Space-efficient: Heap queues are space-efficient, as they store elements in an array-based representation, minimizing the overhead associated with node-based data structures like linked lists.It provides logarithmic time complexity for many operations, making it a popular choice for many applications. Efficient: A heap queue is a highly efficient data structure for managing priority queues and heaps in Python.Advantages of using a heap queue (or heapq) in Python: The heapq module is efficient and easy to use, making it a popular choice for implementing priority queues and other data structures in Python. 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. 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. Software Engineering Interview Questions.Top 10 System Design Interview Questions and Answers.Top 20 Puzzles Commonly Asked During SDE Interviews.Commonly Asked Data Structure Interview Questions.Top 10 algorithms in Interview Questions.Top 20 Dynamic Programming Interview Questions.Top 20 Hashing Technique based Interview Questions. Top 50 Dynamic Programming (DP) Problems.Top 20 Greedy Algorithms Interview Questions.Top 100 DSA Interview Questions Topic-wise.Once a task.interrupt is serviced, it is popped out from heap queue.The task/interrupt with the highest priority will be serviced first and it is always the first element in the queue.The interrupts are pushed into the priority queue preserving the min-heap property.The interrupts along with their priorities approach the scheduler.The tasks are serviced and while in progress, just a message gets printed as an execution log stating which task is in progress.All the tasks are in a priority queue and are maintained with the min-heap property.The element that has ‘1’ as priority is considered to be the most important task. The tasks to be executed are assigned with priorities.To implement this the heapq module is used. If the interrupt has a higher priority, it is executed first otherwise, once all the jobs are completed, the interrupt will be serviced. So the scheduler has to decide whether to execute the interrupt or the existing task. Apart from the tasks, there will be interrupts approaching the scheduler. The priority queue is used by the scheduler to decide which task has to be performed. Now let us implement a simple scheduler that assigns the jobs to the processor.
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