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114#!/usr/bin/env python3
"""
Pure Python implementation of exponential search algorithm
For more information, see the Wikipedia page:
https://en.wikipedia.org/wiki/Exponential_search
For doctests run the following command:
python3 -m doctest -v exponential_search.py
For manual testing run:
python3 exponential_search.py
"""
from __future__ import annotations
def binary_search_by_recursion(
sorted_collection: list[int], item: int, left: int = 0, right: int = -1
) -> int:
"""Pure implementation of binary search algorithm in Python using recursion
Be careful: the collection must be ascending sorted otherwise, the result will be
unpredictable.
:param sorted_collection: some ascending sorted collection with comparable items
:param item: item value to search
:param left: starting index for the search
:param right: ending index for the search
:return: index of the found item or -1 if the item is not found
Examples:
>>> binary_search_by_recursion([0, 5, 7, 10, 15], 0, 0, 4)
0
>>> binary_search_by_recursion([0, 5, 7, 10, 15], 15, 0, 4)
4
>>> binary_search_by_recursion([0, 5, 7, 10, 15], 5, 0, 4)
1
>>> binary_search_by_recursion([0, 5, 7, 10, 15], 6, 0, 4)
-1
"""
if right < 0:
right = len(sorted_collection) - 1
if list(sorted_collection) != sorted(sorted_collection):
raise ValueError("sorted_collection must be sorted in ascending order")
if right < left:
return -1
midpoint = left + (right - left) // 2
if sorted_collection[midpoint] == item:
return midpoint
elif sorted_collection[midpoint] > item:
return binary_search_by_recursion(sorted_collection, item, left, midpoint - 1)
else:
return binary_search_by_recursion(sorted_collection, item, midpoint + 1, right)
def exponential_search(sorted_collection: list[int], item: int) -> int:
"""
Pure implementation of an exponential search algorithm in Python.
For more information, refer to:
https://en.wikipedia.org/wiki/Exponential_search
Be careful: the collection must be ascending sorted, otherwise the result will be
unpredictable.
:param sorted_collection: some ascending sorted collection with comparable items
:param item: item value to search
:return: index of the found item or -1 if the item is not found
The time complexity of this algorithm is O(log i) where i is the index of the item.
Examples:
>>> exponential_search([0, 5, 7, 10, 15], 0)
0
>>> exponential_search([0, 5, 7, 10, 15], 15)
4
>>> exponential_search([0, 5, 7, 10, 15], 5)
1
>>> exponential_search([0, 5, 7, 10, 15], 6)
-1
"""
if list(sorted_collection) != sorted(sorted_collection):
raise ValueError("sorted_collection must be sorted in ascending order")
if sorted_collection[0] == item:
return 0
bound = 1
while bound < len(sorted_collection) and sorted_collection[bound] < item:
bound *= 2
left = bound // 2
right = min(bound, len(sorted_collection) - 1)
return binary_search_by_recursion(sorted_collection, item, left, right)
if __name__ == "__main__":
import doctest
doctest.testmod()
# Manual testing
user_input = input("Enter numbers separated by commas: ").strip()
collection = sorted(int(item) for item in user_input.split(","))
target = int(input("Enter a number to search for: "))
result = exponential_search(sorted_collection=collection, item=target)
if result == -1:
print(f"{target} was not found in {collection}.")
else:
print(f"{target} was found at index {result} in {collection}.")