default attributes and methods in addition to user-defined attributes. To see all the attributes and methods of an object, the built-in
dir() function can be used. Let's try to see all the attributes of the
car_b object that we created in the last section. Execute the following script:
In the output, you will see the following attributes:
['__class__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__', 'make', 'model', 'name', 'start', 'stop']
This built-in function is useful for inspecting all of the attributes and functions of an object, especially when used via Python's REPL.
Class vs Instance Attributes
Attributes can be broadly categorized into two types: Class attributes and Instance attributes. Class attributes are shared by all the objects of a class while instance attributes are the exclusive property of the instance.
Remember, an instance is just another name for the object. Instance attributes are declared inside any method while class attributes are declared outside of any method. The following example clarifies the difference:
class Car: # create class attributes car_count = 0 # create class methods def start(self, name, make, model): print ("Engine started") self.name = name self.make = make self.model = model Car.car_count += 1
In the script above, we create a class
Car with one class attribute
car_count and three instance attributes
mode. The class contains one method
start() which contains the three instance attributes. The values for the instance attributes are passed as arguments to the
start() method. Inside the
start method, the
car_count attribute is incremented by one.
It is important to mention that inside the method, the instance attributes are referred using the
self keyword, while class attributes are referred by the class name.
Let's create an object of the
Car class and call the
car_a = Car() car_a.start("Corrola", "Toyota", 2015) print(car_a.name) print(car_a.car_count)
In the above script we print the instance attribute
name and class attribute
car_count. You will see in the output that the
car_count attribute will have a value of 1, as shown below:
Engine started Corrola 1
Now, let's create another object of the
car class and call the
car_b = Car() car_b.start("City", "Honda", 2013) print(car_b.name) print(car_b.car_count)
Now if you print the value of the
car_count attribute, you will see 2 in the output. This is because the
car_count attribute is a class attribute and hence it is shared between the instances. The
car_a object incremented its value to 1, while
car_b object incremented it again, hence the final value became 2. The output looks like this:
Engine started City 2
As we described earlier, in object-oriented programming, the methods are used to implement the functionalities of an object. In the previous section, we created
stop() methods for the
Car class. Till now, we have been using the objects of a class in order to call the methods. However, there is a type of method that can be called directly using the class name. Such a method is called a static method.
To declare a static method, you have to specify the
@staticmethod descriptor before the name of the method as shown below:
class Car: def get_class_details(): print ("This is a car class") Car.get_class_details()
In the above script, we create a class
Car with one static method
get_class_details(). Let's call this method using the class name.
You can see that we did not need to create an instance of the
Car class in order to call the
get_class_details() method, rather we simply used the class name. It is important to mention that static methods can only access class attributes in Python.
Returning Multiple Values from a Method
One of the best features of the Python language is the ability of class methods to return multiple values. Take a look at the following example:
class Square: def get_squares(a, b): return a*a, b*b print(Square.get_squares(3, 5))
In the above script, we created a class named
Square with one static method
get_squares(). The method takes two parameters; multiply each parameter with itself and returns both the results using
return statement. In the output of the script above, you will see the squares of 3 and 5.
The str Method
Till now we have been printing attributes using the
print() method. Let's see what happens if we print the object of a class.
To do so we'll create a simple
Car class with one method and try to print the object of the class to the console. Execute the following script:
class Car: # create class methods def start(self): print ("Engine started") car_a = Car() print(car_a)
In the script above we create
car_a object of the
Car class and print its value on the screen. Basically here we are treating
car_a object as a string. The output looks likes this:
<__main__.Car object at 0x000001CCCF4335C0>
The output shows the memory location where our object is stored. Every Python object has a
__str__ method by default. When you use the object as a string, the
__str__ method is called, which by default prints the memory location of the object. However, you can provide your own definition for the
__str__ method as well. For instance, look at the following example:
# Creates class Car class Car: # create class methods def __str__(self): return "Car class Object" def start(self): print ("Engine started") car_a = Car() print(car_a)
In the script above, we override the
__str__ method by providing our own custom definition for the method. Now, if you print the
car_a object, you will see the message "Car class Object" on the console. This is the message that we printed inside our custom the
Using this method you can create custom and more meaningful descriptions for when an object is printed. You could even display some of the data within the class, like the
name of a
A constructor is a special method that is called by default whenever you create an object of a class.
To create a constructor, you have to create a method with keyword
__init__. Take a look at the following example:
class Car: # create class attributes car_count = 0 # create class methods def __init__(self): Car.car_count +=1 print(Car.car_count)
In the script above, we create a
Car class with one class attribute
car_count. The class contains a constructor which increments the value of
car_count and prints the resultant value on screen.
Now, whenever an object of the
Car class will be created the constructor will be called, the value of the
car_count will be incremented and displayed on the screen. Let's create a simple object and see what happens:
car_a = Car() car_b = Car() car_c = Car()
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In the output, you will see a value of 1, 2, and 3 printed since with every object the value of
car_count variable is incremented and displayed on the screen.
