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Parse Logs for Error Patterns

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Your question is Parse Logs for Error Patterns. Start with the requirements on the right.

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Problem

Pinterest's infrastructure team wants to summarize error logs from services supporting PinLater. Each log line uses the format timestamp|service|level|message. Implement a function that parses valid lines, keeps only entries whose level is exactly ERROR, and counts which configured error patterns occur in each entry.

A pattern matches when it appears as a case-insensitive substring of the message. If one message contains the same pattern multiple times, count that pattern only once for the message. One message may match multiple patterns. Ignore malformed lines, lines with a non-ERROR level, and patterns that never match.

Return a list of result objects sorted by descending count, then ascending pattern text. Each object must contain the original pattern, the number of distinct error log lines containing it, and the sorted list of affected services.

Formal Specification

  • Input: logs, a list of strings, and patterns, a list of non-empty strings.
  • Output: a list of dictionaries with keys pattern, count, and services.
  • A valid line has exactly four pipe-separated fields, and its level field must equal ERROR.

Constraints

  • 1 <= len(logs) <= 100000
  • 1 <= len(patterns) <= 1000
  • Each log line has at most 2000 characters
  • Each pattern is non-empty and has at most 100 characters
  • Pattern matching is case-insensitive
  • A valid log line contains exactly four pipe-separated fields

Function Signature

def analyze_error_logs(logs, patterns):
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