Frequent Error Patterns From Logs | Dataford Interview Questions

Quest Global service logs contain API request outcomes. Given a list of log records, identify the k most frequent error patterns efficiently. An error pattern is the pair (endpoint, status_code) for records whose status code is at least 400.

Return the patterns ordered by decreasing frequency. If two patterns have the same frequency, order them lexicographically by endpoint and then numerically by status code.

Formal Specification

Implement top_error_patterns(logs, k).

logs is a list of dictionaries. Each dictionary has an endpoint string and a status_code integer.
k is a positive integer.
Return a list of dictionaries, each containing endpoint, status_code, and count.
Return at most k patterns. If fewer than k distinct error patterns exist, return all of them.
Ignore records with status codes below 400.

Constraints

0 <= len(logs) <= 10^5
1 <= k <= 10^4
100 <= status_code <= 599
Endpoint strings contain at most 200 characters
Every log record contains endpoint and status_code

Function Signature

def top_error_patterns(logs, k):

Your question is Frequent Error Patterns From Logs. 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