Heap insertion (bubble up) in Data Structures Theory - Mini Project: Build & Apply

Heap insertion (bubble up)

📖 Scenario: Imagine you are managing a priority queue for tasks where the highest priority task should always be at the top. You will learn how to insert a new task into a max-heap and maintain the heap property by bubbling the new element up.

🎯 Goal: Build a simple max-heap insertion process that adds a new element to the heap and restores the heap order by bubbling the element up.

📋 What You'll Learn

Create a list called heap representing a max-heap with given values

Create a variable called new_value with the value to insert

Write a loop that bubbles the new_value up the heap to maintain max-heap property

Insert the new_value into the heap and complete the bubble up process

💡 Why This Matters

🌍 Real World

Heaps are used in priority queues, scheduling tasks, and algorithms like heapsort.

💼 Career

Understanding heap insertion is important for software engineers working with efficient data structures and algorithms.

1

Create the initial max-heap list

Create a list called heap with these exact values: [40, 30, 20, 15, 10, 5] representing a max-heap.

Data Structures Theory

# Create the max-heap list called heap
# Your code here

Need a hint?

Use square brackets to create a list and assign it to heap.

2

Set the new value to insert

Create a variable called new_value and set it to 35, the value to insert into the heap.

Data Structures Theory

heap = [40, 30, 20, 15, 10, 5]
# Create new_value variable and set it to 35
# Your code here

Need a hint?

Assign the number 35 to the variable new_value.

3

Bubble up the new value in the heap

Append new_value to the end of heap. Then use a while loop with variable index to bubble the new value up. Inside the loop, compare the new value with its parent and swap if the new value is greater. Use integer division // to find the parent index.

Data Structures Theory

heap = [40, 30, 20, 15, 10, 5]
new_value = 35
# Append new_value to heap and bubble it up
# Your code here

Need a hint?

Remember to stop bubbling up when the new value is not greater than its parent or when it reaches the root.

4

Complete the heap insertion

Ensure the final heap list maintains the max-heap property after insertion and bubbling up. The heap should now include new_value in the correct position.

Data Structures Theory

heap = [40, 30, 20, 15, 10, 5]
new_value = 35
heap.append(new_value)
index = len(heap) - 1
while index > 0:
    parent_index = (index - 1) // 2
    if heap[index] > heap[parent_index]:
        heap[index], heap[parent_index] = heap[parent_index], heap[index]
        index = parent_index
    else:
        break
# Finalize the heap insertion
# Your code here

Need a hint?

The heap list should be correctly updated with the new value in its proper place.