import heapq
myList = [9, 5, 4, 1, 3, 2]
heapq.heapify(myList) # turn myList into a Min Heap
print(myList) # => [1, 3, 2, 5, 9, 4]
print(myList[0]) # first value is always the smallest in the heap
heapq.heappush(myList, 10) # insert 10
x = heapq.heappop(myList) # pop and return smallest item
print(x) # => 1
#Negate all values to use Min Heap as Max Heap
myList = [9, 5, 4, 1, 3, 2]
myList = [-val for val in myList] # multiply by -1 to negate
heapq.heapify(myList)
x = heapq.heappop(myList)
print(-x) # => 9 (making sure to multiply by -1 again)
Heaps are binary trees for which every parent node has a value less than or equal to any of its children. Useful for accessing min/max value quickly. Time complexity: O(n) for heapify, O(log n) push and pop. See: Heapq
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