Deadline-Prioritized Task Consumption | Dataford Interview Questions

How would you implement a consumeTask function using a heap to prioritize deadlines in a task scheduler?

Implement consumeTask(tasks) using Python's heapq. Each task is a dictionary with an integer deadline and an id. Return task IDs in ascending deadline order. If deadlines are equal, preserve the tasks' original input order.

The input is a list of task dictionaries, and the output is a list of task IDs.

Constraints

0 <= tasks.length <= 1000
Each task contains a unique string id and an integer deadline
Deadlines may be negative, zero, or positive
All task IDs are returned exactly once

Function Signature

def consumeTask(tasks):

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Problem

How would you implement a consumeTask function using a heap to prioritize deadlines in a task scheduler?

The input is a list of task dictionaries, and the output is a list of task IDs.

Constraints

0 <= tasks.length <= 1000
Each task contains a unique string id and an integer deadline
Deadlines may be negative, zero, or positive
All task IDs are returned exactly once

Function Signature

def consumeTask(tasks):

Your question is Deadline-Prioritized Task Consumption. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.