Python Object-oriented programming

In this part of the Python programming tutorial, we will talk about object oriented programming in Python.
There are three widely used programming paradigms there. Procedural programming, functional programming and object-oriented programming. Python supports both procedural and object-oriented programming. There is some limited support for f unctional programming too.
Object-oriented programming (OOP) is a programming paradigm that uses objects and their interactions to design applications and computer programs. (Wikipedia)
There are some basic programming concepts in OOP:

• Abstraction
• Polymorphism
• Encapsulation
• Inheritance

The abstraction is simplifying complex reality by modelling classes appropriate to the problem. The polymorphism is the process of using an operator or function in different ways for different data input. The encapsulation hides the implementation details of a class from other objects. The inheritance is a way to form new classes using classes that have already been defined.

Objects

Everything in Python is an object. Objects are basic building blocks of a Python OOP program.

#!/usr/bin/python

# objects.py

import sys


def function(): pass


print type(1)
print type("")
print type([])
print type({})
print type(())
print type(object)
print type(function)
print type(sys)

In this example we show, that all these entities are in fact objects. The type() function returns the type of the object specified.

$ ./objects.py 
<type 'int'>
<type 'str'>
<type 'list'>
<type 'dict'>
<type 'tuple'>
<type 'type'>
<type 'function'>
<type 'module'>

The class keyword

The previous objects were all built-in objects of the Python programming language. The user defined objects are created using the class keyword. The class is a blueprint that defines a nature of a future object. From classes we construct instances. An instance is a specific object created from a particular class. For example, Huck might be an instance of a Dog class.

#!/usr/bin/python

# first.py

class First:
   pass

fr = First()

print type(fr)
print type(First)

This is our first class. The body of the class is left empty for now. It is a convention to give classes a name that starts with a capital letter.

fr = First()

Here we create a new instance of the First class. Or in other words, we instantiate the First class. The fr is a reference to our new object.

$ ./first.py 
<type 'instance'>
<type 'classobj'>

Here we see that fr is an instance object and First is a class object.
Inside a class, we can define attributes and methods. An attribute is a characteristic of an object. This can be for example a salary of an employee. A method defines operations that we can perform with our objects. A method might define a cancellation of an account. Technically, attributes are variables and methods are functions defined inside a class.

Attributes

Attributes are characteristics of an object. A special method called __init__() is used to initialize the attributes of an object.

#!/usr/bin/python

# initialize.py


class Cat:
   def __init__(self, name):
      self.name = name


missy = Cat('Missy')
lucky = Cat('Lucky')

print missy.name
print lucky.name

In this code example, we have a Cat class. The special method __init__() is called automatically right after the object has been created.

 def __init__(self, name):

Each method in a class definition begins with a reference to the instance object. It is by convention named self. There is nothing special about the self name. We could name it this, for example. The name is the argument. The value is passed during the class instantiation.

 self.name = name

Here we pass an attribute to an instance object.

 missy = Cat('Missy')
 lucky = Cat('Lucky')

Here we instantiate two objects. Missy and Lucky cats. The number of arguments must correspond to the __init__() method of the class definition. The 'Missy' and 'Lucky' strings become the name parameter of the __init__() method.

 print missy.name
 print lucky.name

Here we print the instance variables of two cat objects. Each instance of a class can have their own attributes.

$ ./initialize.py 
Missy
Lucky

The attributes can be assigned dynamically, not just during initialization. This shows the next example.

#!/usr/bin/python

# dynamic.py

class Dynamic:
   pass


d = Dynamic()
d.name = "Dynamic"
print d.name

We define and create an empty Dynamic class.

 d.name = "Dynamic"

This line of code creates a new name attribute.

$ ./dynamic.py 
Dynamic

So far, we have been talking about the instance attributes. In Python there are also so called class object attributes. Class object attributes are same for all instances of a class.

#!/usr/bin/python

# cat.py


class Cat:
   species = 'mammal'

   def __init__(self, name, age):
      self.name = name
      self.age = age


missy = Cat('Missy', 3)
lucky = Cat('Lucky', 5)

print missy.name, missy.age
print lucky.name, lucky.age

print Cat.species
print missy.__class__.species
print lucky.__class__.species

In our example, we have two cats with specific name and age attributes. Both cats share some characteristics. Missy and Lucky are both mammals. This is reflected in a class level attribute species. The attribute is defined outside any method name in the body of a class.

 print Cat.species
 print missy.__class__.species

There are two ways, how we can access the class object attributes. Either via the name of the Cat class, or with the help of a special __class__ attribute.

$ ./cat.py 
Missy 3
Lucky 5
mammal
mammal
mammal

Methods

Methods are functions defined inside the body of a class. They are used to perform operations with the attributes of our objects. Methods are essential in encapsulation concept of the OOP paradigm. For example, we might have a connect() method in our AccessDatabase class. We need not to be informed, how exactly the method connect connects to the database. We only know, that it is used to connect to a database. This is essential in dividing responsibilities in programming. Especially in large applications.

#!/usr/bin/python

# circle.py


class Circle:
   pi = 3.141592

   def __init__(self, radius=1):
      self.radius = radius 

   def area(self):
      return self.radius * self.radius * Circle.pi

   def setRadius(self, radius):
      self.radius = radius

   def getRadius(self):
      return self.radius


c = Circle()

c.setRadius(5)
print c.getRadius()
print c.area()

In the code example, we have a Circle class. We define three new methods.

 def area(self):
    return self.radius * self.radius * Circle.pi

The area() method returns the area of a circle.

 def setRadius(self, radius):
    self.radius = radius

The setRadius() method sets a new value for a radius attribute.

 def getRadius(self):
    return self.radius

The getRadius() method returns the current radius.

 c.setRadius(5)

The method is called on an instance object. The c object is paired with the self parameter of the class definition. The number 5 is paired with the radius parameter.

