start = time.time()
BubbleSort.bubble_sort(test_list)
finish = time.time()
print("********************************")
print("BubbleSort: ", test_list)
print("time: %f" % (finish - start))
print("\n")
test_list = [
1, 5, 52, 4, 23, 1, 32, 4, 5, 6, 19, 4234, 100, 2, 3, 45, 68, 125, 37,
54614, 2, 46, 67, 1, 5, 52, 4, 23, 1, 32, 4, 5, 6, 19, 4234, 100, 2, 3,
45, 68, 125, 37, 54614, 2, 46, 67, 1, 5, 52, 4, 23, 1, 32, 4, 5, 6, 19,
4234, 100, 2, 3, 45, 68, 125, 37, 54614, 2, 46, 67
]
start = time.time()
SelectionSort.selection_sort(test_list)
finish = time.time()
print("********************************")
print("SelectionSort: ", test_list)
print("time: %f" % (finish - start))
print("\n")
test_list = [
1, 5, 52, 4, 23, 1, 32, 4, 5, 6, 19, 4234, 100, 2, 3, 45, 68, 125, 37,
54614, 2, 46, 67, 1, 5, 52, 4, 23, 1, 32, 4, 5, 6, 19, 4234, 100, 2, 3,
45, 68, 125, 37, 54614, 2, 46, 67, 1, 5, 52, 4, 23, 1, 32, 4, 5, 6, 19,
4234, 100, 2, 3, 45, 68, 125, 37, 54614, 2, 46, 67
]
start = time.time()
InsertionSort.insertion_sort(test_list)
finish = time.time()
def test_random_input_list(self):
self.assertTrue(SelectionSort.selection_sort([5, 3, 7, 2]) == [2, 3, 5, 7])
def test_reversed_input_list(self):
self.assertTrue(SelectionSort.selection_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5])
def test_edge_case_one_item_input_list(self): #Expected to return input_list as it is
self.assertTrue(SelectionSort.selection_sort([1]) == [1])
def test_edge_case_empty_input_list(self): #Exepcted to return input_list as it is
self.assertTrue(SelectionSort.selection_sort([]) == [])
# we have a data set starting with the very basic happy path to complex
data = {
"data1": range(10000) #Large sorted array
}
#-----------------------------------------------------------------------------#
# BRUTE FORCE SORTING #
#-----------------------------------------------------------------------------#
# SELECTION SORTING
for i in range(len(data)):
# invoke the start time to measure the performance
start_time = time.time()
# Calling selection_sort for each data set
SelectionSort.selection_sort(data["data" + str(i + 1)])
print("Selection time for data" + str(i + 1) + " = " +
str(time.time() - start_time))
# BUBBLE SORTING
for i in range(len(data)):
# invoke the start time to measure the performance
start_time = time.time()
# Calling bubble_sort for each data set
BubbleSort.bubble_sort(data["data" + str(i + 1)])
print("Bubble time for data" + str(i + 1) + " = " +
str(time.time() - start_time))
#-----------------------------------------------------------------------------#
# DECREASE AND CONQUER #
#-----------------------------------------------------------------------------#