Introduction:

1. Presently the Python is considered as a more powerful language because it has provided a great tool and enriched library for data crunching and preparation. 

2. The use of super () in Python is mostly used to make the program more dynamic.

3.  It is the concept which is mostly used in Inheritance programming when we need to refer to multiple classes or parent classes without having to name them first.

Here, I am going to discuss about the Super () in Python regarding its use and implementation. Here we are also going to discuss the example and then we will explain the working approach of super () in details.

Introduction to Super Function:

1. As we have already discussed earlier that the super() in Python is mostly used to make the program more dynamic.

2.  When we are going to implement the concept of single inheritance programming then if we need to refer to multiple classes or parent classes without having to name them first then super() is get used.

3. Sometimes when we need to return a proxy object while using the delegates method calls to a parent or sister class of type then Super () is used. 

4. When we are going to implement the concept of overriding in a class for accessing the inherited methods then super () is going to be used.

Let us consider the following example which will let you know how to write a super() in Python. Mostly in Python 3 when we need to write a program using super() then it has to go through the following manner.

Example:

class MyParentClass():
def __init__(self):
pass 
class SubClass(MyParentClass):
def __init__(self):
super()

Here we are going to discuss the concept in more detailed way.

Making use of Super in your Programming:

As we have already discussed above that it is a technique in which we need to return a proxy object while using the delegates method calls to a parent or sister class. Also when we are going to implement the concept of single inheritance programming then if we need to refer to multiple classes or parent classes without having to name them first.

It should be noted that If you are using Python version 3.0 and above, the method for using super function is as follows.

super().methoName(args)

If you are using an earlier build of Python, the syntax for super function will be,

super(subClass, instance).method(args)

Let us consider the following example which will let you know how the use of super()  will take place in a program.

Example:

When we are going to use the super() in inline approach then the technique for implementation will be as follows.

class MyParentClass(object):
def __init__(self):
pass
 
class SubClass(MyParentClass):
def __init__(self):
MyParentClass.__init__(self)

But on the other hand if we are going to use earlier version of Python like Python 2 then the implementation will be like as below.

class SubClass(MyParentClass):
def __init__(self):
super(SubClass, self).__init__()

Let us consider the following program which will let you know the use of super(). Here in the following program the we are having a class called Square and an another class called Cube which is going to inherits the class Square. The code is as showed below.

Program:

class Square: 
     def __init__(self, side): 
         self.side = side 
  
     def area(self): 
         return self.side * self.side 
  
class Cube(Square): 
      def area(self): 
         face_area = self.side * self.side 
         return face_area * 6
  
     def volume(self): 
         face_area = self.side * self.side 
         return face_area * self.side 

Note:

Here in the above program it should be get noted that the  Cube class does not have an __init__() method. So the __init__() of Square class will be used for initialization of Cube instances. It is the basic property of inheritance mechanism which we are going to implement here.

As we have already discussed above that super() is basically used to returns a proxy object of the parent class so, when we are going to call the method  area() of Square class using super() as, super().area(). Then it is usually going to be accomplished as a modified definition of the class Cube.

class Cube(Square): 
     def area(self): 
         return super().area() * 6
  
     def volume(self): 
         return super().area() * self.side() 

Uses of Super Function in Python:

1. The super function in Python is proved to be extremely useful for forwarding compatibility. 

2. It enables the concept of code reusability what Inheritance concept is used to provide.

3. If we are going to use correctly then it diminishes the requirement of declaring the characteristics of all the classes.

4. If we are going to use the super() then it must be present within your Python library.

5. Because, during the execution, both the callee as well as caller functions must have the same signature as well as address otherwise it will give you the error.

6. If we need to use a super function, then we need to call it by using the super() keyword.

7. If we are going to use a zero argument form of super() then it can be done when we can only be used inside a class definition.

8. As it is used to support the concept of auto-filled by the compiler so if we use super() inside a class, say X, super() will be converted into super(X, self) by the compiler.

