Thread-Safe Worker Queue With Retries | Dataford Interview Questions

Write a thread-safe worker queue in Python that processes tasks using Celery-like logic, handling graceful shutdowns and retries at Peregrine Technologies.

Implement process_tasks(tasks, worker_count, max_retries). Each task is a dictionary with a unique task_id and failures_before_success, which simulates how many attempts fail before success. Return results in input order, including each task ID, final status, and total attempts. Workers must use a thread-safe queue, retry failed tasks up to max_retries, wait for all queued work to finish, and then shut down cleanly.

Input values are valid and failures_before_success is nonnegative.

Constraints

0 <= tasks.length <= 1000
1 <= worker_count <= 100
0 <= max_retries <= 100
Each task_id is unique
Each failures_before_success value is a nonnegative integer
Results must preserve the input task order

Function Signature

def process_tasks(tasks, worker_count, max_retries):

Your question is Thread-Safe Worker Queue With Retries. 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.

Problem

Write a thread-safe worker queue in Python that processes tasks using Celery-like logic, handling graceful shutdowns and retries at Peregrine Technologies.

Input values are valid and failures_before_success is nonnegative.

Constraints

0 <= tasks.length <= 1000
1 <= worker_count <= 100
0 <= max_retries <= 100
Each task_id is unique
Each failures_before_success value is a nonnegative integer
Results must preserve the input task order

Function Signature

def process_tasks(tasks, worker_count, max_retries):

Your question is Thread-Safe Worker Queue With Retries. 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.