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_heapq

Heap queue algorithm (a.k.a. priority queue).

Heaps are arrays for which a[k] <= a[2*k+1] and a[k] <= a[2*k+2] for
all k, counting elements from 0.  For the sake of comparison,
non-existing elements are considered to be infinite.  The interesting
property of a heap is that a[0] is always its smallest element.

Usage:

heap = []            # creates an empty heap
heappush(heap, item) # pushes a new item on the heap
item = heappop(heap) # pops the smallest item from the heap
item = heap[0]       # smallest item on the heap without popping it
heapify(x)           # transforms list into a heap, in-place, in linear time
item = heapreplace(heap, item) # pops and returns smallest item, and adds
                               # new item; the heap size is unchanged

Our API differs from textbook heap algorithms as follows:

- We use 0-based indexing.  This makes the relationship between the
  index for a node and the indexes for its children slightly less
  obvious, but is more suitable since Python uses 0-based indexing.

- Our heappop() method returns the smallest item, not the largest.

These two make it possible to view the heap as a regular Python list
without surprises: heap[0] is the smallest item, and heap.sort()
maintains the heap invariant!

Functions

heapify

heapify(heap, /)

  Transform list into a heap, in-place, in O(len(heap)) time.

heappop

heappop(heap, /)

  Pop the smallest item off the heap, maintaining the heap invariant.

heappush

heappush(heap, item, /)

  Push item onto heap, maintaining the heap invariant.

heappushpop

heappushpop(heap, item, /)

  Push item on the heap, then pop and return the smallest item from the heap.

  The combined action runs more efficiently than heappush() followed by
  a separate call to heappop().

heapreplace

heapreplace(heap, item, /)

  Pop and return the current smallest value, and add the new item.

  This is more efficient than heappop() followed by heappush(), and can be
  more appropriate when using a fixed-size heap.  Note that the value
  returned may be larger than item!  That constrains reasonable uses of
  this routine unless written as part of a conditional replacement:

      if item > heap[0]:
          item = heapreplace(heap, item)