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Heaps and prority queus In python

15/10/2020 Client: murali Deadline: 7 Days

You have been provided a Python file, heap.py, which constructs a heap structure with a list. Using that code as a guide:


Develop a heap data structure using a linked structure (Nodes and Pointers)


The heap must support add and remove from the heap


All operations most abide by the rules that govern a heap (see lecture slides for reference)


Once you have your heap structure created, next you must use it as a backing structure to a priority queue.


Develop a priority queue data structure that is backed by a heap (linked structure NOT A LIST)


Implement the normal methods that accompany a priority queue structure


Enqueue, dequeue, and peek by priority not position


Also length and whether or not the structure is empty (is_empty)


Perform the following operations to showcase your working structure


Enqueue the following items: 4, 7, 5, 11, 8, 6, 9


Dequeue 3 items by priority, they should be 4, 5, & 6.






related heap.py file code is below




class Heap:


    def __init__(self):


        self.heap = [0]


        self.size = 0




    def float(self, k):


        while k // 2 > 0:


            if self.heap[k] < self.heap[k//2]:


                self.heap[k], self.heap[k//2] = self.heap[k//2], self.heap[k]


            k //= 2




    def insert(self, item):


        self.heap.append(item)


        self.size += 1


        self.float(self.size)




    def sink(self, k):


        while k * 2 <= self.size:


            mc = self.minchild(k)


            if self.heap[k] > self.heap[mc]:


                self.heap[k], self.heap[mc] = self.heap[mc], self.heap[k]


            k = mc




    def minchild(self, k):


        if k * 2 + 1 > self.size:


            return k * 2


        elif self.heap[k*2] < self.heap[k*2+1]:


            return k * 2


        else:


            return k * 2 + 1




    def pop(self):


        item = self.heap[1]


        self.heap[1] = self.heap[self.size]


        self.size -= 1


        self.heap.pop()


        self.sink(1)


        return item




h = Heap()


for i in (4, 8, 7, 2, 9, 10, 5, 1, 3, 6):


    h.insert(i)




print(h.heap)




for i in range(10):


    n = h.pop()


    print(n)


    print(h.heap)

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