Scope @ NareshIT:

1. At Naresh IT you will get a good Experienced faculty who will guide you, mentor you and nurture you to achieve your dream goal.

2. Here you will get a good hand on practice in terms of practical industry-oriented environment which will definitely help you a lot to shape your future.

3. During the designing process of application, we will let you know about the other aspect of the application too. 

4. Our Expert trainer will let you know about every in’s and out’s about the problem scenario.

Achieving your dream goal is our motto. Our excellent team is working restlessly for our students to click their target. So, believe on us and our advice, and we assured you about your sure success.

Introduction:

1. Presently the Python is considered as a more powerful language that provides a great tool for data crunching and preparation. 

2. The Merge sort is the most common techniques which is being used for arranging the elements in either increasing or decreasing order. It uses the concept of Divide and Conquer technique.

3. When we are going to implement the concept of Merge Sort using Python then it is very easy and more effective.

4. As we know that the Python is basically used to have numerous enriched functionable libraries which may be get used to parse the data which is being written in other languages. 

Here, I am going to discuss the Python Merge sort concepts, which will let you know how to use these concepts in programming.

What is Merge Sort in Python?

1. The Merge sort is the most common techniques which is being used for arranging the elements in either increasing or decreasing order. 

2. The Merge sort uses the concept of Divide and Conquer technique which is very much effective techniques for Parallel Processing environment. 

3. In this technique the list elements to be get sorted, are used to implement the concept of Divide and Conquer technique. 

4. In Merge Sort technique as it is based on the divide and conquer algorithm, so we need to divide the list first.

5. Here the list is divided into two halves, then sorted separately and merged back to reach the solution. 

6. We are basically using the function merge () for merging the sorted arrays at the last.

Let us consider the following example which will let you know how to write a loop in Python. Mostly in Python 3 when we need to write a loop mechanism then it has to go through the following manner.

The Divide and Conquer approach:

As we have already discussed above that it is a technique in which the list/array is divided 

into two equal half and then we are going to apply the conquer technique to find the final sorted list. The basic mechanism is as mentioned below.

1. Here at the first, we need to split the array into two half.

2. After splitting the array, we need to repeat this process into each half until each half is of size 1 or 0. 

3. The array of size 1 is trivially sorted.

4. Now the two sorted arrays are combined into one big array. 

5. The same process is allowed to be continued until all the elements are combined and the array is sorted. 

Let us consider the following example which will let you know how the merge sort process will take place.

Example:

Let the list is {38, 27, 43, 3, 9, 82, 10}

1. At the first the list is get divided as {38, 27, 43, 3} and {9, 82, 10}.

2. After this the list is divided as {38, 27},{43, 3} and { 9, 82},{ 10}.

3. After this the list is divided as {38},{27},{ 43}, {3} and { 9},{ 82},{ 10}.

4. Since at this stage the size becomes 1 now so, the merge processes is now come into action. 

5. Here we need to start merging of each individual arrays back till the complete array is merged.

6. So in the first pass the merging is done between {38},{27},{ 43}, {3} and { 9},{ 82}.

7. We get the final array after first pass as {27,38},{3,43} and { 9,82}.

8. At 2nd pass the merged array will be {3,27,38,43} and {9,10,82}.

9. At 3rd pass the final sorted array will be {3,9,10,27,38,43,82}.

Implementing Merge Sort in Python:

If we need to get implement the concept of Merge sort in Python 3 then we need to write the following code as mentioned below. Here I am trying to explain the process in simplest way so that you can understand the concept easily.

