Chapter 6: Object-Oriented Programming in Python
6.2 Polymorphism and Encapsulation
6.2.1 Polymorphism
In object-oriented programming, polymorphism refers to the ability of an object to take on many forms. This means that a single class can be used in multiple ways, or a child class can change the way some methods behave compared to its parent.
Polymorphism is a powerful tool for software developers, as it allows for more flexible and adaptable code. For example, imagine a program that handles different types of shapes, such as circles, squares, and rectangles. Instead of creating separate classes for each shape, a developer could create a single "Shape" class that defines basic properties and methods, then create child classes for each specific shape.
These child classes could have their own unique properties and methods, but they would also inherit the properties and methods of the parent "Shape" class. This means that the developer could write code that works with any kind of shape, without having to worry about the specific details of each shape.
Furthermore, if the developer needs to add a new type of shape to the program, they can simply create a new child class that inherits from the "Shape" class. This makes the code more scalable and easier to maintain over time.
In conclusion, polymorphism is a key concept in object-oriented programming that allows for more flexible, adaptable, and scalable code. By using polymorphism effectively, developers can create programs that are easier to understand, modify, and extend over time.
Example:
The best way to understand this is through an example.
class Bird:
def intro(self):
print("There are many types of birds.")
def flight(self):
print("Most of the birds can fly but some cannot.")
class Sparrow(Bird):
def flight(self):
print("Sparrows can fly.")
class Ostrich(Bird):
def flight(self):
print("Ostriches cannot fly.")
obj_bird = Bird()
obj_spr = Sparrow()
obj_ost = Ostrich()
obj_bird.intro()
obj_bird.flight()
obj_spr.intro()
obj_spr.flight()
obj_ost.intro()
obj_ost.flight()In the above program, we defined two classes Sparrow and Ostrich, both inheriting Bird. The flight method in Sparrow and Ostrich is working differently, hence showing polymorphism.
6.2.2 Encapsulation
Encapsulation is a crucial concept in object-oriented programming. It involves bundling data along with the methods that manipulate it into a single unit. By doing so, encapsulation protects the data from being tampered with or misused by external factors.
Python provides a way to limit access to methods and variables through the use of leading underscores(). This technique is known as encapsulation, which can help to maintain data integrity by preventing direct modification. Additionally, we can create class methods as private by adding a double underscore() in front of the method name. This further enhances encapsulation by making the method inaccessible from external sources.
Overall, encapsulation serves as a cornerstone of object-oriented programming by providing a means of protecting data and ensuring its proper use within a program. By understanding the importance of encapsulation and how it can be implemented in Python, programmers can write more secure and robust code.
Example:
class Computer:
def __init__(self):
self.__maxprice = 900
def sell(self):
print("Selling Price: {}".format(self.__maxprice))
def setMaxPrice(self, price):
self.__maxprice = price
c = Computer()
c.sell()
# change the price
c.__maxprice = 1000
c.sell()
# using setter function
c.setMaxPrice(1000)
c.sell()In the above program, we defined a Computer class and used __init__() method to store the maximum selling price of Computer. We tried to modify the price. However, we can't change it because Python treats the __maxprice as private attributes. As a Python programmer, to make this attribute private and unseen to the outsiders, we use double underscore (__) before the attributes and methods name. However, Python provides us the privilege to update the value, using setter methods. So, to change the value, we have used setMaxPrice() method.
In a nutshell, encapsulation is a fundamental concept in Object-Oriented Programming (OOP) that involves wrapping data and the methods that manipulate the data into one single entity. This helps to prevent accidental modification of the data. Encapsulation is a way of ensuring that an object's internal state cannot be tampered with directly from outside the object, but can only be accessed or modified through its methods, ensuring its integrity.
In addition, encapsulation also helps to improve code organization and maintainability. By encapsulating data and methods into a single entity, the code becomes more modular and easier to understand. This makes it easier to modify and maintain the code over time.
Furthermore, when combined with Polymorphism, encapsulation becomes even more powerful. Polymorphism is the ability of an object to take on many forms. This means that an object can be used in different contexts and can behave differently depending on the context in which it is used. Together with encapsulation, polymorphism allows for more efficient and flexible code that can adapt to different situations.
Therefore, it is important to understand the principles of encapsulation and polymorphism in order to write efficient, organized, and maintainable code in OOP. By implementing these principles, developers can create code that is more robust, flexible, and adaptable to changing requirements and environments.
