Runtime: 209 ms (87.19%), Memory: 18.9 MB (71.55%) - Gitcode

Author: vinija

1052-grumpy-bookstore-owner/1052. Grumpy Bookstore Owner.py

@@ -0,0 +1,41 @@
+from typing import List
+
+class Solution:
+    def maxSatisfied(self, customers: List[int], grumpy: List[int], minutes: int) -> int:
+        # Initial satisfied customers count
+        satisfied_customers = 0
+        # Additional satisfied customers due to using the technique
+        additional_satisfied = 0
+        # Maximum additional satisfied customers we can get
+        max_additional_satisfied = 0
+
+        n = len(customers)
+
+        # Calculate the initial satisfied customers and the first window's additional satisfied
+        for i in range(n):
+            if grumpy[i] == 0:
+                satisfied_customers += customers[i]
+            else:
+                if i < minutes:
+                    additional_satisfied += customers[i]
+
+        # Set max_additional_satisfied to the first window's additional satisfied customers
+        max_additional_satisfied = additional_satisfied
+
+        # Sliding window to find the optimal additional satisfied customers
+        for i in range(minutes, n):
+            if grumpy[i] == 1:
+                additional_satisfied += customers[i]
+            if grumpy[i - minutes] == 1:
+                additional_satisfied -= customers[i - minutes]
+
+            max_additional_satisfied = max(max_additional_satisfied, additional_satisfied)
+
+        # The total maximum satisfied customers is the sum of initially satisfied customers
+        # and the maximum additional satisfied customers from the optimal window
+        return satisfied_customers + max_additional_satisfied
+
+# Example usage:
+solution = Solution()
+print(solution.maxSatisfied([1, 0, 1, 2, 1, 1, 7, 5], [0, 1, 0, 1, 0, 1, 0, 1], 3))  # Output: 16
+print(solution.maxSatisfied([1], [0], 1))  # Output: 1