Unit Tests for Predictive APIs | Dataford Interview Questions

How do you structure unit tests for an API that serves predictive models? For this coding exercise, implement a validator that identifies failed test cases by checking HTTP status, required response fields, nested JSON values, and numeric values within a tolerance. Use def find_prediction_test_failures(cases, tolerance):; return the zero-based indices of failed cases.

Constraints

1 <= len(cases) <= 10^4
Each response body contains JSON-compatible values: dictionaries, lists, strings, numbers, booleans, or null
Nested response depth is at most 100
0 <= tolerance <= 1
Expected dictionary fields must exist in the actual response, but extra actual fields are allowed
List values must have the same length and order

Function Signature

def find_prediction_test_failures(cases, tolerance):

Your question is Unit Tests for Predictive APIs. 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

Constraints

1 <= len(cases) <= 10^4
Each response body contains JSON-compatible values: dictionaries, lists, strings, numbers, booleans, or null
Nested response depth is at most 100
0 <= tolerance <= 1
Expected dictionary fields must exist in the actual response, but extra actual fields are allowed
List values must have the same length and order

Function Signature

def find_prediction_test_failures(cases, tolerance):

Your question is Unit Tests for Predictive APIs. 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.