With Polymorphism, Python's "duck typing" enables you to use any object that provides the required behavior without forcing it to be a subclass of any particular class or implement any specific interface. This leads to more reusable and cleaner code.
With Encapsulation, you are ensuring that the object's internal state cannot be changed except through its own methods. This encapsulation provides a shield that protects the data from getting altered by external methods. It also allows objects to interact in a complex system without needing to know too much about each other, making code more maintainable and flexible to change.
Moreover, combining these principles with the ones discussed before (i.e., inheritance, super, and overriding methods), you can write Python programs that leverage the full benefits of object-oriented programming. This can lead to code that is more readable, reusable, and easy to maintain or update.
In the next topic, we will continue to explore object-oriented programming by discussing more advanced features, including magic methods and classmethods/staticmethods. This will allow you to further leverage the power of Python's flexible object model.
Now that we have a good understanding of Python's implementation of classes, objects, inheritance, polymorphism, and encapsulation, we can continue to expand our knowledge on more advanced topics in the coming sections.
6.2 Polymorphism and Encapsulation
6.2.1 Polymorphism
In object-oriented programming, polymorphism refers to the ability of an object to take on many forms. This means that a single class can be used in multiple ways, or a child class can change the way some methods behave compared to its parent.
Polymorphism is a powerful tool for software developers, as it allows for more flexible and adaptable code. For example, imagine a program that handles different types of shapes, such as circles, squares, and rectangles. Instead of creating separate classes for each shape, a developer could create a single "Shape" class that defines basic properties and methods, then create child classes for each specific shape.
These child classes could have their own unique properties and methods, but they would also inherit the properties and methods of the parent "Shape" class. This means that the developer could write code that works with any kind of shape, without having to worry about the specific details of each shape.
Furthermore, if the developer needs to add a new type of shape to the program, they can simply create a new child class that inherits from the "Shape" class. This makes the code more scalable and easier to maintain over time.
In conclusion, polymorphism is a key concept in object-oriented programming that allows for more flexible, adaptable, and scalable code. By using polymorphism effectively, developers can create programs that are easier to understand, modify, and extend over time.
Example:
The best way to understand this is through an example.
class Bird:
def intro(self):
print("There are many types of birds.")
def flight(self):
print("Most of the birds can fly but some cannot.")
class Sparrow(Bird):
def flight(self):
print("Sparrows can fly.")
class Ostrich(Bird):
def flight(self):
print("Ostriches cannot fly.")
obj_bird = Bird()
obj_spr = Sparrow()
obj_ost = Ostrich()
obj_bird.intro()
obj_bird.flight()
obj_spr.intro()
obj_spr.flight()
obj_ost.intro()
obj_ost.flight()In the above program, we defined two classes Sparrow and Ostrich, both inheriting Bird. The flight method in Sparrow and Ostrich is working differently, hence showing polymorphism.
6.2.2 Encapsulation
Encapsulation is a crucial concept in object-oriented programming. It involves bundling data along with the methods that manipulate it into a single unit. By doing so, encapsulation protects the data from being tampered with or misused by external factors.
Python provides a way to limit access to methods and variables through the use of leading underscores(). This technique is known as encapsulation, which can help to maintain data integrity by preventing direct modification. Additionally, we can create class methods as private by adding a double underscore() in front of the method name. This further enhances encapsulation by making the method inaccessible from external sources.
Overall, encapsulation serves as a cornerstone of object-oriented programming by providing a means of protecting data and ensuring its proper use within a program. By understanding the importance of encapsulation and how it can be implemented in Python, programmers can write more secure and robust code.
Example:
class Computer:
def __init__(self):
self.__maxprice = 900
def sell(self):
print("Selling Price: {}".format(self.__maxprice))
def setMaxPrice(self, price):
self.__maxprice = price
c = Computer()
c.sell()
# change the price
c.__maxprice = 1000
c.sell()
# using setter function
c.setMaxPrice(1000)
c.sell()In the above program, we defined a Computer class and used __init__() method to store the maximum selling price of Computer. We tried to modify the price. However, we can't change it because Python treats the __maxprice as private attributes. As a Python programmer, to make this attribute private and unseen to the outsiders, we use double underscore (__) before the attributes and methods name. However, Python provides us the privilege to update the value, using setter methods. So, to change the value, we have used setMaxPrice() method.