Program:

def mergeSort(arr):
  if len(arr) > 1:
 
        mid = len(arr)//2       	   # Finding the mid element of the array

        L = arr[:mid]        	 # Dividing the array elements into two halves
        R = arr[mid:]
        mergeSort(L) 		# Sorting the first half
        mergeSort(R) 		# Sorting the second half
        i = j = k = 0
        while i < len(L) and j < len(R):   	# Copy data to temp arrays L[] and R[]
            if L[i] < R[j]:
                arr[k] = L[i]
                i += 1
            else:
                arr[k] = R[j]
                j += 1
            k += 1
        while i < len(L):			# Checking if any element was left
           arr[k] = L[i]
            i += 1
            k += 1
        while j < len(R):
            arr[k] = R[j]
            j += 1
            k += 1
def printList(arr): 			# Code to print the list
   for i in range(len(arr)):
        print(arr[i], end=" ")
    print()
***********
if __name__ == '__main__':  		 # Driver Code

    arr = [12, 11, 13, 5, 6, 7]
    print("Given array is", end="\n")
printList(arr)
    mergeSort(arr)
    print("Sorted array is: ", end="\n")
    printList(arr)

Flowchart for implementation of Merge Sort:

In order to implement the concept of Merge sort we can use the following flow chart as mentioned below.

Flow Chart to implement the Merge Sort.

Advantages and Usage:

Form the above discussion now it is getting clear that it is the technique which is good to implement for sorting the list of elements but to make it better understand in practical way we need to remember the following.

1. The Merge sort is used to access a random element in linear time, but not regular constant time like other algorithms. 

2. It is very much easy and fast process but requires more memory spaces.

3. One of the best features of merge sort is its low number of compares. 

4. For comparisons it takes O(n * log(n)).

5. Since it uses the divide-and-conquer approach, so it is more convenient and reliable for parallel processing-based programs. 

Scope @ NareshIT:

1. At Naresh IT you will get a good Experienced faculty who will guide you, mentor you and nurture you to achieve your dream goal.

2. Here you will get a good hand on practice in terms of practical industry-oriented environment which will definitely help you a lot to shape your future.

3. During the designing process of application, we will let you know about the other aspect of the application too. 

4. Our Expert trainer will let you know about every in’s and out’s about the problem scenario.

Achieving your dream goal is our motto. Our excellent team is working restlessly for our students to click their target. So, believe on us and our advice, and we assured you about your sure success. 

Introduction:

1. As we know that the Python is more powerful language which offer great tools for data crunching and preparation, as well as for complex scientific data analysis and modelling. 

2. In most of the cases we often require parsing the data which is being written in different languages like C, C++ and Java.

3. Here the Python is used to provides us a numerous enriched functionable libraries which may be get used to parse the data which is being written in other languages. 

4. Here I am going to discuss the Python loop concept, which will let you know to learn how to use the loop concept in Python.

5. Python has multiple loop concepts such as for loop, while loop and infinite loop mechanism.

6. Most of the Python programming can be done using these loop mechanisms and they are more relevant in practical sense also.

7. Here as stated earlier above, I am going to discuss the Python loop concepts, which will let you know how to use these concepts in programming.

What is Python for Loop?

1. The loop in Python is basically used when we need to iterate a set of instruction repeatedly depending on the specified condition. 

2. It is having almost similar syntax like other programming concept in its appearance when we are going to make the code.

3. It has a simple structural approach so that it can be easily understood by the programmer.

4. It is mostly used to implements the various concept of programming when in Python we are going to implement the LIST, TUPLE and DICTIONARY concept.

5. The loop concept in Python is used to iterate over a sequence (list, tuple, string) or other iterables objects.

6. Iterating over a sequence is called traversal.

7. Loop continues until we reach the last item in the sequence.

8. The body of for loop is separated from the rest of the code using indentation.

Let us consider the following example which will let you know how to write a loop  in Python. Mostly in Python 3 when we need to write an loop mechanism then it has to go through the following manner.

Python for Loop Syntax:

for val in sequence:

Let us understand the for-loop syntax with an example when we are going to create the list as below:

a=[10,20,30,40,50] // creation of list

for i in a: //applying the loop concept

print(i) 

When we are going to print the output will be 10,20,30,40,50.

In the above example, the execution started from the first item in the list, and it went on until the execution reached 5. It is a very simple example of how we can use a for loop in python. 

Similarly, when we are going to apply the range in for loop then we can access the index of the list. Let us consider another example to know how range function can be used with for loop.

