CommonLounge Archive

Hands-on: Implementing Quick-sort

June 29, 2018

Now that we have learnt about quick-sort, it’s time to implement it. You can work any any programming language of your choice - Python, C++, Java, or anything else you want. Let’s get started!

Implementing Quick-sort

Python

Below, we provide a short Python code template for you to implement quick-sort.

# quick_sort.py 
import random
def quick_sort(array):
    # base case 
    # choose pivot 
    # split into left and right 
    # quick-sort each segment 
    # return 
array = [5, 10, 8, 7, 3, 7, 6, 12, 2, 7]
result = quick_sort(array)
assert result == [2, 3, 5, 6, 7, 7, 7, 8, 10, 12], result

C++, Java, etc

If you’re not using Python, have your implementation accept test cases from standard input, and print results to standard output.

Input description: The first line contains the number of test cases T. This is followed by T lines. Each line starts with a number N, the size of the array. On the same line, the N numbers of the array are listed one after the other.

Sample input:

2
3 227 198 19
10 458 687 945 378 479 421 33 295 922 840

Output description: Output should contain T lines. Each line should just contain the numbers in sorted order, separated by spaces.

Sample output:

19 198 227
33 295 378 421 458 479 687 840 922 945

Notes

The trickiest part about implementing quick-sort is the partition function. Specifically, be careful about how you handle the case where the pivot appears multiple times in the array.

Grading your solution

Python

You can use the following file to grade your solution.

# grader.py
from __future__ import print_function
import datetime
import random
from quick_sort import quick_sort
npassed, nfailed = 0, 0
for itest in range(1, 13):
    print('Test case:', itest)
    nelements = random.randint(int((10**(itest/2.))/2), int(10**(itest/2.)))
    print('Array size:', nelements)
    array = [random.randint(1, 100*nelements) for _ in range(nelements)]
    tic = datetime.datetime.now()
    submission = quick_sort(array)
    toc = datetime.datetime.now()
    answer = sorted(array)
    correct = len(submission) == len(answer) and (submission == answer)
    if correct:
        print('PASSED (Runtime = %.2f seconds)' % (toc-tic).total_seconds())
        npassed += 1
    else:
        print('FAILED')
        nfailed += 1
        print(array)
        print(submission)
        print(answer)
    print('='*100)
print('TOTAL PASSED: %d. TOTAL FAILED: %d.' % (npassed, nfailed))

Save the file above, and then run the following command:

python grader.py

and you should see the results of running the grader.

C++, Java, etc

You’ll find all the files required to check your solution here: Algorithms - Sorting. In particular, the folder includes 3 files - input, answer and grader.py.

Do the following to check your solution.

{COMMAND TO RUN C++/JAVA CODE} < input > output 
python grader.py output answer

Bonus: Implement in-place Quick-sort

If you’d like to, you can also implement in-place quick-sort. Review the section on In-place Quick-sort from the tutorial if you get stuck.

Again, be careful about how you handle the case where the pivot appears multiple times in the array.

Solution

The solution for this assignment can be found here: quick_sort.py. It also contains the solution for the bonus problem. quick_sort() takes about 7 seconds to run for input size 750,000. quick_sort_inplace() takes about 3.5 seconds. Note that if you implemented the solution in C++ / Java, your code should be executing about > 5x faster.


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