In a nutshell, encapsulation is a fundamental concept in Object-Oriented Programming (OOP) that involves wrapping data and the methods that manipulate the data into one single entity. This helps to prevent accidental modification of the data. Encapsulation is a way of ensuring that an object's internal state cannot be tampered with directly from outside the object, but can only be accessed or modified through its methods, ensuring its integrity.
In addition, encapsulation also helps to improve code organization and maintainability. By encapsulating data and methods into a single entity, the code becomes more modular and easier to understand. This makes it easier to modify and maintain the code over time.
Furthermore, when combined with Polymorphism, encapsulation becomes even more powerful. Polymorphism is the ability of an object to take on many forms. This means that an object can be used in different contexts and can behave differently depending on the context in which it is used. Together with encapsulation, polymorphism allows for more efficient and flexible code that can adapt to different situations.
Therefore, it is important to understand the principles of encapsulation and polymorphism in order to write efficient, organized, and maintainable code in OOP. By implementing these principles, developers can create code that is more robust, flexible, and adaptable to changing requirements and environments.
With Polymorphism, Python's "duck typing" enables you to use any object that provides the required behavior without forcing it to be a subclass of any particular class or implement any specific interface. This leads to more reusable and cleaner code.
With Encapsulation, you are ensuring that the object's internal state cannot be changed except through its own methods. This encapsulation provides a shield that protects the data from getting altered by external methods. It also allows objects to interact in a complex system without needing to know too much about each other, making code more maintainable and flexible to change.
Moreover, combining these principles with the ones discussed before (i.e., inheritance, super, and overriding methods), you can write Python programs that leverage the full benefits of object-oriented programming. This can lead to code that is more readable, reusable, and easy to maintain or update.
In the next topic, we will continue to explore object-oriented programming by discussing more advanced features, including magic methods and classmethods/staticmethods. This will allow you to further leverage the power of Python's flexible object model.
Now that we have a good understanding of Python's implementation of classes, objects, inheritance, polymorphism, and encapsulation, we can continue to expand our knowledge on more advanced topics in the coming sections.
6.2 Polymorphism and Encapsulation
6.2.1 Polymorphism
In object-oriented programming, polymorphism refers to the ability of an object to take on many forms. This means that a single class can be used in multiple ways, or a child class can change the way some methods behave compared to its parent.
Polymorphism is a powerful tool for software developers, as it allows for more flexible and adaptable code. For example, imagine a program that handles different types of shapes, such as circles, squares, and rectangles. Instead of creating separate classes for each shape, a developer could create a single "Shape" class that defines basic properties and methods, then create child classes for each specific shape.
These child classes could have their own unique properties and methods, but they would also inherit the properties and methods of the parent "Shape" class. This means that the developer could write code that works with any kind of shape, without having to worry about the specific details of each shape.
Furthermore, if the developer needs to add a new type of shape to the program, they can simply create a new child class that inherits from the "Shape" class. This makes the code more scalable and easier to maintain over time.
In conclusion, polymorphism is a key concept in object-oriented programming that allows for more flexible, adaptable, and scalable code. By using polymorphism effectively, developers can create programs that are easier to understand, modify, and extend over time.
Example:
The best way to understand this is through an example.
class Bird:
def intro(self):
print("There are many types of birds.")
def flight(self):
print("Most of the birds can fly but some cannot.")
class Sparrow(Bird):
def flight(self):
print("Sparrows can fly.")
class Ostrich(Bird):
def flight(self):
print("Ostriches cannot fly.")
obj_bird = Bird()
obj_spr = Sparrow()
obj_ost = Ostrich()
obj_bird.intro()
obj_bird.flight()
obj_spr.intro()
obj_spr.flight()
obj_ost.intro()
obj_ost.flight()In the above program, we defined two classes Sparrow and Ostrich, both inheriting Bird. The flight method in Sparrow and Ostrich is working differently, hence showing polymorphism.
6.2.2 Encapsulation
Encapsulation is a crucial concept in object-oriented programming. It involves bundling data along with the methods that manipulate it into a single unit. By doing so, encapsulation protects the data from being tampered with or misused by external factors.
