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)