Range in Python for Loop

1. As you know that in python, the range is an Built-in function. 

2. It is basically used to returns a sequence when it is used along with the List or Tuple application. 

3. When we are going to apply the range function then it has three parameters which we can define at the time of use. These parameters are,

• Starting parameter value, 

• Ending parameter value and 

• Step parameter value. 

Syntax:

for i in range (Starting parameter value, Ending parameter value, Step parameter value)

let us understand this with an example as discussed below.

a=[10,20,30,40,50] // creation of list

for i in range(0,len(a),1): //applying the loop concept

print(i) 

When we are going to print the output will be used to access the index value such as 0,1,2,3,4.

But if we need to access the value of the list using the range then the same program will be written as 

a=[10,20,30,40,50] // creation of list

for i in range(0,len(a),1): //applying the loop concept

print(a[i]) 

When we are going to print the output will be used to access the index value such as 10,20,30,40,50.

In the above example, the sequence starts from 0 and ends at 5 because the ending parameter is 5 and the step is 1, therefore the while execution it jumps 1 step after each item.

Python While Loop:

1. Like similar to the for loop the Python also support the concept of While loop mechanism. 

2. The while loop in Python is used to iterate over a block of code as long as the test expression (condition) is true.

3. When the condition is tested and the result is false, the loop body will be skipped and the first statement after the while loop will be executed.

Syntax:

while (condition): 

 body of while 

let us consider the following example to implement the concept of while loop. 

a=[1,2,3,4,5] 

i=0 

sum=0 

while i<len(a): 

sum=sum+a[i] 

 i=i+1 

print(sum) 

When we are going to print the output then it will print 15.

Infinite Loop:

It is another approach in Python where if we need to execute statement repeatedly then it is used. A loop becomes infinite loop if the condition given never becomes false. It keeps on running. Such loops are called infinite loop. In python if we need to implement such concept then it can be done as follows.

Let us consider the following example.

a=1 

while (a==1): 

n=int(input("enter the number")) 

print("you entered:" , n) 

When this program will run then the output will be get appeared as 

Enter the number 10 

you entered:10 

Enter the number 12 

you entered:12 

Enter the number 16 

you entered:16 

Break in Loop:

1. The Break in python is a control flow statement. 

2. It is used to exit the execution as soon as the break is encountered. 

3. Let us understand how we can use a break statement in a for loop using an example.

In the above example, as soon as the loop encounters the string “R” it enters the if statement block where the break statement exits the loop. Similarly, we can use the break statement according to the problem statements.

Example:

company = [‘N’,’A’,’R’,’E’,’S’,’H’,’I’,’T’]
 
for x in company:
    if x == "R":
        break
    print(x)

When the above program will run then, as soon as the loop encounters the string “R” it enters the if statement block where the break statement exits the loop. So, the output of the program will be NA.

Continue in Python for Loop:

Like similar as that of break statement, the continue can also be used. It should be get noted that we will use the continue statement when we need to skip some statement based on specified condition. Like break statement It is also a control statement, but it will only skip the current iteration and execute the rest of the iterations anyway.

Let us consider the same example as stated above as

company = [‘N’,’A’,’R’,’E’,’S’,’H’,’I’,’T’]
 for x in company:
    if x == "R":
        continue
    print(x)

When the above program will run then, as soon as the loop encounters the string “R” it enters the if statement block where the continue statement skip the line and rest will execute as it is. So, the output of the program will be NAESHIT.

Scope @ NareshIT:

1. At Naresh IT you will get a good Experienced faculty who will guide you, mentor you and nurture you to achieve your dream goal.

2. Here you will get a good hand on practice in terms of practical industry-oriented environment which will definitely help you a lot to shape your future.

3. During the designing process of application, we will let you know about the other aspect of the application too. 

4. Our Expert trainer will let you know about every in’s and out’s about the problem scenario.

Achieving your dream goal is our motto. Our excellent team is working restlessly for our students to click their target. So, believe on us and our advice, and we assured you about your sure success.