Python provides a way to limit access to methods and variables through the use of leading underscores(). This technique is known as encapsulation, which can help to maintain data integrity by preventing direct modification. Additionally, we can create class methods as private by adding a double underscore() in front of the method name. This further enhances encapsulation by making the method inaccessible from external sources.
Overall, encapsulation serves as a cornerstone of object-oriented programming by providing a means of protecting data and ensuring its proper use within a program. By understanding the importance of encapsulation and how it can be implemented in Python, programmers can write more secure and robust code.
Example:
class Computer:
def __init__(self):
self.__maxprice = 900
def sell(self):
print("Selling Price: {}".format(self.__maxprice))
def setMaxPrice(self, price):
self.__maxprice = price
c = Computer()
c.sell()
# change the price
c.__maxprice = 1000
c.sell()
# using setter function
c.setMaxPrice(1000)
c.sell()In the above program, we defined a Computer class and used __init__() method to store the maximum selling price of Computer. We tried to modify the price. However, we can't change it because Python treats the __maxprice as private attributes. As a Python programmer, to make this attribute private and unseen to the outsiders, we use double underscore (__) before the attributes and methods name. However, Python provides us the privilege to update the value, using setter methods. So, to change the value, we have used setMaxPrice() method.
In a nutshell, encapsulation is a fundamental concept in Object-Oriented Programming (OOP) that involves wrapping data and the methods that manipulate the data into one single entity. This helps to prevent accidental modification of the data. Encapsulation is a way of ensuring that an object's internal state cannot be tampered with directly from outside the object, but can only be accessed or modified through its methods, ensuring its integrity.
In addition, encapsulation also helps to improve code organization and maintainability. By encapsulating data and methods into a single entity, the code becomes more modular and easier to understand. This makes it easier to modify and maintain the code over time.
Furthermore, when combined with Polymorphism, encapsulation becomes even more powerful. Polymorphism is the ability of an object to take on many forms. This means that an object can be used in different contexts and can behave differently depending on the context in which it is used. Together with encapsulation, polymorphism allows for more efficient and flexible code that can adapt to different situations.
Therefore, it is important to understand the principles of encapsulation and polymorphism in order to write efficient, organized, and maintainable code in OOP. By implementing these principles, developers can create code that is more robust, flexible, and adaptable to changing requirements and environments.
With Polymorphism, Python's "duck typing" enables you to use any object that provides the required behavior without forcing it to be a subclass of any particular class or implement any specific interface. This leads to more reusable and cleaner code.
With Encapsulation, you are ensuring that the object's internal state cannot be changed except through its own methods. This encapsulation provides a shield that protects the data from getting altered by external methods. It also allows objects to interact in a complex system without needing to know too much about each other, making code more maintainable and flexible to change.
Moreover, combining these principles with the ones discussed before (i.e., inheritance, super, and overriding methods), you can write Python programs that leverage the full benefits of object-oriented programming. This can lead to code that is more readable, reusable, and easy to maintain or update.
In the next topic, we will continue to explore object-oriented programming by discussing more advanced features, including magic methods and classmethods/staticmethods. This will allow you to further leverage the power of Python's flexible object model.
Now that we have a good understanding of Python's implementation of classes, objects, inheritance, polymorphism, and encapsulation, we can continue to expand our knowledge on more advanced topics in the coming sections.
6.2 Polymorphism and Encapsulation
6.2.1 Polymorphism
In object-oriented programming, polymorphism refers to the ability of an object to take on many forms. This means that a single class can be used in multiple ways, or a child class can change the way some methods behave compared to its parent.
Polymorphism is a powerful tool for software developers, as it allows for more flexible and adaptable code. For example, imagine a program that handles different types of shapes, such as circles, squares, and rectangles. Instead of creating separate classes for each shape, a developer could create a single "Shape" class that defines basic properties and methods, then create child classes for each specific shape.
These child classes could have their own unique properties and methods, but they would also inherit the properties and methods of the parent "Shape" class. This means that the developer could write code that works with any kind of shape, without having to worry about the specific details of each shape.
Furthermore, if the developer needs to add a new type of shape to the program, they can simply create a new child class that inherits from the "Shape" class. This makes the code more scalable and easier to maintain over time.
In conclusion, polymorphism is a key concept in object-oriented programming that allows for more flexible, adaptable, and scalable code. By using polymorphism effectively, developers can create programs that are easier to understand, modify, and extend over time.
