Prioritize Your Data Journey: Python's Priority Queue Perfection!

Priority queue use case.


In computer science and programming, a priority queue is an abstract data structure similar to a regular queue in which each item additionally has a "priority" assigned to it. In a priority queue, an element with high priority is selected/served before low priority element. If items with the same priority occur, they are selected/served according to their queue order.

Priority Queue Data Structure.
Priority Queue meme.

Python Knowledge Base: Make coding great again.
- Updated: 2024-12-20 by Andrey BRATUS, Senior Data Analyst.




    The FIFO rule is applied in a normal queue, the values are removed on the basis of priority in a priority queue. Usually the value of the element is considered for assigning the priority, the item with the highest value is asigned the highest priority. In some cases, we assign the highest priority to the element with the lowest value.


  1. Priority Queue Data Structure Python code.



  2. 
    class PriorityQueue(object):
        def __init__(self):
            self.queue = []
     
        def __str__(self):
            return ' '.join([str(i) for i in self.queue])
     
        # check if the queue is empty
        def isEmpty(self):
            return len(self.queue) == 0
     
        # inserting an element
        def insert(self, data):
            self.queue.append(data)
     
        # popping an element
        def delete(self):
            try:
                max_val = 0
                for i in range(len(self.queue)):
                    if self.queue[i] > self.queue[max_val]:
                        max_val = i
                item = self.queue[max_val]
                del self.queue[max_val]
                return item
            except IndexError:
                print()
                exit()
     
    
    theQueue = PriorityQueue()
    theQueue.insert(1)
    theQueue.insert(11)
    theQueue.insert(13)
    theQueue.insert(3)
    theQueue.insert(5)
    theQueue.insert(25)
    print ("Original queue: ")
    print(theQueue)
    print ("Removing 3 elements one-by-one: ")
    theQueue.delete()
    print(theQueue)
    theQueue.delete()
    print(theQueue)
    theQueue.delete()
    print(theQueue)
    
  3. Priority Queue Data Structure Python code result.


  4. OUT:
    Original queue:
    1 11 13 3 5 25
    Removing 3 elements one-by-one:
    1 11 13 3 5
    1 11 3 5
    1 3 5





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