Priority queue concept in Data Structures Theory - Mini Project: Build & Apply

Understanding Priority Queue Concept

📖 Scenario: Imagine you are organizing a hospital emergency room. Patients arrive with different levels of urgency. You want to manage the order in which patients are treated so that the most urgent cases are handled first.

🎯 Goal: Build a simple representation of a priority queue that stores patients with their urgency levels and shows how to select the patient with the highest priority.

📋 What You'll Learn

Create a data structure to hold patients and their urgency levels

Add a variable to track the highest urgency level

Implement logic to find the patient with the highest urgency

Complete the structure to represent the priority queue concept clearly

💡 Why This Matters

🌍 Real World

Priority queues are used in hospitals, task scheduling, and anywhere urgent items must be handled first.

💼 Career

Understanding priority queues is important for roles in software development, operations, and systems design where task prioritization is key.

1

Create the initial patient list

Create a dictionary called patients with these exact entries: 'Alice': 3, 'Bob': 5, 'Charlie': 2, where the numbers represent urgency levels.

Data Structures Theory

# Create the patients dictionary with urgency levels
# Your code here

Need a hint?

Use a dictionary with patient names as keys and urgency levels as values.

2

Add a variable for highest urgency

Create a variable called highest_urgency and set it to 0 to track the highest urgency level.

Data Structures Theory

patients = {'Alice': 3, 'Bob': 5, 'Charlie': 2}
# Create highest_urgency variable
# Your code here

Need a hint?

Start with 0 because urgency levels are positive numbers.

3

Find the patient with the highest urgency

Use a for loop with variables patient and urgency to iterate over patients.items(). Inside the loop, update highest_urgency if urgency is greater.

Data Structures Theory

patients = {'Alice': 3, 'Bob': 5, 'Charlie': 2}
highest_urgency = 0
# Loop through patients to find highest urgency
# Your code here

Need a hint?

Compare each urgency to the current highest and update if bigger.

4

Complete the priority queue concept

Create a list called priority_queue that contains tuples of patient names and urgencies sorted by urgency in descending order.

Data Structures Theory

patients = {'Alice': 3, 'Bob': 5, 'Charlie': 2}
highest_urgency = 0
for patient, urgency in patients.items():
    if urgency > highest_urgency:
        highest_urgency = urgency
# Create priority_queue sorted by urgency descending
# Your code here

Need a hint?

Use the sorted() function with a key to sort by urgency descending.