Refactor sliding_window_maximum function signature

Updated type hints and parameter names for clarity.

Author: MahyudeenShahid

data_structures/arrays/sliding_window_maximum.py

@@ -1,47 +1,49 @@
 from collections import deque
-from typing import List
 
 
-def sliding_window_maximum(nums: List[int], k: int) -> List[int]:
+def sliding_window_maximum(nums: list[int], window_size: int) -> list[int]:
     """
-    Return a list of the maximum values in each sliding window of size k.
-
+    Return a list of the maximum values in each sliding window of the given size.
     This algorithm runs in O(n) time using a deque to keep track of useful elements.
 
     Parameters
     ----------
-    nums : List[int]
+    nums : list[int]
         The input list of integers.
-    k : int
-        The window size.
+    window_size : int
+        The size of the sliding window.
 
     Returns
     -------
-    List[int]
+    list[int]
         A list containing the maximum of each sliding window.
 
     Examples
     --------
-    >>> sliding_window_maximum([1,3,-1,-3,5,3,6,7], 3)
+    >>> sliding_window_maximum([1, 3, -1, -3, 5, 3, 6, 7], 3)
     [3, 3, 5, 5, 6, 7]
     >>> sliding_window_maximum([9, 11], 2)
     [11]
     >>> sliding_window_maximum([4, -2], 1)
     [4, -2]
     >>> sliding_window_maximum([], 3)
     []
-    >>> sliding_window_maximum([1,2,3], 0)
+    >>> sliding_window_maximum([1, 2, 3], 0)
     []
+
+    Reference
+    ---------
+    https://en.wikipedia.org/wiki/Sliding_window_protocol
     """
-    if not nums or k <= 0:
+    if not nums or window_size <= 0:
         return []
 
     dq: deque[int] = deque()
-    result: List[int] = []
+    result: list[int] = []
 
     for i, num in enumerate(nums):
         # Remove indices that are out of the current window
-        while dq and dq[0] <= i - k:
+        while dq and dq[0] <= i - window_size:
             dq.popleft()
 
         # Remove smaller values as they are not useful
@@ -50,8 +52,8 @@ def sliding_window_maximum(nums: List[int], k: int) -> List[int]:
 
         dq.append(i)
 
-        # Add the current max to the result once the window is of size k
-        if i >= k - 1:
+        # Add the current max to the result once the window is of size window_size
+        if i >= window_size - 1:
             result.append(nums[dq[0]])
 
     return result