Exponential Backoff API Retry | Dataford Interview Questions

Coding: implement an API call retry with exponential backoff (for LLM/API calls), with production follow-ups.

Asked in the Coding round stage. Listed in the creator's description of his Wipro Gen AI Engineer coding round.

Implement retry_api_call(outcomes, max_retries, base_delay). outcomes is an ordered list containing success, timeout, rate_limit, or bad_request. Retry only timeout and rate_limit. Return a dictionary with the final status, total attempts, and retry delays. The delay before retry number r, starting at zero, is base_delay * 2^r.

Constraints

1 <= len(outcomes) <= 100
0 <= max_retries <= 10
0 <= base_delay <= 10^6
Each outcome is one of: success, timeout, rate_limit, bad_request
The outcomes list contains enough entries for every permitted attempt

Function Signature

def retry_api_call(outcomes, max_retries, base_delay):

Whenever you're ready, walk me through your approach or go straight to the code. The requirements are in the Question tab.

Problem

Coding: implement an API call retry with exponential backoff (for LLM/API calls), with production follow-ups.

Asked in the Coding round stage. Listed in the creator's description of his Wipro Gen AI Engineer coding round.

Constraints

1 <= len(outcomes) <= 100
0 <= max_retries <= 10
0 <= base_delay <= 10^6
Each outcome is one of: success, timeout, rate_limit, bad_request
The outcomes list contains enough entries for every permitted attempt

Function Signature

def retry_api_call(outcomes, max_retries, base_delay):

Whenever you're ready, walk me through your approach or go straight to the code. The requirements are in the Question tab.