Add Exponential Search algorithm to searches module

searches/exponential_search.py

@@ -1,113 +1,48 @@
-#!/usr/bin/env python3
-
 """
-Pure Python implementation of exponential search algorithm
+Exponential Search Algorithm
 
-For more information, see the Wikipedia page:
-https://en.wikipedia.org/wiki/Exponential_search
+Time Complexity:
+- Best Case: O(1)
+- Average/Worst Case: O(log i), where i is the index of the first element >= target
 
-For doctests run the following command:
-python3 -m doctest -v exponential_search.py
+Use Case:
+Efficient for searching in sorted arrays where the target is near the beginning.
 
-For manual testing run:
-python3 exponential_search.py
+Author: Michael Alexander Montoya
 """
 
-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:
+def exponential_search(arr, target):
+    if len(arr) == 0:
         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:
+    if arr[0] == target:
         return 0
 
-    bound = 1
-    while bound < len(sorted_collection) and sorted_collection[bound] < item:
-        bound *= 2
+    # Find range for binary search by repeated doubling
+    index = 1
+    while index < len(arr) and arr[index] <= target:
+        index *= 2
 
-    left = bound // 2
-    right = min(bound, len(sorted_collection) - 1)
-    return binary_search_by_recursion(sorted_collection, item, left, right)
+    # Perform binary search in the found range
+    return binary_search(arr, target, index // 2, min(index, len(arr) - 1))
 
 
-if __name__ == "__main__":
-    import doctest
+def binary_search(arr, target, left, right):
+    while left <= right:
+        mid = (left + right) // 2
+        if arr[mid] == target:
+            return mid
+        elif arr[mid] < target:
+            left = mid + 1
+        else:
+            right = mid - 1
+    return -1
 
-    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}.")
+# Example usage:
+if __name__ == "__main__":
+    array = [1, 3, 5, 7, 9, 13, 17, 21, 24, 27, 30]
+    target = 13
+    result = exponential_search(array, target)
+    print(f"Target {target} found at index: {result}")

searches/reservoir_sampling.py

@@ -0,0 +1,48 @@
+"""
+Reservoir Sampling Algorithm
+
+Use Case:
+Efficient for selecting k random items from a data stream of unknown size,
+or when the entire dataset cannot fit into memory.
+
+Time Complexity:
+- O(n), where n is the total number of items
+- Space Complexity: O(k)
+
+Author: Michael Alexander Montoya
+"""
+
+import random
+
+def reservoir_sampling(stream, k):
+    """
+    Performs reservoir sampling on a stream of items.
+
+    Args:
+        stream: An iterable data stream.
+        k: Number of items to sample.
+
+    Returns:
+        A list containing k randomly sampled items from the stream.
+    """
+
+    reservoir = []
+
+    for i, item in enumerate(stream):
+        if i < k:
+            reservoir.append(item)
+        else:
+            j = random.randint(0, i)
+            if j < k:
+                reservoir[j] = item
+
+    return reservoir
+
+
+# Example usage
+if __name__ == "__main__":
+    stream_data = range(1, 1001)  # Simulate a stream of numbers from 1 to 1000
+    sample_size = 10
+
+    sample = reservoir_sampling(stream_data, sample_size)
+    print(f"Random sample of {sample_size} items from stream: {sample}")