This structure enables the PriorityQueue to efficiently serve the element with the highest priority (lowest value). In a min-heap, the parent node is always less than or equal to its child nodes. Python’s PriorityQueue operates using a data structure known as a min-heap. Hence, the element with the lowest value (1 in this case) is removed first. This is a characteristic of Python’s PriorityQueue, where lower numeric values represent higher priority. The elements are removed from the queue in ascending order, not in the sequence they were added. When you run this code, the output will be: 1 Let’s look at a simple example of how to use PriorityQueue in Python: from queue import PriorityQueue This class helps us create a queue where elements are served based on their priority, making it a preferred choice for implementing Priority Queue in Python. Python’s queue module offers a variety of data structures, one of which is the PriorityQueue class. ![]() Therefore, an element with a priority of 1 will be dequeued before an element with a priority of 2. In Python’s PriorityQueue, lower numeric values indicate higher priority. ![]() This class implements the Priority Queue data structure, enabling us to handle and manipulate data efficiently and intuitively. Python offers a built-in PriorityQueue class in the queue module. Queue TypeĪ Guided Walkthrough to Using PriorityQueue So, an element that enters the queue later could leave earlier if its priority is higher. However, in a Priority Queue, this order is determined by the priority of the elements. So, how does a Priority Queue differ from a standard Queue? In a typical Queue, the first element to enter is the first to leave (FIFO – First In First Out).
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