2012年10月5日 · In Python 2.X and 3.x, heaps are supported through an importable library, heapq. It supplies numerous functions to work with the heap data structure modelled in a Python list.

The heapq module maintains the heap invariant, which is not the same thing as maintaining the actual list object in sorted order. Quoting from the heapq documentation: Heaps are binary trees for which every parent node has a value less than or equal to any of its children. This implementation uses arrays for which heap[k] <= heap[2*k+1] and heap[k] <= heap[2*k+2] for …

2010年10月17日 · I wish to hold a heap of objects, not just numbers. They will have an integer attribute in them that the heap can sort by. The easiest way to use heaps in python is heapq, but how do I tell it to...

2010年3月23日 · Python includes the heapq module for min-heaps, but I need a max-heap. What should I use for a max-heap implementation in Python?

2012年4月18日 · This is specifically mentioned as the solution under Priority Queue Implementation in the heapq docs.

2013年1月27日 · How are variables and memory managed in Python? Does it have a stack and a heap and what algorithm is used to manage memory? Given this knowledge are there any recommendations on memory management ...

2013年2月10日 · heap = [(-value, key) for key,value in the_dict.items()] largest = heapq.nsmallest(10, heap) largest = [(key, -value) for value, key in largest] Note that since heapq implements only a min heap it's better to invert the values, so that bigger values become smaller. This solution will be slower for small sizes of the heap, for example ...

2014年8月15日 · How can I make such update? The basic steps for updating elements in the heap following the above logic would be: Check dictionary to get the index of the element you want to update (after checking that the element is in the dictionary + corresponding heap) Update the value in the heap Call heapq.heapify (heap) which runs in O (N).

2012年4月15日 · Python has heapq module which implements heap data structure and it supports some basic operations (push, pop). How to remove i-th element from the heap in O(log n)? Is it even possible with heapq...

2011年10月18日 · A more traditional solution is to store (priority, task) tuples on the heap: pq = [ ] heappush(pq, (10, task1)) heappush(pq, (5, task2)) heappush(pq, (15, task3)) priority, task = heappop(pq) This works fine as long as no two tasks have the same priority; otherwise, the tasks themselves are compared (which might not work at all in Python 3).