A.10: Sorting Algorithms

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Introduction
This module explores various ways to sort unsorted arrays of numbers. While our examples only use numbers, the same methods can be used to sort arrays of arbitrary data types according to arbitrary sort order.
We will rarely write sorting algorithms as software engineers because most languages have built-in sorting functions, and DS&A interview questions rarely test sorting algorithms because sorting algorithms are relatively easily memorised. However, we will learn sorting algorithms because they are a common-enough concept in DS&A and the strategies behind sorting algorithms can be relevant to how we approach other DS&A problems.
There is no need to memorise the below sorting algorithms' implementation. Just understand how they work such that you could describe their logic well-enough to write pseudocode.
Naive Sorting Algorithms
Selection Sort
Runtime: O(n²)
Space: O(1)
Sort In-Place: Yes
Stable: No
Attributes
good space complexity
simple code
slow for large lists / fast for small lists
Selection Sort Pseudo Code
for each element in the array
  consider the current element as the least value
  for each element in the rest of the array forward from the current element
    look for an element that is less
      if it's less, set the inner loop element as the least value
  swap the least value and the current element
Selection Sort
from pprint import pprint
​
A = [64, 25, 12, 22, 11]
​
def selection_sort(arr):
​
    # traverse through all array elements
    for outer_idx in range(len(arr)):
​
        # given current point in array
        # mark that value as min
        min_idx = outer_idx
​
        # start inner loop
        # loop starting at outer_idx to end
        for i in range(outer_idx+1, len(arr)):
​
            # if a lower value is found
            if arr[min_idx] > arr[i]:
                min_idx = i
​
        # loop set a min value
        # swap the found minimum element with
        # the first element
        arr[outer_idx], arr[min_idx] = arr[min_idx], arr[outer_idx]
    return arr
​
result = selection_sort(A)
print ("Sorted array")
pprint(result)
Selection Sort with Prints
from pprint import pprint
​
A = [64, 25, 12, 22, 11]
​
def selection_sort(arr):
​
    # Traverse through all array elements
    for outer_idx in range(len(arr)):
​
        # given current point in array
        # mark that value as min
        min_idx = outer_idx
        print(f'set min value for location: {outer_idx} : {arr[outer_idx]}')
​
        # start inner loop
        # loop starting at outer_idx to end
        print('starting inner loop')
        for i in range(outer_idx+1, len(arr)):
​
            # if a lower value is found
            if arr[min_idx] > arr[i]:
                print(f'found a lower value: {arr[i]}')
                min_idx = i
​
            print('*******************')
​
        # loop set a min value
        # swap the found minimum element with
        # the first element
        print(f'swapping {arr[outer_idx]} with {arr[min_idx]}')
        arr[outer_idx], arr[min_idx] = arr[min_idx], arr[outer_idx]
        print('done with outer loop')
        print('-------------------')
    return arr
​
result = selection_sort(A)
print ("Sorted array")
pprint( result)
Further Reading
​https://www.algostructure.com/sorting/selectionsort.php​
​https://www.hackerearth.com/practice/algorithms/sorting/selection-sort/visualize/​
​https://www.programiz.com/dsa/selection-sort​
​https://www.tutorialspoint.com/data_structures_algorithms/selection_sort_algorithm.htm​
​https://en.wikipedia.org/wiki/Insertion_sort​
Insertion Sort
Runtime: O(n²)
Space: O(1)
Sort In-Place: Yes
Stable: Yes
Attributes
good space complexity
simple code
slow for large lists / fast for small lists
good for nearly sorted lists - will exit early if list is done ("adaptive")
can sort while new items are being added to list ("online")
Insertion Sort Pseudo Code
begin with the second element
for each element in the array, starting with the second element
  consider the current element as "removed"
  look backwards through the array starting from the current element
    if the current element is more than the inner loop value
      move the current element into the inner loop location
    if the inner loop element is less than the current element, end the loop
Insertion Sort
from pprint import pprint
​
A = [64, 25, 12, 22, 11]
​
def insertion_sort(arr):
​
    # Traverse through the array starting with the 2nd element
    for i in range(1, len(arr)):
​
        # set the current element as key
