OOP in Python, a beginners guide..........

7/26/2014 VYBHAVA TECHNOLOGIES 1

Contents
> Differences Procedure vs Object Oriented Programming
> Features of OOP
> Fundamental Concepts of OOP in Python
> What is Class
> What is Object
> Methods in Classes
Instantiating objects with __init__
self
> Encapsulation
> Data Abstraction
> Public, Protected and Private Data
> Inheritance
> Polymorphism
> Operator Overloading

Difference between Procedure Oriented and
Object Oriented Programming
Procedural programming creates a step by step program that
guides the application through a sequence of instructions. Each
instruction is executed in order.
Procedural programming also focuses on the idea that all
algorithms are executed with functions and data that the
programmer has access to and is able to change.
Object-Oriented programming is much more similar to the way
the real world works; it is analogous to the human brain. Each
program is made up of many entities called objects.
Instead, a message must be sent requesting the data, just like
people must ask one another for information; we cannot see
inside each other’s heads.

Featuers of OOP
Ability to simulate real-world event much more effectively
Code is reusable thus less code may have to be written
Data becomes active
Better able to create GUI (graphical user interface) applications
Programmers are able to produce faster, more accurate and better-
written applications

Fundamental concepts of OOP in Python
The four major principles of object orientation are:
Encapsulation
Data Abstraction
Inheritance
Polymorphism

What is an Object..?
 Objects are the basic run-time entities in an object-oriented
system.
They may represent a person, a place, a bank account, a table of
data or any item that the program must handle.
When a program is executed the objects interact by sending
messages to one another.
Objects have two components:
- Data (i.e., attributes)
- Behaviors (i.e., methods)

Object Attributes and Methods Example
Object Attributes Object Methods
Store the data for that object
Example (taxi):
Driver
OnDuty
NumPassengers
Location
Define the behaviors for the
object
Example (taxi):
- PickUp
- DropOff
- GoOnDuty
- GoOffDuty
- GetDriver
- SetDriver
- GetNumPassengers

What is a Class..?
A class is a special data type which defines how to build a certain
kind of object.
The class also stores some data items that are shared by all the
instances of this class
 Instances are objects that are created which follow the definition
given inside of the class
Python doesn’t use separate class interface definitions as in some
languages
You just define the class and then use it

Methods in Classes
Define a method in a class by including function definitions
within the scope of the class block
There must be a special first argument self in all of method
definitions which gets bound to the calling instance
There is usually a special method called __init__ in most
classes

A Simple Class def: Student
class student:
“““A class representing a student ”””
def __init__(self , n, a):
self.full_name = n
self.age = a
def get_age(self): #Method
return self.age
Define class:
Class name, begin with capital letter, by convention
object: class based on (Python built-in type)
Define a method
Like defining a function
Must have a special first parameter, self, which provides way
for a method to refer to object itself

Instantiating Objects with ‘__init__’
 __init__ is the default constructor
__init__ serves as a constructor for the class. Usually
does some initialization work
An __init__ method can take any number of
arguments
However, the first argument self in the definition of
__init__ is special

Self
The first argument of every method is a reference to the current
instance of the class
By convention, we name this argument self
In __init__, self refers to the object currently being created; so, in
other class methods, it refers to the instance whose method was
called
Similar to the keyword this in Java or C++
But Python uses self more often than Java uses this
You do not give a value for this parameter(self) when you call the
method, Python will provide it.
Continue…

…Continue
Although you must specify self explicitly when defining the
method, you don’t include it when calling the method.
Python passes it for you automatically
Defining a method: Calling a method:
(this code inside a class definition.)
def get_age(self, num): >>> x.get_age(23)
self.age = num

Deleting instances: No Need to “free”
 When you are done with an object, you don’t have to delete
or free it explicitly.
 Python has automatic garbage collection.
 Python will automatically detect when all of the references to
a piece of memory have gone out of scope. Automatically
frees that memory.
 Generally works well, few memory leaks
 There’s also no “destructor” method for classes

Syntax for accessing attributes and methods
>>> f = student(“Python”, 14)
>>> f.full_name # Access attribute
“Python”
>>> f.get_age() # Access a method
14

Encapsulation
Important advantage of OOP consists in the encapsulation
of data. We can say that object-oriented programming
relies heavily on encapsulation.
The terms encapsulation and abstraction (also data hiding)
are often used as synonyms. They are nearly synonymous,
i.e. abstraction is achieved though encapsulation.
Data hiding and encapsulation are the same concept, so it's
correct to use them as synonyms
Generally speaking encapsulation is the mechanism for
restricting the access to some of an objects's components,
this means, that the internal representation of an object
can't be seen from outside of the objects definition.