Except for the name, the constructor can be used as an ordinary method. You can pass and receive values from a constructor. It is usually used in this way when you want to initialize attribute values upon instantiating the class.
Local vs Global Variables
We know that there are two types of Python attributes, instance attributes, and class attributes. The attributes of a class are also referred to as variables. Depending on the scope, variables can also be categorized into two types: Local variables and Global variables.
A local variable in a class is a variable that can only be accessed inside the code block where it is defined. For instance, if you define a variable inside a method, it cannot be accessed anywhere outside that method. Look at the following script:
# Creates class Car class Car: def start(self): message = "Engine started" return message
In the script above we create a local variable
message inside the
start() method of the
Car class. Now let's create an object of the
Car class and try to access the local variable
message as shown below:
car_a = Car() print(car_a.message)
The above script will return the following error:
AttributeError: 'Car' object has no attribute 'message'
This is because we cannot access the local variable outside the block in which the local variable is defined.
A global variable is defined outside of any code block e.g method, if-statements, etc. A global variable can be accessed anywhere in the class. Take a look at the following example.
# Creates class Car class Car: message1 = "Engine started" def start(self): message2 = "Car started" return message2 car_a = Car() print(car_a.message1)
In the script above, we created a global variable
message1 and printed its value on the screen. In the output, you will see the value of the
message1 variable, printed without an error.
It is important to mention that there is a difference between class and instance attributes, and local vs global variables. The class and instance attributes differ in the way they are accessed i.e. using class name and using instance name. On the other hand, local vs global variables differ in their scope, or in other words the place where they can be accessed. A local variable can only be accessed inside the method. Though in this article, both the local variable and instance attributes are defined inside the method, local attribute is defined with the self-keyword.
The access modifiers in Python are used to modify the default scope of variables. There are three types of access modifiers in Python: public, private, and protected.
Variables with the public access modifiers can be accessed anywhere inside or outside the class, the private variables can only be accessed inside the class, while protected variables can be accessed within the same package.
To create a private variable, you need to prefix double underscores with the name of the variable. To create a protected variable, you need to prefix a single underscore with the variable name. For public variables, you do not have to add any prefixes at all.
Let's see public, private, and protected variables in action. Execute the following script:
class Car: def __init__(self): print ("Engine started") self.name = "corolla" self.__make = "toyota" self._model = 1999
In the script above, we create a simple
Car class with a constructor and three variables
name variable is public while the
model variables have been declared private and protected, respectively.
Let's create an object of the
Car class and try to access the
name variable. Execute the following script:
car_a = Car() print(car_a.name)
name is a public variable, therefore we can access it outside the class. In the output, you will see the value for the
name printed on the console.
Now let's try to print the value of the
make variable. Execute the following script:
In the output, you will see the following error message:
AttributeError: 'Car' object has no attribute 'make'
We have covered most of the basic object-oriented programming concepts in the last few sections. Now, let's talk about the pillars of the object-oriented programming: Polymorphism, Inheritance, and Encapsulation, collectively referred to as PIE.
Inheritance in object-oriented programming is pretty similar to real-world inheritance where a child inherits some of the characteristics from his parents, in addition to his/her own unique characteristics.
In object-oriented programming, inheritance signifies an IS-A relation. For instance, a car is a vehicle. Inheritance is one of the most amazing concepts of object-oriented programming as it fosters code re-usability.
The basic idea of inheritance in object-oriented programming is that a class can inherit the characteristics of another class. The class which inherits another class is called the child class or derived class, and the class which is inherited by another class is called parent or base class.
