Return super(OrderedList, self)._getitem_(i) Return super(OrderedList, self).pop(i)įor x in super(OrderedList, self)._iter_(): Super(OrderedList, self).insert(i, (self.key(x), x)) Super(OrderedList, self).append((self.key(x), x)) pop(0)ĭef _init_(self, iterable=None, key=None): If you want MinQueue like functionality use positive values. If you want MaxQueue like functionality use negative values. """Keep a list sorted as you append or extend itĪn ordered list, this sorts items from smallest to largest using key, so If you want to keep an entire list ordered, not just the top value, I've used some variation of this code in multiple projects, it's a drop in replacement for the standard list class with a similar api: import bisect Obviously, calling put will (and should!) raise an error if you try to insert an object which your key-function cannot process. Python 3 code from queue import PriorityQueue PriorityQueue.put(self, (self.key(x), x)) Python 2 code from Queue import PriorityQueue You won't have to insert (priority, object) tuples manually and the handling feels more natural.ĭemo of the desired behavior: > h = KeyHeap(sum) If you want inserted objects to be prioritized by a specific rule, I found it very helpful to write a simple subclass of PriorityQueue which accepts a key-function. I can either use a (priority, object) as Charlie Martin suggests, or just implement _cmp_ for my object. """Add ``item`` to the queue if doesn't already exist.""" """Remove and return the smallest item from the queue.""" """Check if ``item`` exists in the queue.""" The data structure will be created in O(N). Items (list): An initial item list - it can be unsorted and Want to use the data structure for custom objects. Python's built-in objects, but you should implement those methods if you Important: the items of this data structure must be both comparable and Provides O(1) membership test, O(log N) insertion and O(log N) The result should be quite efficient for all operators: class PriorityQueueSet(object):Ĭombined priority queue and set data structure.Īcts like a priority queue, except that its items are guaranteed to be Extract-Max/Min from the Priority QueueĮxtract-Max returns the node with maximum value after removing it from a Max Heap whereas Extract-Min returns the node with minimum value after removing it from Min Heap.I ended up implementing a wrapper for heapq, adding a dict for maintaining the queue's elements unique. Peek operation returns the maximum element from Max Heap or minimum element from Min Heap without deleting the node.Ĥ. Peeking from the Priority Queue (Find max/min) Deleting an Element from the Priority Queueĭeleting an element from a priority queue (max-heap) is done as follows:Īlgorithm for deletion of an element in the priority queue (max-heap)Įlse swap nodeToBeDeleted with the lastLeafNodeįor Min Heap, the above algorithm is modified so that the both childNodes are smaller than currentNode.ģ. Insert the newNode at the end (last node from left to right.)įor Min Heap, the above algorithm is modified so that parentNode is always smaller than newNode.Ģ. Insert an element at the end of the queueĪlgorithm for insertion of an element into priority queue (max-heap) Insert the new element at the end of the tree.Inserting an element into a priority queue (max-heap) is done by the following steps. Inserting an Element into the Priority Queue Among these data structures, heap data structure provides an efficient implementation of priority queues.īasic operations of a priority queue are inserting, removing, and peeking elements.īefore studying the priority queue, please refer to the heap data structure for a better understanding of binary heap as it is used to implement the priority queue in this article.ġ. Priority queue can be implemented using an array, a linked list, a heap data structure, or a binary search tree. The element with the highest priority is removed first. In a queue, the first-in-first-out rule is implemented whereas, in a priority queue, the values are removed on the basis of priority. Removing Highest Priority Elementĭifference between Priority Queue and Normal Queue We can also set priorities according to our needs. However, in other cases, we can assume the element with the lowest value as the highest priority element. The element with the highest value is considered the highest priority element. Generally, the value of the element itself is considered for assigning the priority. However, if elements with the same priority occur, they are served according to their order in the queue. That is, higher priority elements are served first. And, elements are served on the basis of their priority. Decrease Key and Delete Node Operations on a Fibonacci HeapĪ priority queue is a special type of queue in which each element is associated with a priority value.
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