Merge sort is recursive:

Base case: a list of 0 or 1 items is already sorted.
Otherwise, split the list in half, merge sort each half (recursively), and merge the two sorted halves.

def merge(left, right):
    result = []
    i = j = 0
    while i < len(left) and j < len(right):
        if left[i] <= right[j]:
            result.append(left[i])
            i += 1
        else:
            result.append(right[j])
            j += 1
    return result + left[i:] + right[j:]

def merge_sort(items):
    if len(items) <= 1:
        return items
    mid = len(items) // 2
    return merge(merge_sort(items[:mid]), merge_sort(items[mid:]))

print(merge_sort([38, 27, 43, 3, 9, 82, 10]))

Splitting in half repeatedly gives about log n levels, and each level does O(n) work merging, so merge sort is O(n log n). For a million items that's around 20 million steps instead of the 500 billion selection sort needs.