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# Implements a min-heap. For max-heap, simply reverse all comparison orders.
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#
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# Note on alternate subroutine namings (used in some textbooks):
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# - _bubble_up = siftdown
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# - _bubble_down = siftup
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def _bubble_up(heap, i):
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while i > 0:
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parent_i = (i - 1) // 2
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if heap[i] < heap[parent_i]:
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heap[i], heap[parent_i] = heap[parent_i], heap[i]
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i = parent_i
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continue
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break
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def _bubble_down(heap, i):
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startpos = i
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newitem = heap[i]
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left_i = 2 * i + 1
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while left_i < len(heap):
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# Pick the smaller of the L and R children
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right_i = left_i + 1
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if right_i < len(heap) and not heap[left_i] < heap[right_i]:
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child_i = right_i
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else:
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child_i = left_i
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# Break if heap invariant satisfied
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if heap[i] < heap[child_i]:
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break
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# Move the smaller child up.
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heap[i], heap[child_i] = heap[child_i], heap[i]
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i = child_i
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left_i = 2 * i + 1
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def heapify(lst):
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for i in reversed(range(len(lst) // 2)):
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_bubble_down(lst, i)
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def heappush(heap, item):
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heap.append(item)
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_bubble_up(heap, len(heap) - 1)
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def heappop(heap):
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if len(heap) == 1:
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return heap.pop()
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min_value = heap[0]
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heap[0] = heap[-1]
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del heap[-1]
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_bubble_down(heap, 0)
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return min_value
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