Update: Create stopwatch_sort function and write doctests

sorts/stopwatch_sort.py

@@ -0,0 +1,124 @@
+"""
+One of reasons for learning about algorithms is
+that they can affect the efficiency of a program.
+Therefore, it will be helpful for learners
+to see each algorithm's sorting process speed
+and compare the results of different algorithms.
+
+This function, stopwatch_sort, will return a list of sorting results,
+so it can be used to see how long each sorting algorithm
+takes to complete the sorting process.
+"""
+
+import random
+import time
+
+from binary_insertion_sort import binary_insertion_sort
+from bubble_sort import bubble_sort_iterative
+from bucket_sort import bucket_sort
+from counting_sort import counting_sort
+from heap_sort import heap_sort
+from merge_sort import merge_sort
+from quick_sort import quick_sort
+from radix_sort import radix_sort
+from selection_sort import selection_sort
+
+
+def stopwatch_sort(func_list: list, number_of_integers: int = 10000) -> list:
+    """
+    implementation of comparing sorting algorithms
+    :param func_list: list of sorting functions
+    :param number_of_integers: number of randomly chosen integers to sort
+    :return: list of results, where each result is a list including:
+        the function name, the number of sorted integers,
+        whether the integers were sorted properly,
+        and milliseconds taken to complete the sorting process.
+
+    For example, when the following code is executed:
+    results = stopwatch_sort([binary_insertion_sort, bubble_sort_iterative], 8000)
+
+    The results will be similar to:
+    [['binary_insertion_sort', 8000, True, 2186.258316040039],
+    ['bubble_sort_iterative', 8000, True, 7760.7762813568115]]
+
+    Examples:
+    >>> first_results = stopwatch_sort([binary_insertion_sort], 5000)
+    >>> len(first_results)
+    1
+    >>> len(first_results[0])
+    4
+    >>> first_results[0][0]
+    'binary_insertion_sort'
+    >>> first_results[0][1]
+    5000
+    >>> first_results[0][2]
+    True
+    >>> float(first_results[0][3]) >= 0
+    True
+    >>> second_results = stopwatch_sort([binary_insertion_sort, merge_sort])
+    >>> len(second_results)
+    2
+    >>> len(second_results[1])
+    4
+    >>> second_results[1][0]
+    'merge_sort'
+    >>> second_results[1][1]
+    10000
+    >>> second_results[1][2]
+    True
+    >>> float(second_results[1][3]) >= 0
+    True
+    """
+
+    range_multiplier = 2
+    int_range = (
+        number_of_integers * range_multiplier
+    )  # Extendable range of random choice
+    input_integers = [random.randint(0, int_range) for _ in range(number_of_integers)]
+    sorted_integers = sorted(input_integers)
+
+    result_list = []
+
+    for func in func_list:
+        # To prevent input_integers from being changed by function
+        instance_integers = input_integers.copy()
+
+        # Record the start and end time of sorting
+        start_time = time.time()
+        sorted_numbers = func(instance_integers)
+        end_time = time.time()
+
+        # Each result consists of four elements
+        func_name = func.__name__
+        length_of_sorted_numbers = len(sorted_numbers)
+        properly_sorted = sorted_numbers == sorted_integers
+        process_time_milliseconds = (end_time - start_time) * 1000
+        process_result = [
+            func_name,
+            length_of_sorted_numbers,
+            properly_sorted,
+            process_time_milliseconds,
+        ]
+        result_list.append(process_result)
+
+    return result_list
+
+
+if __name__ == "__main__":
+    user_input = input("Enter how many random numbers to be sorted: ")
+    user_input_int = int(user_input)
+    algorithm_list = [
+        binary_insertion_sort,
+        bubble_sort_iterative,
+        bucket_sort,
+        counting_sort,
+        heap_sort,
+        merge_sort,
+        quick_sort,
+        radix_sort,
+        selection_sort,
+    ]
+
+    results = stopwatch_sort(algorithm_list, user_input_int)
+    for result in results:
+        print(result)