Daily Leetcode Challenge | NOV 14 | Minimized Maximum of Products Distributed to Any Store

Daily Leetcode Challenge- November 2024 - Day 14 - Minimized Maximum of Products Distributed to Any Store
Approach/Topic : Greedy
question link: leetcode.com/p...
optimized approach beats 90% of the test cases
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[@darshankumar5546]

Hindi Explanation here: ua-cam.com/video/MzMSfD6vhTU/v-deo.html

[@darshankumar5546]

import heapq
class Solution:
def minimizedMaximum(self, n: int, quantities: List[int]) -> int:
m=len(quantities)
minHeap=[]
for i in quantities: # O(m)
minHeap.append((-i,i,1)) # avg quantity per store , total quantity,#no of stores

heapq.heapify(minHeap) # O(m)
print(minHeap)
print('n-m =',n-m)
#O((n-m)logm)
for i in range(n-m): #O(n-m)
_,totalQuantity,totalStores=heapq.heappop(minHeap) #O(logm)
totalStores+=1
avg=(totalQuantity/totalStores)
heapq.heappush(minHeap,(-avg,totalQuantity,totalStores)) #O(logm)
print(minHeap)
avg,_,_=heapq.heappop(minHeap)
avg=avg*(-1)

return ceil(avg)