 Access to this data is typically only achieved through
special methods: Getters and Setters
By using solely get() and set() methods, we can make sure
that the internal data cannot be accidentally set into an
inconsistent or invalid state.
C++, Java, and C# rely on the public, private,
and protected keywords in order to implement variable
scoping and encapsulation
 It's nearly always possible to circumvent this protection
mechanism

Public, Protected and Private Data
 If an identifier doesn't start with an underscore character "_" it
can be accessed from outside, i.e. the value can be read and
changed
 Data can be protected by making members private or protected.
Instance variable names starting with two underscore characters
cannot be accessed from outside of the class.
 At least not directly, but they can be accessed through private
name mangling.
 That means, private data __A can be accessed by the following
name construct: instance_name._classname__A

 If an identifier is only preceded by one underscore character, it
is a protected member.
 Protected members can be accessed like public members from
outside of class
Example:
class Encapsulation(object):
def __init__(self, a, b, c):
self.public = a
self._protected = b
self.__private = c

The following interactive sessions shows the behavior of public,
protected and private members:
>>> x = Encapsulation(11,13,17)
>>> x.public
11
>>> x._protected
13
>>> x._protected = 23
>>> x._protected
23
>>> x.__private
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'Encapsulation' object has no attribute '__private‘
>>>

The following table shows the different behavior Public,
Protected and Private Data
Name Notation Behavior
name Public Can be accessed from inside and
outside
_name Protected Like a public member, but they
shouldn't be directly accessed from
outside
__name Private Can't be seen and accessed from
outside

Inheritance
 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.
 Derived class inherits features from the base class, adding new features
to it.
 This results into re-usability of code.
Syntax:
class Baseclass(Object):
body_of_base_class
class DerivedClass(BaseClass):
body_of_derived_clas

While designing a inheritance concept, following key pointes keep it
in mind
A sub type never implements less functionality than the super type
Inheritance should never be more than two levels deep
We use inheritance when we want to avoid redundant code.

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.

Polymorphism
Polymorphism in Latin word which made up of ‘ploy’
means many and ‘morphs’ means forms
From the Greek , Polymorphism means many(poly)
shapes (morph)
 This is something similar to a word having several different
meanings depending on the context
 Generally speaking, polymorphism means that a method or
function is able to cope with different types of input.

A simple word ‘Cut’ can have different meaning
depending where it is used
Cut
Surgeon: The Surgeon
would begin to make an
incision
Hair Stylist: The Hair
Stylist would begin to cut
someone’s hair
Actor: The actor would
abruptly stop acting out the
current scene, awaiting
directional guidance
If any body says “Cut” to these people

In OOP , Polymorphism is the characteristic of being able to
assign a different meaning to a particular symbol or operator in
different contexts specifically to allow an entity such as a
variable, a function or an object to have more than one form.
There are two kinds of Polymorphism
Overloading :
Two or more methods with different signatures
Overriding:
Replacing an inherited method with another having the same
signature

Python operators work for built-in classes.
But same operator behaves differently with different types. For
example, the + operator will, perform arithmetic addition on
two numbers, merge two lists and concatenate two strings. This
feature in Python, that allows same operator to have different
meaning according to the context is called operator overloading
One final thing to mention about operator overloading is that
you can make your custom methods do whatever you want.
However, common practice is to follow the structure of the
built-in methods.
Operator Overloading

Explanation for Operator Overloading Sample Program
What actually happens is that, when you do p1 - p2, Python will
call p1.__sub__(p2) which in turn is Point.__sub__(p1,p2).
Similarly, we can overload other operators as well. The special
function that we need to implement is tabulated below.
Operator Expression Internally
Addition p1 + p2 p1.__add__(p2)
Subtraction p1 – p2 p1.__sub__(p2)
Multiplication p1 * p2 p1.__mul__(p2)
Power p1 ** p2 p1.__pow__(p2)
Division p1 / p2 p1.__truediv__(p2)

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