Seems like you already incorporated a few of the suggestions from back when this was on StackOverflow, e.g. changing the inner loop tomax. However, you do so in a very inefficient way:

• you create a slice of the list, O(n) time and space
• you get themax of that slice, O(n) time
• you get theindex of that element, O(n) time

Instead, you can get themax of therange of indices, using akey function for comparing the actual values at those indices:

largest = max(range(0, lastUnsortedInteger+1), key=arr.__getitem__)

This way, this step has only O(n) time (for Python 3).

Some other points:

• thean parameter (the length of the array/list) is not necessary, you can uselen
• in my opinion, it is a bit simpler looping from first to last index, and usingmin instead ofmax accordingly
• since the swap is a single line now and only used once, we could inline this directly into the sorting function
• the function modifies the list in-place, so noreturn is needed and might lead users to expect that the function does not modify the list but create a sorted copy instead
• technically,arr is not an array but alist, and you might prefersnake_case tocamelCase (it's "Python" after all)

My version:

def selection_sort(lst):    for i in range(len(lst) - 1):        k = min(range(i, len(lst)), key=lst.__getitem__)        lst[i], lst[k] = lst[k], lst[i]

Needless to say, for all practical purposes you should just usesorted orsort.

• python
• algorithm
• sorting