Are you working on any large dataset that should be sorted easily & quickly? Then, you have to use the algorithm โQuick Sort in Pythonโ. You might know about the Sorting Algorithms in Data Structure & Algorithm Topic where Quick Sort is a simple section.
This article is intended to focus on the Development of a Quick Sort Algorithm using Python programming language. But before we move ahead with our discussion on Quicksort in Python programming language, we should be aware of the basics of the Quicksort algorithm.
So, let us start our journey from the basics of the sorting algorithm present in computer science. Also, if you’re curious to know what the ways to implement Quick Sort are and needย help with Python homeworkย then this article is for you.
Summary or Key Highlights:ย
- Quick Sort Algorithm is one section of the Sorting Algorithm of Data Structure.
- In the Quick Sort, a Pivot Element is chosen from the set of data.
- Based upon the Pivot Element, the array is divided into two parts each time.
- In the end, all small part arrays got merged.
- The Time & Space Complexity of the Quick Sort Algorithm is the best.
- The Recursion Method is the key player of the Quick Sort Technique.
What Is Sorting Algorithm & Its Different Types? Get To Know
ย In computer science, there is a special section present on the Data Structure topic. The section is known as the Sorting Algorithm section. Though, this section belongs in the intermediate position between the Data Structure & Algorithm.
There are likely nine different sorting algorithms present. Now, as a developer, you should choose a particular algorithm to solve any problem.
Different sorting algorithm takes different times to solve different problems. So, picking up the most appropriate sorting algorithm will be a difficult task for the developer. So, you should solve more & more problems to come out of the situation.
There are many algorithms. They all have different strategies to sort the giving sequence. Like there are Bubble sort algorithms, Heap sort algorithms, etc.
What Is Quicksort In Python Programming Language? Read Below
The Quicksort algorithm is a special sorting algorithm present in computer science. The Quicksort algorithm was first discovered in 1959. The name โQuick Sortโ comes from its speed to sort any number of elements provided as an array in the problem.
The Quicksort algorithm depends upon the strategy of Divide & Conquer. That means a large set of data will be first divided into some small pieces. Now, those small pieces will be evaluated & at the end, they will be again combined to get the full result.
Following the same manner, the Quicksort algorithm first divides a set of elements into two pieces. Now, those two pieces will again be divided into two small pieces. In this way, when the pieces become very small they are calculated.
In the end, all those results are merged & the final result is produced. The element by which the basis of the division of the element set happens is known as the Pivot element in the Quicksort algorithm.
What Are The Steps In Quicksort Algorithm?
So, we should pay attention to the steps required for the Quicksort algorithm. The required steps are following:
Choose Pivot:
At first, the pivot element should be declared inside of the program. Here, the pivot element can be any element from the set provided in the program. But mainly, the first or last element is chosen as the pivot element. Sometimes, the mid element can also be chosen.
Divide:
After getting the Pivot element, we should break down the list of elements into two parts. The one part will be on the left side of the Pivot element. And another will be on the right side of the Pivot element. Now, these two parts have been taken into consideration.
Divide:
Inside those two sub-parts, the pivot element will again be picked up. And based upon that pivot element, those sub-parts will again divide into the smaller sub-parts. In this way, the complete process will be executed.
Recursion:
The same process will be followed recursively after & after till we do not receive any sub-parts having only two or three elements. Now, those elements will be sorted & the result sub-part will be produced.
Conquer:
At the last, all the mini sub-parts are going to merge. Hence, the total lists of the elements are now present in front of the programmer. Hence, there are no more tasks present to complete the Quicksort algorithm.
How Does Quicksort Work?
Now, whatever we have discussed in the previous steps we will display with one practical example.ย
Suppose, there is an array of elements present like the {1, 4, 2, 5, 3}. Now, we have to pick up the Pivot Element from that array. We are going to pick up the Last Element 3 as the Pivot Element.
Now, based on the Pivot Element, there will be two different arrays will be developed. In one array, there will be data in the sequence as like {1, 2} as Element 2 is present after Element 1. And another array will have the data as like {4, 5} with the same logic.
Now, we can further again divide those two smaller arrays with the last element as Pivot One. But, as they are already present in the correct sorted manner, we are skipping the step. Now, the Pivot Element will be placed at the right spot.
In the end, all the elements of different arrays will be merged to make the new sorted array with Quick Sort.
What Is The Pseudo-Code Of The Quicksort Algorithm In Python Programming Language?
Pseudo-codes are the higher form of the algorithms. Any algorithm can be defined using Pseudo-codes to get a better blueprint of any process. We are going to do the same thing for the Quicksort algorithm process.
Pseudo-codes are not complete code nor is it following any programming languages for the implementation process. With any normal textual language, it can be defined. The goal is to find out the complete workflow of the program.
So, the Pseudo-code of the Quicksort algorithm is following:
function-quicksort(arr)
check length(arr) <= 1
back arr
otherwise: change pivot = arr[0]
change left side = Null array
change right side = Null array
for each element ele in arr[1:]
check ele < pivot
add ele to left side
otherwise: add ele to right side
call again function-quicksort(left side)
call again function-quicksort(right side)
back all data
Now, after discussing theย Pseudo-code of the Quicksort algorithm, we are free to move for the implementation process using the Python.
How To Implement The Quicksort Python Code Easily?
Now, we are going to discuss the Python Code to develop the Quick Sort Algorithm. The development of the Quick Sort Algorithm is not a challenging task. You have to remember the policy to make the partition in the code.