Example:
The best way to understand this is through an example.
class Bird:
def intro(self):
print("There are many types of birds.")
def flight(self):
print("Most of the birds can fly but some cannot.")
class Sparrow(Bird):
def flight(self):
print("Sparrows can fly.")
class Ostrich(Bird):
def flight(self):
print("Ostriches cannot fly.")
obj_bird = Bird()
obj_spr = Sparrow()
obj_ost = Ostrich()
obj_bird.intro()
obj_bird.flight()
obj_spr.intro()
obj_spr.flight()
obj_ost.intro()
obj_ost.flight()In the above program, we defined two classes Sparrow and Ostrich, both inheriting Bird. The flight method in Sparrow and Ostrich is working differently, hence showing polymorphism.
6.2.2 Encapsulation
Encapsulation is a crucial concept in object-oriented programming. It involves bundling data along with the methods that manipulate it into a single unit. By doing so, encapsulation protects the data from being tampered with or misused by external factors.
Python provides a way to limit access to methods and variables through the use of leading underscores(). This technique is known as encapsulation, which can help to maintain data integrity by preventing direct modification. Additionally, we can create class methods as private by adding a double underscore() in front of the method name. This further enhances encapsulation by making the method inaccessible from external sources.
Overall, encapsulation serves as a cornerstone of object-oriented programming by providing a means of protecting data and ensuring its proper use within a program. By understanding the importance of encapsulation and how it can be implemented in Python, programmers can write more secure and robust code.
Example:
class Computer:
def __init__(self):
self.__maxprice = 900
def sell(self):
print("Selling Price: {}".format(self.__maxprice))
def setMaxPrice(self, price):
self.__maxprice = price
c = Computer()
c.sell()
# change the price
c.__maxprice = 1000
c.sell()
# using setter function
c.setMaxPrice(1000)
c.sell()In the above program, we defined a Computer class and used __init__() method to store the maximum selling price of Computer. We tried to modify the price. However, we can't change it because Python treats the __maxprice as private attributes. As a Python programmer, to make this attribute private and unseen to the outsiders, we use double underscore (__) before the attributes and methods name. However, Python provides us the privilege to update the value, using setter methods. So, to change the value, we have used setMaxPrice() method.
In a nutshell, encapsulation is a fundamental concept in Object-Oriented Programming (OOP) that involves wrapping data and the methods that manipulate the data into one single entity. This helps to prevent accidental modification of the data. Encapsulation is a way of ensuring that an object's internal state cannot be tampered with directly from outside the object, but can only be accessed or modified through its methods, ensuring its integrity.
In addition, encapsulation also helps to improve code organization and maintainability. By encapsulating data and methods into a single entity, the code becomes more modular and easier to understand. This makes it easier to modify and maintain the code over time.
Furthermore, when combined with Polymorphism, encapsulation becomes even more powerful. Polymorphism is the ability of an object to take on many forms. This means that an object can be used in different contexts and can behave differently depending on the context in which it is used. Together with encapsulation, polymorphism allows for more efficient and flexible code that can adapt to different situations.
Therefore, it is important to understand the principles of encapsulation and polymorphism in order to write efficient, organized, and maintainable code in OOP. By implementing these principles, developers can create code that is more robust, flexible, and adaptable to changing requirements and environments.
With Polymorphism, Python's "duck typing" enables you to use any object that provides the required behavior without forcing it to be a subclass of any particular class or implement any specific interface. This leads to more reusable and cleaner code.
With Encapsulation, you are ensuring that the object's internal state cannot be changed except through its own methods. This encapsulation provides a shield that protects the data from getting altered by external methods. It also allows objects to interact in a complex system without needing to know too much about each other, making code more maintainable and flexible to change.
Moreover, combining these principles with the ones discussed before (i.e., inheritance, super, and overriding methods), you can write Python programs that leverage the full benefits of object-oriented programming. This can lead to code that is more readable, reusable, and easy to maintain or update.
In the next topic, we will continue to explore object-oriented programming by discussing more advanced features, including magic methods and classmethods/staticmethods. This will allow you to further leverage the power of Python's flexible object model.
Now that we have a good understanding of Python's implementation of classes, objects, inheritance, polymorphism, and encapsulation, we can continue to expand our knowledge on more advanced topics in the coming sections.