Heap Implementation for Python
Project description
It’s like heapq (i.e. blazingly fast) but it’s object-oriented and has more features.
Why?
Less code.
How?
Before:
import heapq
heap = [1234, 12]
heapq.heapify(heap)
heapq.heappush(heap, 55)
print(heapq.heappop(heap))After:
from xheap import Heap
heap = Heap([1234, 12])
heap.push(55)
print(heap.pop())Even more interesting: remove
Imagine a priority queue of tasks where tasks can be cancelled. Just call remove in this case.
heap = Heap([4, 3, 7, 6, 1, 2, 9, 8, 0, 5])
heap.remove(6)A heap is basically a list. So, if you know the index, you can use pop instead.
heap = Heap([4, 3, 7, 6, 1, 2, 9, 8, 0, 5])
heap.pop(3)Max-Heap or Min-Heap?
You define the order of items. Just imagine two heaps of the very same set of items but you need different sorting for each heap. So, you define what min and max means, via cmp.
items = [date(2015, 1, 1), date(2015, 1, 2), date(2015, 1, 3)]
order1 = Heap(items, cmp=lambda x, y: x.day <= y.day)
order2 = Heap(items, cmp=lambda x, y: x.weekday() >= y.weekday())Checking Heap Invariant
If you tinker with a heap you can check whether the heap invariant still holds:
heap = Heap([4, 3, 7, 6, 1, 2, 9, 8, 5])
heap[3] = 10 # I know what I am doing here
heap.check_invariant() # but better check... ooopsConclusion
Good
object-oriented
can remove items from within the heap
can remove items with unknown index
sorting defined per heap (falls back to Pythonic <=)
works with Python2 and Python3
Bad
no drawbacks discovered so far ;)
needs fix:
decrease-key and increase-key seem to be another important missing use-case of heapq; so, I will dig into that as well
merge heaps
ideas are welcome :-)
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
