def test_binary_search(self): array = [1, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 6] self.assertEqual(10, binary_search(array, 5)) self.assertEqual(11, binary_search(array, 6)) self.assertEqual(None, binary_search(array, 7)) self.assertEqual(None, binary_search(array, -1)) # Test binary_search_recur self.assertEqual(10, binary_search_recur(array, 0, 11, 5)) self.assertEqual(11, binary_search_recur(array, 0, 11, 6)) self.assertEqual(-1, binary_search_recur(array, 0, 11, 7)) self.assertEqual(-1, binary_search_recur(array, 0, 11, -1))
test_number = test_list[random.randrange(len(test_list))] print() print("List Length: ", list_length) print("test_number: ", test_number) # Testing on the unsorted list for sequential. start_sequential = time.time() sequential_search(test_list, test_number) end_sequential = time.time() time_sequential = end_sequential - start_sequential print("Time for sequential sort (unsorted): ", time_sequential) test_list = bubble_sort(test_list) start_sequential = time.time() sequential_search(test_list, test_number) end_sequential = time.time() time_sequential = end_sequential - start_sequential start_binary = time.time() binary_search(test_list, test_number) end_binary = time.time() time_binary = end_binary - start_binary print("Time for sequential sort (sorted): ", time_sequential) print("Time for binary sort: ", time_binary) list_length = list_length * 10
''' Binary Search Dependency Library install : pip install algorithms ''' from algorithms import search given_list = [1, 2, 3, 4, 5] number_to_search = int(input('Enter the Number to search : ')) if search.binary_search(given_list, number_to_search) is None: print('Provided Number is not present in list') print('Unsuccessful') else: print('privided number is present in index : ', search.binary_search(given_list, number_to_search)) print('Successful')
# Design and Analysis of Data Structures and Algorithms # Push Test import random from algorithms.sort import bubble_sort, selection_sort, insertion_sort, merge_sort, quick_sort from algorithms.search import linear_search, binary_search, jump_search #numbers = random.sample(range(100, 999), 899) numbers = [10, 20, 30, 40, 50] x = 10 #result = linear_search(numbers, x) result = binary_search(numbers, x) #result = jump_search(numbers, x, len(numbers)) if(result == -1): print("Element is not present in array") else: print("Element is present at index", result) ''' print("Unsorted List") print(numbers) print("Bubble Sort") bs = bubble_sort(numbers) print(bs) print("Selection Sort") ss = selection_sort(numbers) print(ss)
from algorithms.search import binary_search, binary_search_recur import random alist = [random.randint(1, 5) for i in range(100)] print(alist) print(binary_search(alist, 4)) blist = [random.randint(1, 5) for i in range(100)] print(binary_search_recur(blist, 40, 80, 5))
def test_binary_search(search_data, target, expected): assert search.binary_search(search_data, target) == expected reference(search_data, target, expected) leetcode_algo(search_data, target, expected)
def test_binary_search(test_input, expected): assert binary_search(test_input[0], test_input[1]) == expected
def step_impl(context): array = [] context.result = search.binary_search(array, 1)
def step_impl(context): array = [-95423814.4, -851, -52.4856324126, -2.54, 26, 99] context.result = search.binary_search(array, -2.54)
def step_impl(context): array = [3, 58, 5, 8, 26, 99] context.result = search.binary_search(array, 58)