Selection Sort is an in-place sorting algorithm that succeeds in sorting smaller arrays of values, but suffers with larger arrays.
How It Works?
Selection Sort works in-place, meaning it doesn't require a separate array for storing the sorted values. Instead we perform a series of swaps, finding lowest value (usually indicated by index
j) to index
i moves from left to right, shrinking the array at each pass.
Below is a more traditional implementation where only one swap occurs, if and only if, a value is found to be smaller than
def traditionalSelectionSort(nums: list) -> list: for i in range(len(nums) - 1): minIndex = i for j in range(i, len(nums)): if nums[j] < nums[minIndex]: minIndex = j if minIndex != i: nums[i], nums[minIndex] = nums[minIndex], nums[i] return nums print(selectionSort([3, 8, 2, 5, 7, 4])) # => [2, 3, 4, 5, 7, 8]
Below is a modified version of implementation that will swap every value (
nums[j]) less than
nums[i]. I prefer this approach since it's more condensed and swapping values in an array is a constant operation (e.g.
def modifiedSelectionSort(nums: list) -> list: for i in range(len(nums) - 1): # i = receiving min value for j in range(i, len(nums)): # j = searches for min values if nums[j] < nums[i]: # swap with values < nums[i] nums[i], nums[j] = nums[j], nums[i] return nums print(selectionSort([3, 8, 2, 5, 7, 4])) # => [2, 3, 4, 5, 7, 8]
Selection Sort is similar to Insertion Sort (except for when comparing best-case performances, in which Insertion Sort is better).
Time: Worst: O(n^2) Best: O(n^2) Average: O(n^2) Space: O(1) - swapping in place
Selection Sort - Wikipedia article on Selection Sort.