        key = arr[i]
​
        # look backwards through the array
        # move every value forward by one until it finds
        # a value smaller than key
        j = i-1
        while j >= 0 and key < arr[j] :
                # move j ahead one
                arr[j + 1] = arr[j]
                j -= 1
        # put key in the space we found using the loop
        arr[j + 1] = key
​
    return arr
​
result = insertion_sort(A)
print ("Sorted array")
pprint( result)
Insertion Sort with Prints
from pprint import pprint
​
A = [64, 25, 12, 22, 11]
​
def insertion_sort(arr):
​
    # Traverse through the array starting with the 2nd element
    for i in range(1, len(arr)):
​
        print('****************************')
        # set the current element as key
        key = arr[i]
        print(f'removed: {key}')
​
        # look backwards through the array
        # move every value forward by one until it finds
        # a value smaller than key
        print('looking back ')
        j = i-1
        while j >= 0 and key < arr[j] :
                # move j ahead one
                print(f'putting {arr[j]} at: {j+1}')
                arr[j + 1] = arr[j]
                j -= 1
        # put key in the space we found using the loop
        print(f'putting *key* {key} at: {j+1}')
        arr[j + 1] = key
​
    return arr
​
result = insertion_sort(A)
print ("Sorted array")
pprint( result)
Further Reading
​https://www.algostructure.com/sorting/insertionsort.php​
​https://www.hackerearth.com/practice/algorithms/sorting/insertion-sort/visualize/​
​https://www.programiz.com/dsa/insertion-sort​
​https://www.geeksforgeeks.org/insertion-sort/​
Bubble Sort
Runtime: O(n²)
Space: O(1)
Sort In-Place: Yes
Stable: Yes
Attributes
good space complexity
simple code
slow for large lists / fast for small lists
Bubble sort is considered the "beginner's" sorting algorithm. It is slow and lacks the features of other naive algorithms. However, the pseudocode is simple and so it is used to introduce concepts of sorting algorithms.
Bubble Sort Pseudo Code
for each element in an array
  starting with the current element and
  look at all elements after it
    compare the inner element with it's neighbor
    if the inner elemnt is larger
      swap them
Bubble Sort
from pprint import pprint
​
A = [64, 25, 12, 22, 11]
​
def bubble_sort(arr):
​
    # Traverse through the array
    for i in range(len(arr)):
​
        # loop to compare array elements
        for j in range(0, len(arr) - i - 1):
​
            # compare two adjacent elements
            # change > to < to sort in descending order
            if arr[j] > arr[j + 1]:
​
                # swapping elements if elements
                # are not in the intended order
                temp = arr[j]
                arr[j] = arr[j+1]
                arr[j+1] = temp
​
    return arr
​
result = bubble_sort(A)
print ("Sorted array")
pprint( result)
Bubble Sort with Print
from pprint import pprint
​
A = [64, 25, 12, 22, 11]
​
def bubble_sort(arr):
​
    # Traverse through the array
    for i in range(len(arr)):
​
        print('***************************')
        print(f'at: {i}')
        # loop to compare array elements
        for j in range(0, len(arr) - i - 1):
​
            # compare two adjacent elements
            # change > to < to sort in descending order
            print(f'comparing: {j} to {j+1} {arr}')
            if arr[j] > arr[j + 1]:
​
                print(f'its larger, swapping : {arr[j]} to {arr[j+1]}')
                # swapping elements if elements
                # are not in the intended order
                temp = arr[j]
                arr[j] = arr[j+1]
                arr[j+1] = temp
​
    return arr
​
result = bubble_sort(A)
print ("Sorted array")
pprint( result)
What's the Difference Between Insetion Sort and Bubble Sort?
The main difference is that insertion sort finds an element's place in the already sorted list, and bubble sort does not. This behavior is why insertion sort is "online" and new unsorted things can be added to the end of the array.
See more here: https://stackoverflow.com/a/17271911/271932​
Further Reading
​https://www.algostructure.com/sorting/bubblesort.php​
​https://www.hackerearth.com/practice/algorithms/sorting/bubble-sort/visualize/​
​https://www.programiz.com/dsa/bubble-sort​
​https://www.geeksforgeeks.org/bubble-sort/​
​https://en.wikipedia.org/wiki/Bubble_sort​
A.9.1: Recursive Backtracking
A.10.1: Divide and Conquer Sorting
Last modified 4mo ago
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Introduction
Naive Sorting Algorithms
Selection Sort
Insertion Sort
Bubble Sort