def test_remove_duplicate_values_with_hash_table_multiple():
my_linked_list = LinkedList()
input_values = [0, 0, 1, 1, 2, 2, 3, 0, 1, 2, 3, 4, 5, 6, 5, 7, 8, 9, 1, 0, 0, 0]
my_linked_list.append_nodes(input_values)
my_linked_list.remove_duplicate_values_use_hashtable()
expected_output_values = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
actual_output_values = linked_list_values_to_array(my_linked_list)
assert expected_output_values == actual_output_values
def main():
sets_of_duplicates = 4
max_value = 10000
big_array = initialize_array_with_duplicates(max_value, sets_of_duplicates)
linked_list_0_non_opt = LinkedList()
ta = datetime.now()
linked_list_0_non_opt.append_nodes(big_array)
tb = datetime.now()
append_time = tb - ta
print("Time to prepare list non-optimized:", append_time)
print("List size:", linked_list_0_non_opt.get_node_count())
linked_list_1 = LinkedList()
t0 = datetime.now()
linked_list_1.append_nodes_optimized(big_array)
t1 = datetime.now()
append_time = t1 - t0
print("Time to prepare list optimized:", append_time)
print("List size:", linked_list_1.get_node_count())
t2 = datetime.now()
linked_list_1.remove_duplicate_values()
t3 = datetime.now()
dedup_time_list = t3 - t2
print("Time to de-dup using built-in list as additional data structure:", dedup_time_list)
print("Size of de-duped list:", linked_list_1.get_node_count())
linked_list_2 = LinkedList()
t4 = datetime.now()
linked_list_2.append_nodes_optimized(big_array)
t5 = datetime.now()
append_time = t5 - t4
print("Time to prepare list optimized:", append_time)
print("List size:", linked_list_2.get_node_count())
t6 = datetime.now()
linked_list_2.remove_duplicate_values_use_hashtable()
t7 = datetime.now()
dedup_time_dict = t7 - t6
print("Time to de-dup using dictionary as additional data structure:", dedup_time_dict)
print("Size of de-duped list:", linked_list_2.get_node_count())
