Top k error codes
A log pipeline collects error codes from a web service in the order they occurred. Given that ordered list and an integer k, return the k codes that occurred most often, highest count first. When two codes have equal counts, the one whose first occurrence came earlier in the log wins the earlier spot. Assume 1 <= k <= number of distinct codes. Example: codes = ["504", "500", "504", "500", "404"], k = 2 gives ["504", "500"] — both occur twice, and "504" appeared first.
Implement
frequent_error_codes(codes: list[str], k: int) → list[str]Examples
in
[["504","500","504","500","404"],2]out["504","500"]What a strong answer looks like
State your approach and its time/space complexity out loud before you optimize. Handle the edge cases (empty input, duplicates, overflow), and say why you chose this over the brute force. Green tests are the floor, not the grade.
0:00 of about 15 min
solution.py
InputExpectedGot
[["504","500","504","500","404"],2]["504","500"]not run yetsample