And the logic to make the partition in the code, you can get from the Pseudo-Code that is being discussed earlier. One thing that is more attractive in Python Quick Sort, is that there is no need to import any package in the program to work on the process.
Python Program To Demonstrate The Implementation Process Of Quick Sort:
def qsort(x): # Declaration Of The Function
if len(x) <= 1: # Checking The Length or End Condition
return x # Returning The Value
else: # For Other Condition
p = x[0] # Getting Pivot Value
l = [k for k in x[1:] if k < p] # Generating Left Sub Array
r = [k for k in x[1:] if k >= p] # Generating Right Sub Array
return qsort(l) + [p] + qsort(r) # Recursively Calling The Function
a = [4, 2, 7, 2, 1] # Assigning The Unsorted String Value
print(โUnsorted Array: โ, a) # Printing The Original Element
b = qsort(a) # Calling The Function
print(โSorted Array: โ, b) # Printing The Elements
Steps Of The Program:ย
- First, we have to declare the array with some natural numbers placed in random order.
- Then, the Unsorted Array will be printed in the output.
- Then, the Quick Sort Function will be called in the program where the Array will be shared.
- In the Quick Sort Function, the First Element will be chosen as the Pivot Element.
- One For Loop will be executed to check lower values from the Pivot Element. And made a Left Subarray.
- By using the same manner, all the higher values than the Pivot Element will be stored in the Right Subarray.
- Now, the Quick Sort Function will be called in the Return Statement where as per the Rule, the Pivot Element is placed in between the Left Subarray & Right Subarray.
- At last, the new array will be printed in the Python Code.
Let us try to find out the output of the above code. It will help to understand the implementation process of the Quicksort algorithm in Python programming language.
Output:
From the above output, we can see that the Unsorted Array is now become a sorted one. All the elements in the Unsorted Array, even the repetitive Element 2 are placed in the correct position. So, the Python Code works completely fine.
What Are The Time & Space Complexity Of Quick Sort Algorithm?
Now, at the end of the core discussion, we want to shed some light on the Time & Space Complexity of the Quick Sort Algorithm. For any algorithm, the Time Complexity & Space Complexity indicates how much efficient the sorting algorithm is.
The Time Complexity of the Quick Sort Algorithm for the Average Case will be O(N Log N). And for the worst cases, the Time Complexity can go up to O(N^2). So, we can understand the Quick Sort Algorithm is taking time efficiently.
Now, it is time to discuss the Space Complexity of the Quick Sort Algorithm. The Space Complexity of the Quick Sort Algorithm will be the O(Log N) for average cases. And for the worst cases, the Space Complexity will be the O(N).
Indexing in Python lists may present challenges, and to tackle this issue, we’ve developed a detailed article aimed at enhancing your understanding.
What Is The Role Of Recursion In Quick Sort Algorithm?
Recursion is the pillar of the Quicksort algorithm process. Without the recursion method, we canโt implement the Quicksort algorithm in Python programming language.
Recursion is a method that calls the same function again & again time from the said function only. In this way, some processes are completed. It works similarly to the loop concept, but it takes small space.
Now, you might ask Can Quicksort Algorithm be Implemented Without Using the Recursion Method?
Yes! The Quicksort algorithm can be implemented without using the recursion method. Other sorting algorithms can also be implemented without using the same. But in that case, they will take a long time to get the solution to the problem.
In those cases, we should develop one for loop to check & divide the set of elements in the program. This is the reason, instead of using the iteration method; the recursion method is used highly in the sorting algorithms.
How Fast Is Quicksort? Read Below
Before ending the topic, we want to discuss this one of the important questions. Sometimes, you can face the question โIs Heap Sort Faster than Quicksort?โ. In all similar questions, put the Answer as YES!
The Quick Sort is one of the most important sorting algorithms that is considered the fastest. Because, the inner loop of the Quick Sort Algorithm where the For Loop is mainly used, consumes more small spaces & statements. That is the reason, Quick Sort can perform well.
On the other hand, Sorting Algorithms like Heap Sort take 4 times more statements in the For Loop before going for the execution. That is the reason, the Time Complexity of Quick Sort is the same for both Best & Average Cases.
What Are Advantages & Disadvantages Of Quick Sort Algorithms?
Advantages Of Quick Sort Algorithm:
- It is faster than any other sorting algorithm.ย
- For Large Datasets, it will be best suited to the sorting algorithm.
- The Quick Sort Algorithm is mainly used for real-world applications.
Disadvantages Of Quick Sort Algorithm:
- The worst-case time complexity is relatively too high which depends on pivot choosing.
- The Quick Sort is not suitable for the dataset which is relatively too short.
- The Quick Sort is an unstable sorting algorithm that sometimes causes problems.
Conclusion:
As we saw, the โQuick Sort in Pythonโ programming language is very important to know.
Quicksort algorithm in Python programming language is dependent upon the successful implementation of the recursion method inside of the program.
It is advisable to have a basic understanding of the Python programming language before moving into the development process. Also, the Data Structure concept should be cleared.
So, hope you have liked this piece of article. Share your thoughts in the comments section and let us know if we can improve more.
Takeaways:
- The main element of the Quick Sort Algorithm is to pick up the Pivot Element.
- Based on the Pivot Element, the Time Complexity can be different.
- The Partition Module of Quick Sort is developed on the Pivot Element Selection.
- The Quick Sort Algorithm follows the Divide and Conquer Policy.
- The Time Complexity of Quick Sort is O(N Log N).
- The Space Complexity of Quick Sort is O(Log N).
- The Quick Sort Algorithm is the fastest than any other Sorting Algorithm.
