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Object Oriented Programming in Python



Hello dear readers! welcome back to another section of our tutorial on Python. In this tutorial post, we will be studying about the Object Oriented Programming (OOP) in Python.

Python Programming has been an object oriented language since it existed. Because of this, creating and using classes and objects are very easy.

If you do not have any previous experience with object oriented programming, then you may want to consult an introductory course on it so that you have an idea of the basic concepts.

However, here is a small overview of Object-Oriented Programming that i have put together to make it easier for you to catch up faster -


An Overview of OOP Technology

  • Class - This is a user-defined prototype for an object that defines a set of attributes that distinguish any object of the class. The attributes are data members and methods accessed via dot notation.
  • Class variable - This is a variable that is shared by all instances of a class. Class variables are defined within a class but outside any of the class's methods. The class variables are not used as frequently as the instance variables.
  • Instance variable - This is a variable that is defined inside a method and belongs only to the current instance of a class.
  • Data member - This is a class variable or an instance variable that holds a data that is associated with a class and it's objects.
  • Function overloading - This is an assignment of more than 1 behavior to a certain function. The work carried out varies by the types of objects or the arguments involved.
  • Inheritance - It is the transfer of the characteristics of a class to other classes that are derived from it.
  • Instance - It is an individual object of a certain class. An obj that belongs to a class Circle, for example, is an instance of the class Circle.
  • Instantiation - This is the creation of an instance of a class.
  • Method - A special kind of function that is defined in a class definition.
  • Object - A unique instance of a data structure defined by its class. An object is made up of both data members (class variables & instance variables) and methods.
  • Operator overloading - This is the assignment of more than 1 function to a certain operator.



Creating Classes

The Python class statement creates a new class definition. The name of the class immediately follows the keyword class followed by a colon as follows -

class ClassName:
   'Optional class documentation string'
   class_suite

  • Class has a documentation string, that can be accessed via ClassName._doc_.
  • The class_suite consists of all component statements defining the class members, functions & data attributes.

Example

Following is an example of a simple Python class -

class Employee:
   'Common base class for all employees'
   empCount = 0

   def __init__(self, name, salary):
      self.name = name
      self.salary = salary
      Employee.empCount += 1
   
   def displayCount(self):
     print "Total Employee %d" % Employee.empCount

   def displayEmployee(self):
      print "Name : ", self.name,  ", Salary: ", self.salary

  • The variable empCount is a class whose value is shared among all instances of this class. This can be accessed as Employee.empCount from inside the class or outside the class.
  • The first method __init__ is a special method, which is called initialization method that Python calls when you create a new instance of this class.
  • From the above code, you declare other class methods like normal functions with the exception that the first argument to each method is self. Python adds the slef argument to the list for you; you do not need to include it when you call the methods.


Creating Instance Objects

To create instances of a class, you call the class using class name and pass in whatever arguments that it's __init__ method accepts.

"This would create first object of Employee class"
emp1 = Employee("Kennedy", 8000)
"This would create second object of Employee class"
emp2 = Employee("David", 6000)


Accessing Attributes

You access the object's attributes by making use of the dot operator with Object. Class variable would be accessed by using the class name as follows -

emp1.displayEmployee()
emp2.displayEmployee()
print "Total Employee %d" % Employee.empCount

Now, putting all the ideas together -

#!/usr/bin/python

class Employee:
   'Common base class for all employees'
   empCount = 0

   def __init__(self, name, salary):
      self.name = name
      self.salary = salary
      Employee.empCount += 1
   
   def displayCount(self):
     print "Total Employee %d" % Employee.empCount

   def displayEmployee(self):
      print "Name : ", self.name,  ", Salary: ", self.salary

"This would create first object of Employee class"
emp1 = Employee("Kennedy", 8000)
"This would create second object of Employee class"
emp2 = Employee("David", 6000)
emp1.displayEmployee()
emp2.displayEmployee()
print "Total Employee %d" % Employee.empCount

Output

When the above code is executed, it will produce the following result -

Name :  Kennedy ,Salary:  8000
Name :  David ,Salary:  6000
Total Employee 2

You can add, remove, or modify attributes of classes and objects at any time -

emp1.age = 12  # Add an 'age' attribute.
emp1.age = 13  # Modify 'age' attribute.
del emp1.age  # Delete 'age' attribute.

