Object Oriented Programming.pptx

Object Oriented Programming
Encapsulation, Inheritance, and
Polymorphism

Python Objects and Class
• You’ll learn about the core functionality of Python, Python objects and
classes.
• You'll learn what a class is, how to create it and use it in your program.
• Python is an object oriented programming language.
• Unlike procedure oriented programming, where the main emphasis is on
functions, object oriented programming stress on objects.
• Object is simply a collection of data (variables) and methods (functions) that
act on those data.
• Class is a blueprint for the object.
• We can think of class as a sketch (prototype) of a house. It contains all the
details about the floors, doors, windows etc.
• Based on these descriptions we build the house. House is the object.
• As, many houses can be made from a description, we can create many objects
from a class.
• An object is also called an instance of a class and the process of creating this
object is called instantiation.

Defining a Class in Python:
• Like function definitions begin with the keyword def, in Python, we define
a class using the keyword class.
• The first string is called docstring and has a brief description about the
class.
• Although not mandatory, this is recommended.
• Here is a simple class definition.
class MyNewClass:
'''This is a docstring. I have created a new class'''
pass
• A class creates a new local namespace where all its attributes are defined.
Attributes may be data or functions.
• There are also special attributes in it that begins with double underscores
(__).
• For example, __doc__ gives us the docstring of that class.
• As soon as we define a class, a new class object is created with the same
name.
• This class object allows us to access the different attributes as well as to
instantiate new objects of that class

• Here, the self is used as a reference variable, which refers to the
current class object.
• It is always the first argument in the function definition. However,
using self is optional in the function call.
The self-parameter
• The self-parameter refers to the current instance of the class and
accesses the class variables.
• We can use anything instead of self, but it must be the first parameter
of any function which belongs to the class.

Creating an Object in Python
• We saw that the class object could be used to access different
attributes.
• It can also be used to create new object instances (instantiation) of
that class.
• The procedure to create an object is similar to a function call.
>>> ob = MyClass()
• This will create a new instance object named ob. We can access
attributes of objects using the object name prefix.
• Attributes may be data or method.
• Method of an object are corresponding functions of that class.
• Any function object that is a class attribute defines a method for
objects of that class.
• This means to say, since MyClass.func is a function object (attribute of
class), ob.func will be a method object.

• You may have noticed the self parameter in function definition inside the
class but, we called the method simply as ob.func() without any
arguments. It still worked.
• This is because, whenever an object calls its method, the object itself is
passed as the first argument.
• So, ob.func() translates into MyClass.func(ob).
• In general, calling a method with a list of n arguments is equivalent to
calling the corresponding function with an argument list that is
created by inserting the method's object before the first argument.
• For these reasons, the first argument of the function in class must
be the object itself.
• This is conventionally called self.
• It can be named otherwise but we highly recommend to follow the
convention.
• Now you must be familiar with class object, instance object, function
object, method object and their differences.

Constructors in Python
• Class functions that begins with double underscore (__) are called
special functions as they have special meaning.
• Of one particular interest is the __init__() function.
• This special function gets called whenever a new object of that class
is instantiated.
• This type of function is also called constructors in Object Oriented
Programming (OOP).
• We normally use it to initialize all the variables.

• In the above example, we define a new class to represent complex
numbers.
• It has two functions, __init__() to initialize the variables (defaults to
zero) and getData() to display the number properly.
• An interesting thing to note in the above step is that attributes of an
object can be created on the fly.
• We created a new attribute attr for object c2 and we read it as well.
• But this did not create that attribute for object c1.

Deleting Attributes and Objects:
• Any attribute of an object can be deleted anytime, using the del
statement. Try the following on the Python shell to see the output.

• Actually, it is more complicated than that.
• When we do c1 = ComplexNumber(1,3), a new instance object is
created in memory and the name c1 binds with it.
• On the command del c1, this binding is removed and the name c1 is
deleted from the corresponding namespace.
• The object however continues to exist in memory and if no other
name is bound to it, it is later automatically destroyed.
• This automatic destruction of unreferenced objects in Python is also
called garbage collection.

Python Inheritance
• Inheritance enables us to define a class that takes all the functionality from parent
class and allows us to add more.
• In this article, you will learn to use inheritance in Python.
• Inheritance is a powerful feature in object oriented programming.
• It refers to defining a new class with little or no modification to an existing class.
• The new class is called derived (or child) class and the one from which it
inherits is called the base (or parent) class.
Python Inheritance Syntax:
class BaseClass:
Body of base class
class DerivedClass(BaseClass):
Body of derived class
• Derived class inherits features from the base class, adding new features to it. This
results into reusability of code.

Example of Inheritance in Python:
• To demonstrate the use of inheritance, let us take an example.
• A polygon is a closed figure with 3 or more sides. Say, we have a class
called Polygon defined as follows.

• Polygon class has data attributes to store the number of sides, n and
magnitude of each side as a list, sides.
• Method inputSides() takes in magnitude of each side and similarly, dispSides()
will display these properly.
• A triangle is a polygon with 3 sides.
• So, we can created a class called Triangle which inherits from Polygon.
• This makes all the attributes available in class Polygon readily available in
Triangle.
• We don't need to define them again (code re-usability).
• Triangle class is defined in the above code.
• However, class Triangle has a new method findArea() to find and print the
area of the triangle.
• We can see that, even though we did not define methods like inputSides() or
dispSides() for class Triangle, we were able to use them.
• If an attribute is not found in the class, search continues to the base class.
• This repeats recursively, if the base class is itself derived from other classes.

