![]() Resolving equal priorities and order stability We'll use priority queue this way in our next example. If we want to reverse this, we can simply use the negative of the priority value when adding elements to the queue.Īs a more robust solution, we can wrap our queue items in a custom class with overloaded comparison operators implemented to give us the desired ordering. That means the smallest priority value always comes out first. Technically, PriorityQueue is implemented using a min-heap data structure. That is priority 0 is higher than priority 1. Note that by default, the lower the value of the priority number, the higher the priority of the entry. ![]() Print('Getting items from the priority queue') # They will be printed in the order of their priority # Let's get items from the priority queue one by one # We add items to priority queue in the order they're listed Items = įor item, priority in zip(items, priorities): Here's a dummy example of how to use it: import random In the simplest case, an entry in the priority queue will be a tuple (priority_number, data). Python comes with a built-in PriorityQueue class, contained in the queue module. Priority queue in Python? Short answer: use queue.PriorityQueue ![]() ![]() A queue is a first in, first out (FIFO) data structure, whereas in a priority queue the element with the highest priority is served before lower priority elements. Priority queue is a data structure similar to a queue, but where each element has an associated priority. ![]()
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