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Effectively fetch the smallest element in a heap of Python

 1 year ago
source link: https://donghao.org/2023/02/24/effectively-fetch-the-smallest-element-in-a-heap-of-python/
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Effectively fetch the smallest element in a heap of Python

To solve Leetcode #1675, I wrote the below code with the help of hints:

import sys
import heapq

class Solution:
    def minimumDeviation(self, nums: List[int]) -> int:
        n = len(nums)
        heapq.heapify(nums)
        _max = max(nums)
        ans = max(nums) - min(nums)
        while True:
            item = heapq.heappop(nums)
            if item % 2 == 1:
                heapq.heappush(nums, item * 2)
                _max = max(_max, item * 2)
                ans = min(ans, _max - heapq.nsmallest(1, nums)[0])
            else:
                heapq.heappush(nums, item)
                break
        print("stage1:", nums)
        nums = [-item for item in nums]
        heapq.heapify(nums)
        _max = max(nums)
        while True:
            item = heapq.heappop(nums)
            if item % 2 == 0:
                heapq.heappush(nums, item // 2)
                _max = max(_max, item // 2)
                ans = min(ans, _max - heapq.nsmallest(1, nums)[0])
            else:
                break
                
        return ans      
Python
import sys
import heapq
class Solution:
    def minimumDeviation(self, nums: List[int]) -> int:
        n = len(nums)
        heapq.heapify(nums)
        _max = max(nums)
        ans = max(nums) - min(nums)
        while True:
            item = heapq.heappop(nums)
            if item % 2 == 1:
                heapq.heappush(nums, item * 2)
                _max = max(_max, item * 2)
                ans = min(ans, _max - heapq.nsmallest(1, nums)[0])
            else:
                heapq.heappush(nums, item)
                break
        print("stage1:", nums)
        nums = [-item for item in nums]
        heapq.heapify(nums)
        _max = max(nums)
        while True:
            item = heapq.heappop(nums)
            if item % 2 == 0:
                heapq.heappush(nums, item // 2)
                _max = max(_max, item // 2)
                ans = min(ans, _max - heapq.nsmallest(1, nums)[0])
            else:
                break
        return ans      

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