Update Solution.py

Author: samarthswami1016

solution/3100-3199/3139.Minimum Cost to Equalize Array/Solution.py

@@ -1,12 +1,16 @@
 class Solution:
     MOD = 10**9 + 7
+
     def solve(self, k):
         sumDifferences = k * len(self.nums) - self.sumNums
         ones = max(2 * (k - self.minNums) - sumDifferences, 0)
         if (sumDifferences - ones) & 1 != 0:
             ones += 1
         return ones * self.cost1 + ((sumDifferences - ones) // 2) * self.cost2
-    def minCostToEqualizeArray(self, nums: List[int], cost1: int, cost2: int) -> int:
+
+    def minCostToEqualizeArray(self, nums: list[int], cost1: int, cost2: int) -> int:
+        from bisect import bisect_left
+
         cost2 = min(2 * cost1, cost2)
         self.nums = nums
         self.minNums = min(nums)
@@ -16,6 +20,10 @@ def minCostToEqualizeArray(self, nums: List[int], cost1: int, cost2: int) -> int
         m = max(nums)
         sameParity = range(m, 10**18, 2)
         diffParity = range(m + 1, 10**18, 2)
-        i = bisect_left(sameParity, 0, key=lambda i: self.solve(i + 2) - self.solve(i))
-        j = bisect_left(diffParity, 0, key=lambda j: self.solve(j + 2) - self.solve(j))
+        i = bisect_left(
+            sameParity, 0, key=lambda i: self.solve(i + 2) - self.solve(i)
+        )
+        j = bisect_left(
+            diffParity, 0, key=lambda j: self.solve(j + 2) - self.solve(j)
+        )
         return min(self.solve(sameParity[i]), self.solve(diffParity[j])) % Solution.MOD