""" Introspective Sort is a hybrid sort (Quick Sort + Heap Sort + Insertion Sort) if the size of the list is under 16, use insertion sort https://en.wikipedia.org/wiki/Introsort """ import math def insertion_sort(array: list, start: int = 0, end: int = 0) -> list: """ >>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12] >>> insertion_sort(array, 0, len(array)) [1, 2, 4, 6, 7, 8, 8, 12, 14, 14, 22, 23, 27, 45, 56, 79] >>> array = [21, 15, 11, 45, -2, -11, 46] >>> insertion_sort(array, 0, len(array)) [-11, -2, 11, 15, 21, 45, 46] >>> array = [-2, 0, 89, 11, 48, 79, 12] >>> insertion_sort(array, 0, len(array)) [-2, 0, 11, 12, 48, 79, 89] >>> array = ['a', 'z', 'd', 'p', 'v', 'l', 'o', 'o'] >>> insertion_sort(array, 0, len(array)) ['a', 'd', 'l', 'o', 'o', 'p', 'v', 'z'] >>> array = [73.568, 73.56, -45.03, 1.7, 0, 89.45] >>> insertion_sort(array, 0, len(array)) [-45.03, 0, 1.7, 73.56, 73.568, 89.45] """ end = end or len(array) for i in range(start, end): temp_index = i temp_index_value = array[i] while temp_index != start and temp_index_value < array[temp_index - 1]: array[temp_index] = array[temp_index - 1] temp_index -= 1 array[temp_index] = temp_index_value return array def heapify(array: list, index: int, heap_size: int) -> None: # Max Heap """ >>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12] >>> heapify(array, len(array) // 2, len(array)) """ largest = index left_index = 2 * index + 1 # Left Node right_index = 2 * index + 2 # Right Node if left_index < heap_size and array[largest] < array[left_index]: largest = left_index if right_index < heap_size and array[largest] < array[right_index]: largest = right_index if largest != index: array[index], array[largest] = array[largest], array[index] heapify(array, largest, heap_size) def heap_sort(array: list) -> list: """ >>> heap_sort([4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]) [1, 2, 4, 6, 7, 8, 8, 12, 14, 14, 22, 23, 27, 45, 56, 79] >>> heap_sort([-2, -11, 0, 0, 0, 87, 45, -69, 78, 12, 10, 103, 89, 52]) [-69, -11, -2, 0, 0, 0, 10, 12, 45, 52, 78, 87, 89, 103] >>> heap_sort(['b', 'd', 'e', 'f', 'g', 'p', 'x', 'z', 'b', 's', 'e', 'u', 'v']) ['b', 'b', 'd', 'e', 'e', 'f', 'g', 'p', 's', 'u', 'v', 'x', 'z'] >>> heap_sort([6.2, -45.54, 8465.20, 758.56, -457.0, 0, 1, 2.879, 1.7, 11.7]) [-457.0, -45.54, 0, 1, 1.7, 2.879, 6.2, 11.7, 758.56, 8465.2] """ n = len(array) for i in range(n // 2, -1, -1): heapify(array, i, n) for i in range(n - 1, 0, -1): array[i], array[0] = array[0], array[i] heapify(array, 0, i) return array def median_of_3( array: list, first_index: int, middle_index: int, last_index: int ) -> int: """ >>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12] >>> median_of_3(array, 0, ((len(array) - 0) // 2) + 1, len(array) - 1) 12 >>> array = [13, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12] >>> median_of_3(array, 0, ((len(array) - 0) // 2) + 1, len(array) - 1) 13 >>> array = [4, 2, 6, 8, 1, 7, 8, 22, 15, 14, 27, 79, 23, 45, 14, 16] >>> median_of_3(array, 0, ((len(array) - 0) // 2) + 1, len(array) - 1) 14 """ if (array[first_index] > array[middle_index]) != ( array[first_index] > array[last_index] ): return array[first_index] elif (array[middle_index] > array[first_index]) != ( array[middle_index] > array[last_index] ): return array[middle_index] else: return array[last_index] def partition(array: list, low: int, high: int, pivot: int) -> int: """ >>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12] >>> partition(array, 0, len(array), 12) 8 >>> array = [21, 15, 11, 45, -2, -11, 46] >>> partition(array, 0, len(array), 15) 3 >>> array = ['a', 'z', 'd', 'p', 'v', 'l', 'o', 'o'] >>> partition(array, 0, len(array), 'p') 5 >>> array = [6.2, -45.54, 8465.20, 758.56, -457.0, 0, 1, 2.879, 1.7, 11.7] >>> partition(array, 0, len(array), 2.879) 6 """ i = low j = high while True: while array[i] < pivot: i += 1 j -= 1 while pivot < array[j]: j -= 1 if i >= j: return i array[i], array[j] = array[j], array[i] i += 1 def sort(array: list) -> list: """ :param collection: some mutable ordered collection with heterogeneous comparable items inside :return: the same collection ordered by ascending Examples: >>> sort([4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]) [1, 2, 4, 6, 7, 8, 8, 12, 14, 14, 22, 23, 27, 45, 56, 79] >>> sort([-1, -5, -3, -13, -44]) [-44, -13, -5, -3, -1] >>> sort([]) [] >>> sort([5]) [5] >>> sort([-3, 0, -7, 6, 23, -34]) [-34, -7, -3, 0, 6, 23] >>> sort([1.7, 1.0, 3.3, 2.1, 0.3 ]) [0.3, 1.0, 1.7, 2.1, 3.3] >>> sort(['d', 'a', 'b', 'e', 'c']) ['a', 'b', 'c', 'd', 'e'] """ if len(array) == 0: return array max_depth = 2 * math.ceil(math.log2(len(array))) size_threshold = 16 return intro_sort(array, 0, len(array), size_threshold, max_depth) def intro_sort( array: list, start: int, end: int, size_threshold: int, max_depth: int ) -> list: """ >>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12] >>> max_depth = 2 * math.ceil(math.log2(len(array))) >>> intro_sort(array, 0, len(array), 16, max_depth) [1, 2, 4, 6, 7, 8, 8, 12, 14, 14, 22, 23, 27, 45, 56, 79] """ while end - start > size_threshold: if max_depth == 0: return heap_sort(array) max_depth -= 1 pivot = median_of_3(array, start, start + ((end - start) // 2) + 1, end - 1) p = partition(array, start, end, pivot) intro_sort(array, p, end, size_threshold, max_depth) end = p return insertion_sort(array, start, end) if __name__ == "__main__": import doctest doctest.testmod() user_input = input("Enter numbers separated by a comma : ").strip() unsorted = [float(item) for item in user_input.split(",")] print(f"{sort(unsorted) = }")