Priority Queue Introduction and Concept in DSA Python - Practice Problems & Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this priority queue insertion sequence?

Consider a min-priority queue implemented using a heap. Insert the elements 5, 3, 6, 2 in this order. What is the state of the heap array after all insertions?

DSA Python

import heapq
pq = []
heapq.heappush(pq, 5)
heapq.heappush(pq, 3)
heapq.heappush(pq, 6)
heapq.heappush(pq, 2)
print(pq)

A [2, 3, 6, 5]

B [3, 2, 6, 5]

C [2, 3, 5, 6]

D [5, 3, 6, 2]

💡 Hint

Remember that heapq in Python maintains the smallest element at index 0.

The heap after inserting 5, 3, 6, 2 will reorder to keep the smallest element at the root. The final heap array is [2, 3, 6, 5].

🧠 Conceptual

intermediate

Which operation does NOT belong to a priority queue?

Select the operation that is NOT typically supported by a priority queue.

A Insert an element with a priority

B Extract the element with the highest priority

C Peek at the element with the highest priority without removing it

D Search for an element by value

💡 Hint

Priority queues focus on priority-based access, not searching by value.

Priority queues do not support searching for elements by value efficiently; they focus on insertion and extracting the highest priority element.

🔧 Debug

advanced

What error does this priority queue code raise?

Identify the error raised by this code snippet using Python's heapq module.

DSA Python

import heapq
pq = []
heapq.heappush(pq, 10)
heapq.heappop(pq)
heapq.heappop(pq)

A IndexError: index out of range

B KeyError: key not found

C TypeError: unsupported operand type(s)

D No error, returns None

💡 Hint

Consider what happens when popping from an empty heap.

After popping the only element, the next pop tries to remove from an empty list, causing IndexError.

🚀 Application

advanced

What is the output after these priority queue operations?

Given a max-priority queue implemented by negating values in a min-heap, what is the output after these operations? Operations: Insert 4, Insert 7, Insert 1, Extract max, Insert 5 Print the remaining heap array (negated back to positive values).

DSA Python

import heapq
pq = []
heapq.heappush(pq, -4)
heapq.heappush(pq, -7)
heapq.heappush(pq, -1)
max_val = -heapq.heappop(pq)
heapq.heappush(pq, -5)
result = [-x for x in pq]
print(sorted(result))

A [1, 5, 7]

B [4, 5, 7]

C [1, 4, 5]

D [1, 4, 7]

💡 Hint

Remember to negate values back to positive and sort to visualize the heap contents.

After extracting max (7), the heap contains 4, 1, and after inserting 5, the heap has 1, 4, 5.

🧠 Conceptual

expert

Which data structure property is essential for a priority queue implemented as a heap?

Select the property that must always hold true in a heap-based priority queue.

A Balanced AVL tree property

B Complete binary tree property

C Linked list ordering property

D Binary search tree property

💡 Hint

Heaps are stored as arrays and must be complete binary trees.

A heap must be a complete binary tree to maintain efficient insertion and extraction operations.