Rather than using the normal statements to access attributes, you can make use of the following functions -

  • The getattr(obj, name[, default]) - to access the attribute of objects.
  • The hasattr(obj, name) - to check if an attribute exists or not.
  • The setattr(obj, name, value) - to set an attribute. If the attribute does not exist, then it would be created.
  • The delattt(obj, name) - to delete an attribute.

# Returns true if 'age' attribute exists
getattr(emp1, 'age')    # Returns value of 'age' attribute
setattr(emp1, 'age', 12) # Set attribute 'age' at 12
delattr(empl, 'age')    # Delete attribute 'age'


Built-in Class Attributes

Every Python class keeps the following built-in attributes and you can have access to them by making use of dot operator like any other attribute -

  • __dict__ - This is the dictionary containing the class's namespace.
  • __doc__ - This is the class documentation string or none, if undefined.
  • __name__ - Class name.
  • __module__ - Module name in which the class is defined. This attribute is "__main__" in interactive mode.
  • __bases__ - A possibly empty tuple containing the base classes, in the order of their occurrence in the base class list.

Example

For the above class, let us now try to access all these attributes -

#!/usr/bin/python

class Employee:
   'Common base class for all employees'
   empCount = 0

   def __init__(self, name, salary):
      self.name = name
      self.salary = salary
      Employee.empCount += 1
   
   def displayCount(self):
     print "Total Employee %d" % Employee.empCount

   def displayEmployee(self):
      print "Name : ", self.name,  ", Salary: ", self.salary

print "Employee.__doc__:", Employee.__doc__
print "Employee.__name__:", Employee.__name__
print "Employee.__module__:", Employee.__module__
print "Employee.__bases__:", Employee.__bases__
print "Employee.__dict__:", Employee.__dict__

Output

When the above code is executed, it will produce the following result -

Employee.__doc__: Common base class for all employees
Employee.__name__: Employee
Employee.__module__: __main__
Employee.__bases__: ()
Employee.__dict__: {'__module__': '__main__', 'displayCount':
<function displayCount at 0xb7c84994>, 'empCount': 2, 
'displayEmployee': <function displayEmployee at 0xb7c8441c>, 
'__doc__': 'Common base class for all employees', 
'__init__': <function __init__ at 0xb7c846bc>}


Destroying Objects

Python deletes all the unwanted objects automatically to free the memory space. The process by which Python occasionally claims back blocks of memory that are no longer in use is termed Garbage Collection.

The Python's garbage collector runs during execution of the program and is set off when an object's reference count reaches zero. You should take note that an object's reference count changes as the number of aliases that point to it also changes.

An object's reference count rises when it is assigned a new name or placed in a container (list, tuple, or dictionary). But it decreases when it is deleted with del, its reference is now reassigned or goes out of scope. When an object's reference count reaches zero, then Python collects it automatically.

a = 40      # Create object <40>
b = a       # Increase ref. count  of <40> 
c = [b]     # Increase ref. count  of <40> 

del a       # Decrease ref. count  of <40>
b = 100     # Decrease ref. count  of <40> 
c[0] = -1   # Decrease ref. count  of <40>

You normally will not observe when the garbage collector pulls down an orphaned instance & then reclaims its space. But a class can implement the special method __del__() callled a destructor, that is invoked when the instance is about to be pulled down. This method might be used to clean up any non memory resources used by an instance.

Example

The __del__() destructor in the below example prints the class name of an instance that is at the point of being destroyed -

#!/usr/bin/python

class Point:
   def __init__( self, x=0, y=0):
      self.x = x
      self.y = y
   def __del__(self):
      class_name = self.__class__.__name__
      print class_name, "destroyed"

pt1 = Point()
pt2 = pt1
pt3 = pt1
print id(pt1), id(pt2), id(pt3) # prints the ids of the obejcts
del pt1
del pt2
del pt3

Output

When the above code is executed, it will produce the following result -

3083401324 3083401324 3083401324
Point destroyed


Note - Ideally, you should define your classes in separate files, then import them to your main program file using the import statement.


Class Inheritance
Instead of starting from scratch, you can create a class by deriving it from a preexisting class by listing out the parent class in parentheses after the new class name.

The Python child class inherits the attributes of it's parent class, and you can use those attributes as though they were defined in the child class. A child class can also override the data members, as well as methods from the parents.

