PYTHON PRIORITY QUEUE UPDATE
PYTHON PRIORITY QUEUE CODE

'''Create destructive sorted iterator of priorityDictionary. For example, the following line must work even though the key/value pair at i will shortly be destroyed.Ĭlass d_priority_dict (priority_dict): # Pasted from :

PYTHON PRIORITY QUEUE CODE

BE's shortest path code requires that the destructive iterator does not destroy access via the current key until the very end of the current iteration (see ). Simple point but referring to the integration of Matteo's priority dict with Brian Eppstein's 'Dijkstra' shortest path implementation, I found that introducing BE's _iter_ () function from works well. Definition of the Node class in Priority Queues also has an extra field called priority, which stores the priority factor for each element of the Queue class Node: def init(self, val, priority): self.value val self.priority priority self.next None. Beware: this will destroy elements as they are returned. A Priority Queue in Python can be implemented by following these steps.

_rebuild_heap () def sorted_iter ( self ): '''Sorted iterator of the priority dictionary items. # We just rebuild the heap from scratch after passing to super.

PYTHON PRIORITY QUEUE UPDATE

_rebuild_heap () def setdefault ( self, key, val ): if key not in self : self = val return val return self def update ( self, * args, ** kwargs ): # Reimplementing dict.update is tricky - see e.g. _heap, ( val, key )) else : # When the heap grows larger than 2 * len(self), we rebuild it # from scratch to avoid wasting too much memory. _heap ) < 2 * len ( self ): heappush ( self. _heap v, k = heappop ( heap ) while k not in self or self != v : v, k = heappop ( heap ) del self return k def _setitem_ ( self, key, val ): # We are not going to remove the previous value from the heap, # since this would have a cost O(n). _heap v, k = heap while k not in self or self != v : heappop ( heap ) v, k = heap return k def pop_smallest ( self ): '''Return the item with the lowest priority and remove it. _heap ) def smallest ( self ): '''Return the item with the lowest priority. _rebuild_heap () def _rebuild_heap ( self ): self.

''' def _init_ ( self, * args, ** kwargs ): super ( priority_dict, self ). The 'sorted_iter' method provides a destructive sorted iterator. The advantage over a standard heapq-based priority queue is that priorities of items can be efficiently updated (amortized O(1)) using code as 'thedict = new_priority.' The 'smallest' method can be used to return the object with lowest priority, and 'pop_smallest' also removes it. Keys of the dictionary are items to be put into the queue, and values are their respective priorities. From heapq import heapify, heappush, heappop class priority_dict ( dict ): '''Dictionary that can be used as a priority queue.

Python priority queue