Assume all the elements are in a range of 0 999 from queue import PriorityQueue q PriorityQueue. Another option is to use an array to keep track of the elements in the priority queue. The heapq module is efficient and easy to use, making it a popular choice for implementing priority queues and other data structures in Python. Priority queue is not iterable, so you have to pop out all the elements and then push them back to see if an element is inside. If maxsize is less than or equal to zero, the queue size is infinite. Insertion will block once this size has been reached, until queue items are consumed. ![]() Note that the heapq module in Python provides functions for performing heap operations on lists in-place, without creating a separate data structure for the heap. maxsize is an integer that sets the upperbound limit on the number of items that can be placed in the queue. This program creates a heap queue using the heapq module in Python and performs various operations such as converting a list into a heap, adding a new value to the heap, removing the smallest element from the heap, getting the n smallest and n largest elements from the heap.
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