Syntax
Derived classes are declared much like their parent class; however a list of base classes to inherit from is given after the class name -

class SubClassName (ParentClass1[, ParentClass2, ...]):
   'Optional class documentation string'
   class_suite

Example
#!/usr/bin/python

class Parent:        # define parent class
   parentAttr = 100
   def __init__(self):
      print "Calling parent constructor"

   def parentMethod(self):
      print 'Calling parent method'

   def setAttr(self, attr):
      Parent.parentAttr = attr

   def getAttr(self):
      print "Parent attribute :", Parent.parentAttr

class Child(Parent): # define child class
   def __init__(self):
      print "Calling child constructor"

   def childMethod(self):
      print 'Calling child method'

c = Child()          # instance of child
c.childMethod()      # child calls its method
c.parentMethod()     # calls parent's method
c.setAttr(200)       # again call parent's method
c.getAttr()          # again call parent's method

Output
When the above code is executed, it will produce the following result -

Calling child constructor
Calling child method
Calling parent method
Parent attribute : 200

Similar way, you can drive a class from multiple parent classes as follows -

class A:        # define your class A
.....

class B:         # define your class B
.....

class C(A, B):   # subclass of A and B
.....

You can make use of issubclass() or isinatance() functions to check a relationship of two classes and also instances.

  • The issubclass(sub, sup) boolean function returns true if the given sub class sub is indeed a subclass of the superclass sup.
  • The isinatance(obj, classes) boolean function returns true if the obj is an instance of class Class or instance of a subclass of Class.


Overriding Methods
You can always override your parent class methods. A reason to override a parent's methods is because you may want a special functionality in your subclass.

Example
#!/usr/bin/python

class Parent:        # define parent class
   def myMethod(self):
      print 'Calling parent method'

class Child(Parent): # define child class
   def myMethod(self):
      print 'Calling child method'

c = Child()          # instance of child
c.myMethod()         # child calls overridden method

Output
When the above code is executed, it will produce the following result -

Calling child method

Base Overloading Methods
The following table lists some generic functionality that you can override in your own classes -

Sr.No.Method, Description & Sample Call
1
__init__ ( self [,args...] )
Constructor (with any optional arguments)
Sample Call : obj = className(args)
2
__del__( self )
Destructor, deletes an object
Sample Call : del obj
3
__repr__( self )
Evaluable string representation
Sample Call : repr(obj)
4
__str__( self )
Printable string representation
Sample Call : str(obj)
5
__cmp__ ( self, x )
Object comparison
Sample Call : cmp(obj, x)


Overloading Operators
Let us assume you have created a Vector class in representing a two-dimensional vectors, what then happens when you use the plus operator to add them? Most likely Python will shout at you.

Nevertheless, you could define the __add__ method in your class for the purpose of executing vector addition and the plus operator would behave as expected -

#!/usr/bin/python

class Vector:
   def __init__(self, a, b):
      self.a = a
      self.b = b

   def __str__(self):
      return 'Vector (%d, %d)' % (self.a, self.b)
   
   def __add__(self,other):
      return Vector(self.a + other.a, self.b + other.b)

v1 = Vector(2,10)
v2 = Vector(5,-2)
print v1 + v2

Output
When the above code is executed, it will produce the following result -

Vector(7,8)


Data Hiding
An object's attributes may be visible or not outside of the class definition. The attributes needs to be named using the double under score prefix, and those attributes are not to be directly visible to outsiders.

Example
#!/usr/bin/python

class JustCounter:
   __secretCount = 0
  
   def count(self):
      self.__secretCount += 1
      print self.__secretCount

counter = JustCounter()
counter.count()
counter.count()
print counter.__secretCount

Output
When the above code is executed, it will produce the following result -

1
2
Traceback (most recent call last):
   File "test.py", line 12, in <module>
      print counter.__secretCount
AttributeError: JustCounter instance has no attribute '__secretCount'

Python protects those members by internally changing the name to include the class name. You can access such object's attributes as object._className__attrName. So if you would replace your last line as following, then it works for you -


.........................
print counter._JustCounter__secretCount

Output
When the above code is executed, it will produce the following result -

1
2
2


Alright guys! This is where we are rounding up for this tutorial post. In our next tutorial, we are going to be discussing about the Python Regular Expressions.

Feel free to ask your questions where necessary and i will attend to them as soon as possible. If this tutorial was helpful to you, you can use the share button to share this tutorial.

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Thanks for reading and bye for now.

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