To make it more fair, we also want the queue to be stable with respect to the insertion order - if two or more customers with the same priority are in the queue, we must serve them in the order of arrival. We'll use it to reveal two important problems with our tuple-based solution from the previous section.Īssume we have a customer support center, and we want to implement a queueing policy that prioritizes requests from older customers (those who signed up for our service earlier). 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. Due to the length of the class, I am going to divide it into sections.Priority queue is a data structure similar to a queue, but where each element has an associated priority. The following source code shows how to implement a priority queue with a min-heap (class HeapPriorityQueue in the GitHub repository). Source Code for Priority Queue with Min-Heap The sift up and sift down operations may seem complex, but we can implement them both in 10 lines of Java code or less. The first element to be inserted becomes the root node of the tree in the array, we place it at the first position: 1 st Element – Inserting the 4 into an Empty Priority Queue I'll show the min-heap in its tree and array representations in each step. In the following examples, I will show you step by step how to fill a min-heap-based priority queue with the sample values shown above (4, 7, 3, 8, 2, 9, 6, 5, 1). The example in the following section demonstrates the two steps. Step 2 ensures that, at the end of the operation, each element is again less than its children. Step 1 sounds complicated, but in the array representation, it simply means that the new element is placed in the first free position of the array. As long as the parent node of the new element is less than the element itself (which would violate the min-heap rule), we swap the new node with its parent node.If the lowest level is complete, we append the node under the first node of the lowest level.If the lowest level of the tree is not complete, we insert the new element next to the last node of the lowest level.If the tree is empty, we insert the new element as the root.We insert the new element as the last element in the tree, i.e.:.To insert an element into a heap, we proceed as follows: That tells how the peek() operation has to work: it simply has to return the first element of the array.īut how is such a heap constructed? How do enqueue() and dequeue() work? Inserting into the Min-Heap: Sift Up OK, the smallest element is always on the left. Priority Queue Using a Min-Heap – The Algorithm The min-heap of the PriorityQueue created in the example is precisely the one I displayed at the beginning of the article. And if you look closely, you'll see that the numbers are in the same order as in the graphical array representation above. The output of the program is: priorityQueue = Code language: plaintext ( plaintext ) ( "priorityQueue = " + priorityQueue) Code language: Java ( java ) The following lines of code demonstrate this well: PriorityQueue priorityQueue = new PriorityQueue() What you see is the array representation of the min-heap underlying the PriorityQueue. This is why, when you print a Java PriorityQueue as a string, you see the smallest element on the left. In a min-heap, the smallest element is always at the top, i.e., in the array, it is always at the first position.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |