Exercise 4: Task Scheduler ⏰

The Scenario

You're building a task scheduler for a game server. Tasks arrive with a priority number — the lower the number, the more urgent the task.

Your job: process all tasks in priority order!

Your Task

Write a function process_tasks(tasks) that:

Takes a list of (priority, task_name) tuples
Returns a list of task names in the order they should be processed (lowest priority number first)
If two tasks have the same priority, either order is fine

Use heapq!

Examples

tasks = [(3, "Email"), (1, "Fire"), (2, "Meeting"), (1, "Crash")]
print(process_tasks(tasks))
# Output: ["Crash", "Fire", "Meeting", "Email"]
# (or ["Fire", "Crash", ...] — both priority-1 tasks can go first)

tasks2 = [(5, "Cleanup"), (1, "Critical Bug"), (3, "Feature")]
print(process_tasks(tasks2))
# Output: ["Critical Bug", "Feature", "Cleanup"]

Starter Code

import heapq

def process_tasks(tasks):
    # Your code here
    pass

# Test your function:
tasks = [(3, "Email"), (1, "Fire"), (2, "Meeting"), (1, "Crash")]
print(process_tasks(tasks))
# Output: ["Crash", "Fire", "Meeting", "Email"]

tasks2 = [(5, "Cleanup"), (1, "Critical Bug"), (3, "Feature")]
print(process_tasks(tasks2))
# Output: ["Critical Bug", "Feature", "Cleanup"]

Hints

💡 Hint 1

When you push a tuple into a heap, Python compares by the first element (priority number). That's exactly what we want!

💡 Hint 2

Push all (priority, name) tuples into a heap
Pop them one by one — they come out in priority order
Collect just the task names

✅ Solution

import heapq

def process_tasks(tasks):
    heap = []
    for priority, name in tasks:
        heapq.heappush(heap, (priority, name))
    
    result = []
    while heap:
        priority, name = heapq.heappop(heap)
        result.append(name)
    return result

Why this works: Tuples are compared element-by-element. Since priority is first, the heap sorts by priority automatically. Lower numbers = higher urgency = popped first!

Bonus Challenge 🌟

What if you want higher priority numbers to go first? (e.g., priority 5 is more urgent than priority 1)

Modify your function to handle this. (Hint: negate trick again!)

tasks = [(3, "Email"), (5, "Fire"), (2, "Meeting")]
print(process_tasks_max(tasks))
# Output: ["Fire", "Email", "Meeting"]

Task Scheduler