Problem

You are given log lines from an Apple service and a list of error patterns to track. Write a Python function that scans the logs and returns how many times each pattern appears, along with the matching log lines for each pattern.

A log line matches a pattern if the pattern appears as a case-sensitive substring anywhere in that line. A single line may match multiple patterns. Ignore empty log lines.

Formal Specification

• Input:
  • logs: a list of strings, where each string is one log line
  • patterns: a list of unique strings representing error patterns to search for
• Output:
  • A dictionary where each key is a pattern and each value is another dictionary with:
    • count: number of matching log lines
    • lines: list of matching log lines in original order

Examples

Example 1

• Input: logs = ["INFO startup complete", "ERROR timeout on request", "WARN retry", "ERROR timeout on request"], patterns = ["ERROR", "timeout"]
• Output: {"ERROR": {"count": 2, "lines": ["ERROR timeout on request", "ERROR timeout on request"]}, "timeout": {"count": 2, "lines": ["ERROR timeout on request", "ERROR timeout on request"]}}
• Explanation: Both patterns appear in the two error lines.

Example 2

• Input: logs = ["", "UIKit failed to load", "NetworkError: disconnected"], patterns = ["failed", "Error"]
• Output: {"failed": {"count": 1, "lines": ["UIKit failed to load"]}, "Error": {"count": 1, "lines": ["NetworkError: disconnected"]}}
• Explanation: Empty lines are ignored, and matching is case-sensitive.

Constraints

• 1 <= len(logs) <= 10^4
• 1 <= len(patterns) <= 100
• 0 <= len(logs[i]) <= 500
• 1 <= len(patterns[i]) <= 50
• patterns contains unique strings