Method Overriding in Python
• In the above example, notice that __init__() method was defined in both
classes, Triangle as well Polygon.
• When this happens, the method in the derived class overrides that in
the base class.
• This is to say, __init__() in Triangle gets preference over the same in
Polygon.
• Generally when overriding a base method, we tend to extend the
definition rather than simply replace it.
• The same is being done by calling the method in base class from the
one in derived class (calling Polygon.__init__() from __init__() in
Triangle).
• A better option would be to use the built-in function super().

• So, super().__init__(3) is equivalent to Polygon.__init__(self,3) and is
preferred. You can learn more about the super() function in
Python.
• Two built-in functions isinstance() and issubclass() are used to
check inheritances.
• Function isinstance() returns True if the object is an instance of the
class or other classes derived from it.
• Each and every class in Python inherits from the base class object.

Similarly, issubclass() is used to check for class inheritance.

Python Multiple Inheritance
• You’ll learn what is multiple inheritance in Python and how to use it in
your program.
• You'll also learn about multilevel inheritance and the method
resolution order.
• Like C++, a class can be derived from more than one base classes in
Python. This is called multiple inheritance.
• In multiple inheritance, the features of all the base classes are
inherited into the derived class.
• The syntax for multiple inheritance is similar to single inheritance.
Python Multiple Inheritance Example:
class Base1:
pass
class Base2:
pass
class MultiDerived(Base1, Base2):
pass

Here, MultiDerived is derived from classes Base1 and Base2.
The class MultiDerived inherits from both Base1 and Base2.

Multilevel Inheritance in Python:
• On the other hand, we can also inherit form a derived class.
• This is called multilevel inheritance.
• It can be of any depth in Python.
• In multilevel inheritance, features of the base class and the derived
class is inherited into the new derived class.
• An example with corresponding visualization is given below.
class Base:
pass
class Derived1(Base):
pass
class Derived2(Derived1):
pass
• Here, Derived1 is derived from Base, and Derived2 is derived from
Derived1

Method Resolution Order in Python
• Every class in Python is derived from the class object. It is the most
base type in Python.
• So technically, all other class, either built-in or user-defines, are
derived classes and all objects are instances of object class.
# Output: True
print(issubclass(list,object))
# Output: True
print(isinstance(5.5,object))
# Output: True
print(isinstance("Hello",object))

• In the multiple inheritance scenario, any specified attribute is searched first in
the current class.
• If not found, the search continues into parent classes in depth-first, left-right
fashion without searching same class twice.
• So, in the above example of MultiDerived class the search order is
[MultiDerived, Base1, Base2, object].
• This order is also called linearization of MultiDerived class and the set of rules
used to find this order is called Method Resolution Order (MRO).
• MRO must prevent local precedence ordering and also provide monotonicity.
• It ensures that a class always appears before its parents and in case of
multiple parents, the order is same as tuple of base classes.
• MRO of a class can be viewed as the __mro__ attribute or mro() method. The
former returns a tuple while latter returns a list

Here is a little more complex multiple inheritance example and its visualization along with
the MRO.

Encapsulation
• Using OOP in Python, we can restrict access to methods and variables.
• This prevents data from direct modification which is called
encapsulation.
• In Python, we denote private attributes using underscore as the prefix
i.e single _ or double __.
Example 4: Data Encapsulation in Python

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()

Output
Selling Price: 900
Selling Price: 900
Selling Price: 1000
• In the above program, we defined a Computer class.
• We used __init__() method to store the maximum selling price
of Computer. Here, notice the code
c.__maxprice = 1000
• Here, we have tried to modify the value of __maxprice outside of
the class.
• However, since __maxprice is a private variable, this modification is
not seen on the output.
• As shown, to change the value, we have to use a setter function
i.e setMaxPrice() which takes price as a parameter.

Polymorphism
• Polymorphism is an ability (in OOP) to use a common interface for
multiple forms (data types).
• Suppose, we need to color a shape, there are multiple shape options
(rectangle, square, circle).
• However we could use the same method to color any shape. This concept
is called Polymorphism.
• Example 5: Using Polymorphism in Python

class Parrot:
def fly(self):
print("Parrot can fly")
def swim(self):
print("Parrot can't swim")
class Penguin:
def fly(self):
print("Penguin can't fly")
def swim(self):
print("Penguin can swim")
# common interface
def flying_test(bird):
bird.fly()
#instantiate objects
blu = Parrot()
peggy = Penguin()
# passing the object
flying_test(blu)
flying_test(peggy)

Output
• Parrot can fly Penguin can't flyIn the above program, we defined two
classes Parrot and Penguin.
• Each of them have a common fly() method. However, their functions
are different.
• To use polymorphism, we created a common interface
i.e flying_test() function that takes any object and calls the
object's fly() method.
• Thus, when we passed the blu and peggy objects in
the flying_test() function, it ran effectively.

Points to Remember:
• Object-Oriented Programming makes the program easy to understand
as well as efficient.
• Since the class is sharable, the code can be reused.
• Data is safe and secure with data abstraction.
• Polymorphism allows the same interface for different objects, so
programmers can write efficient code.

Object Oriented Programming.pptx

More Related Content

Similar to Object Oriented Programming.pptx (20)

Recently uploaded (20)

Object Oriented Programming.pptx