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mirror of https://github.com/bregman-arie/devops-exercises.git synced 2025-07-09 23:45:42 +02:00

Convert binary search to iterative, add helper functions and main with complexity docstring while preserving functionality (#10552)

Co-authored-by: Arie Bregman <bregman.arie@gmail.com>
This commit is contained in:
Adam Djellouli
2025-03-26 21:22:05 -01:00
committed by GitHub
parent 70f382d5b1
commit 689a09a3b1

View File

@ -1,28 +1,42 @@
#!/usr/bin/env python
import random
from typing import List
from typing import List, Optional
def binary_search(arr: List[int], lb: int, ub: int, target: int) -> int:
def binary_search(arr: List[int], lb: int, ub: int, target: int) -> Optional[int]:
"""
A Binary Search Example which has O(log n) time complexity.
"""
if lb <= ub:
mid: int = lb + (ub - lb) // 2
while lb <= ub:
mid = lb + (ub - lb) // 2
if arr[mid] == target:
return mid
elif arr[mid] < target:
return binary_search(arr, mid + 1, ub, target)
lb = mid + 1
else:
return binary_search(arr, lb, mid - 1, target)
else:
return 0
ub = mid - 1
return -1
def generate_random_list(size: int = 10, lower: int = 1, upper: int = 50) -> List[int]:
return sorted(random.randint(lower, upper) for _ in range(size))
def find_target_in_list(target: int, lst: List[int]) -> int:
return binary_search(lst, 0, len(lst) - 1, target)
def main():
"""
Executes the binary search algorithm with a randomly generated list.
Time Complexity: O(log n)
"""
rand_num_li = generate_random_list()
target = random.randint(1, 50)
index = find_target_in_list(target, rand_num_li)
print(f"List: {rand_num_li}\nTarget: {target}\nIndex: {index}")
if __name__ == '__main__':
rand_num_li: List[int] = sorted([random.randint(1, 50) for _ in range(10)])
target: int = random.randint(1, 50)
print("List: {}\nTarget: {}\nIndex: {}".format(
rand_num_li, target,
binary_search(rand_num_li, 0, len(rand_num_li) - 1, target)))
main()