$ ./circle.py 
5
78.5398

In Python, we can call methods in two ways. There are bounded and unbounded method calls.

#!/usr/bin/python

# methods.py

class Methods:
   def __init__(self):
      self.name = 'Methods'

   def getName(self):
      return self.name


m = Methods()

print m.getName()
print Methods.getName(m)

In this example, we demostrate both method calls.

 print m.getName()

This is the bounded method call. The Python interpreter automatically pairs the m instance with the self parameter.

 print Methods.getName(m)

And this is the unbounded method call. The instance object is explicitly given to the getName() method.

$ ./methods.py 
Methods
Methods

Inheritance

The inheritance is a way to form new classes using classes that have already been defined. The newly formed classes are called derivedclasses, the classes that we derive from are called base classes. Important benefits of inheritance are code reuse and reduction of complexity of a program. The derived classes (descendants) override or extend the functionality of base classes (ancestors).

#!/usr/bin/python

# inherit.py


class Animal:
   def __init__(self):
      print "Animal created"

   def whoAmI(self):
      print "Animal"

   def eat(self):
      print "Eating"


class Dog(Animal):
   def __init__(self):
      Animal.__init__(self)
      print "Dog created"

   def whoAmI(self):
      print "Dog"

   def bark(self):
      print "Woof!"


d = Dog()
d.whoAmI()
d.eat()
d.bark()

In this example, we have two classes. Animal and Dog. The animal is the base class, the Dog is the derived class. The derived class inherits the functionality of the base class. It is shown by the eat() method. The derived class modifies existing behaviour of the base class, shown by the whoAmI() method. Finally, the derived class extends the functionality of the base class, by defining a new bark() method.

 class Dog(Animal):
    def __init__(self):
       Animal.__init__(self)
       print "Dog created"

We put the ancestor classes in round brackets after the name of the descendant class. If the derived class provides it's own __init__() method, it must explicitly call the base class __init__() method.

$ ./inherit.py 
Animal created
Dog created
Dog
Eating
Woof!

Polymorphism

The polymorphism is the process of using an operator or function in different ways for different data input. In practical terms, polymorphism means that if class B inherits from class A, it doesn’t have to inherit everything about class A; it can do some of the things that class A does differently. (wikipedia)

#!/usr/bin/python

# basic.py


a = "alfa"
b = (1, 2, 3, 4)
c = ['o', 'm', 'e', 'g', 'a']

print a[2]
print b[1]
print c[3]

Python programming language uses polymorphism extensively in built-in types. Here we use the same indexing operator for three different data types.

$ ./basic.py 
f
2
g

Polymorphism is most commonly used when dealing with inheritance.

#!/usr/bin/python

# polymorphism.py


class Animal:
   def __init__(self, name=''):
      self.name = name

   def talk(self):
      pass


class Cat(Animal):
   def talk(self):
      print "Meow!"


class Dog(Animal):
   def talk(self):
      print "Woof!"


a = Animal()
a.talk()

c = Cat("Missy")
c.talk()

d = Dog("Rocky")
d.talk()

Here we have two species. A dog and a cat. Both are animals. The Dog class and the Cat class inherit the Animal class. They have a talk() method, which gives different output for them.

$ ./polymorphism.py 
Meow!
Woof!

Special Methods

Classes in Python programming language can implement certain operations with special method names. These methods are not called directly, but by a specific language syntax. This is similar to what is known as operator overloading in C++ or Ruby.

#!/usr/bin/python

# book.py

class Book:
   def __init__(self, title, author, pages):
      print "A book is created"
      self.title = title
      self.author = author
      self.pages = pages

   def __str__(self):
      return "Title:%s , author:%s, pages:%s " % \
              (self.title, self.author, self.pages)

   def __len__(self):
      return self.pages

   def __del__(self):
      print "A book is destroyed"


book = Book("Inside Steve's Brain", "Leander Kahney", 304)

print book
print len(book)
del book

In our code example, we have a book class. Here we introduce four special methods. The __init__(), __str__(), __len__() and the __del__() methods.

book = Book("Inside Steve's Brain", "Leander Kahney", 304)

Here we call the __init__() method. The method creates a new instance of a Book class.

print book

The print keyword calls the __str__() method. This method should return an informal string representation of an object.

print len(book)

The len() function invokes the __len__() method. In our case, we print the number of pages of our book.

del book

The del keyword deletes an object. It calls the __del__() method.
In the next example we implement a vector class and demonstrate addition and substraction operations on it.

#!/usr/bin/python

# vector.py


class Vector:

  def __init__(self, data):
    self.data = data

  def __str__(self):
    return repr(self.data)

  def __add__(self, other):
    data = []
    for j in range(len(self.data)):
      data.append(self.data[j] + other.data[j])
    return Vector(data)

  def __sub__(self, other):
    data = []
    for j in range(len(self.data)):
      data.append(self.data[j] - other.data[j])
    return Vector(data)


x = Vector([1, 2, 3])
y = Vector([3, 0, 2])
print x + y
print y - x

  def __add__(self, other):
    data = []
    for j in range(len(self.data)):
      data.append(self.data[j] + other.data[j])
    return Vector(data)

Here we implement the addition operation of vectors. The __add__() method is called, when we add two Vector objects with the + operator. Here we add each member of the respective vectors.

$ ./vector.py 
[4, 2, 5]
[2, -2, -1]

In this part of the Python tutorial, we have covered object-oriented programming in Python.