Parsing Logs for Error Counts | Dataford Interview Questions

Write a Python function to parse a log file and return a dictionary of error counts by hour.

Implement parse_error_counts(log_lines), where log_lines is a list of strings formatted as YYYY-MM-DD HH:MM:SS LEVEL message; count only entries whose level is ERROR. Return a dictionary keyed by YYYY-MM-DD HH, and ignore malformed lines. For example, two errors during 2026-01-15 09 produce {"2026-01-15 09": 2}.

Constraints

0 <= len(log_lines) <= 100000
Each valid line uses the format YYYY-MM-DD HH:MM:SS LEVEL message
LEVEL is a whitespace-delimited token
Only LEVEL == ERROR is counted
Malformed lines must be ignored

Function Signature

def parse_error_counts(log_lines):

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Problem

Write a Python function to parse a log file and return a dictionary of error counts by hour.

Constraints

0 <= len(log_lines) <= 100000
Each valid line uses the format YYYY-MM-DD HH:MM:SS LEVEL message
LEVEL is a whitespace-delimited token
Only LEVEL == ERROR is counted
Malformed lines must be ignored

Function Signature

def parse_error_counts(log_lines):

Your question is Parsing Logs for Error Counts. 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.