Parse Logs for Error Frequency | Dataford Interview Questions

Write a script to parse a large log file, extract error messages, and count their frequency at Rippling.

Implement count_error_messages(log_lines), where log_lines is an iterable of strings. Each valid line has the format TIMESTAMP LEVEL MESSAGE, separated by spaces. Count only lines whose level is exactly ERROR, using the remaining text as the message. Ignore malformed lines, non-error levels, and errors with an empty message. Return a dictionary mapping each message to its frequency. Process the iterable once so the complete log does not need to be copied.

Constraints

1 <= number of input lines <= 5000
Each input element is a string
A valid line has the format TIMESTAMP LEVEL MESSAGE
The level is separated from the timestamp and message by single spaces
Messages may contain spaces
Ignore malformed lines, non-ERROR levels, and empty ERROR messages
Message matching is case-sensitive

Function Signature

def count_error_messages(log_lines):

Your question is Parse Logs for Error Frequency. Start with the requirements in the Question tab.

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Problem

Write a script to parse a large log file, extract error messages, and count their frequency at Rippling.

Constraints

1 <= number of input lines <= 5000
Each input element is a string
A valid line has the format TIMESTAMP LEVEL MESSAGE
The level is separated from the timestamp and message by single spaces
Messages may contain spaces
Ignore malformed lines, non-ERROR levels, and empty ERROR messages
Message matching is case-sensitive

Function Signature

def count_error_messages(log_lines):

Your question is Parse Logs for Error Frequency. 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.