Let's take a look at a very simple example of inheritance. Execute the following script:
# Create Class Vehicle class Vehicle: def vehicle_method(self): print("This is parent Vehicle class method") # Create Class Car that inherits Vehicle class Car(Vehicle): def car_method(self): print("This is child Car class method")
In the script above, we create two classes
Vehicle class, and the
Car class which inherits the
Vehicle class. To inherit a class, you simply have to write the parent class name inside the parenthesis that follows the child class name. The
Vehicle class contains a method
vehicle_method() and the child class contains a method
car_method(). However, since the
Car class inherits the
Vehicle class, it will also inherit the
Let's see this in action. Execute the following script:
car_a = Car() car_a.vehicle_method() # Calling parent class method
In the script above, we create an object of the
Car class and call the
vehicle_method() using that
Car class object. You can see that the
Car class doesn't have any
vehicle_method() but since it has inherited the
Vehicle class that contains the
vehicle_method(), the car class can also use it. The output looks likes this:
This is parent Vehicle class method
In Python, a parent class can have multiple children and similarly, a child class can have multiple parent classes. Let's take a look at the first scenario. Execute the following script:
# Create Class Vehicle class Vehicle: def vehicle_method(self): print("This is parent Vehicle class method") # Create Class Car that inherits Vehicle class Car(Vehicle): def car_method(self): print("This is child Car class method") # Create Class Cycle that inherits Vehicle class Cycle(Vehicle): def cycleMethod(self): print("This is child Cycle class method")
In the script above the parent
Vehicle class is inherited by two child classes
Cycle. Both the child classes will have access to the
vehicle_method() of the parent class. Execute the following script to see that:
car_a = Car() car_a.vehicle_method() # Calling parent class method car_b = Cycle() car_b.vehicle_method() # Calling parent class method
In the output, you will see the output of the
vehicle_method() method twice as shown below:
This is parent Vehicle class method This is parent Vehicle class method
You can see how a parent class can be inherited by two child classes. In the same way, a child can have multiple parents. Let's take a look at the example:
class Camera: def camera_method(self): print("This is parent Camera class method") class Radio: def radio_method(self): print("This is parent Radio class method") class CellPhone(Camera, Radio): def cell_phone_method(self): print("This is child CellPhone class method")
In the script above, we create three classes:
Camera class and the
Radio classes are inherited by the
CellPhoneclass which means that the
CellPhone class will have access to the methods of both
Radio classes. The following script verifies this:
cell_phone_a = CellPhone() cell_phone_a.camera_method() cell_phone_a.radio_method()
The output looks likes this:
This is parent Camera class method This is parent Radio class method
The term polymorphism literally means having multiple forms. In the context of object-oriented programming, polymorphism refers to the ability of an object to behave in multiple ways.
Polymorphism in programming is implemented via method-overloading and method overriding.
Method overloading refers to the property of a method to behave in different ways depending upon the number or types of the parameters. Take a look at a very simple example of method overloading. Execute the following script:
# Creates class Car class Car: def start(self, a, b=None): if b is not None: print (a + b) else: print (a)
In the script above, if the
start() method is called by passing a single argument, the parameter will be printed on the screen. However, if we pass 2 arguments to the
start() method, it will add both the arguments and will print the result of the sum.
Let's try with single argument first:
car_a = Car() car_a.start(10)
In the output, you will see 10. Now let's try to pass 2 arguments:
In the output, you will see 30.
Method overriding refers to having a method with the same name in the child class as in the parent class. The definition of the method differs in parent and child classes but the name remains the same. Let's take a simple example method overriding in Python.
# Create Class Vehicle class Vehicle: def print_details(self): print("This is parent Vehicle class method") # Create Class Car that inherits Vehicle class Car(Vehicle): def print_details(self): print("This is child Car class method") # Create Class Cycle that inherits Vehicle class Cycle(Vehicle): def print_details(self): print("This is child Cycle class method")
In the script above the
Cycle classes inherit the
Vehicle class. The vehicle class has
print_details() method, which is overridden by the child classes. Now if you call the
print_details() method, the output will depend upon the object through which the method is being called. Execute the following script to see this concept in action:
car_a = Vehicle() car_a. print_details() car_b = Car() car_b.print_details() car_c = Cycle() car_c.print_details()
The output will look like this:
This is parent Vehicle class method This is child Car class method This is child Cycle class method
You can see that the output is different, although the
print_details() method is being called through derived classes of the same base class. However, since the child classes have overridden the parent class method, the methods behave differently.
Encapsulation is the third pillar of object-oriented programming. Encapsulation simply refers to data hiding. As a general principle, in object-oriented programming, one class should not have direct access to the data of the other class. Rather, the access should be controlled via class methods.
To provide controlled access to class data in Python, the access modifiers and properties are used. We have already seen access modifiers, in this section, we will see properties in action.
Suppose we want to ensure that the car model should always be between 2000 and 2018. If a user tries to enter a value less than 2000 for the car model, the value is automatically set to 2000 and if the entered value is greater than 2018, it should be set to 2018. If the value is between 2000 and 2018, it should not be changed. We can create a property for the model attribute which implements this logic as follows:
# Creates class Car class Car: # Creates Car class constructor def __init__(self, model): # initialize instance variables self.model = model # Creates model property def model(self): return self.__model # Create property setter def model(self, model): if model < 2000: self.__model = 2000 elif model > 2018: self.__model = 2018 else: self.__model = model def getCarModel(self): return "The car model is " + str(self.model) carA = Car(2088) print(carA.getCarModel())
A property has three parts. You have to define the attribute, which is
model in the above script. Next, you have to define the property for the attribute using the @property decorator. Finally, you have to create property setter which is
@model.setter descriptor in the above script.
Now, if you try to enter a value greater than 2018 for the model attribute, you will see that the value is set to 2018. Let's test this. Execute the following script:
car_a = Car(2088) print(car_a.get_car_model())
Here we are passing 2088 as the value for
model, however if you print the value for the
model attribute via
get_car_model() function, you will see 2018 in the output.
In this article, we studied some of the most important object-oriented programming concepts. Object-oriented programming is one of the most famous and commonly used programming paradigms. The importance of object-oriented programming is reflected by the fact that most of the modern programming languages are either fully object-oriented or support object-oriented programming.