Add 1.logging_analysis/src/logging_analysis/core.py

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Mika 2026-02-13 12:26:33 +00:00
commit 9f092d44cc

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from __future__ import annotations
import json
from pathlib import Path
from datetime import datetime
from dataclasses import dataclass
from typing import List, Dict, Any
from statistics import mean
import logging
logging.basicConfig(level=logging.INFO, format='[%(levelname)s] %(message)s')
class LogAnalysisError(Exception):
"""Base exception for log analysis errors."""
pass
@dataclass
class LogEntry:
"""Repräsentiert einen einzelnen Logeintrag eines Artefakts."""
timestamp: datetime
expected_artifact_path: str
artifact_key: str
status: str
@staticmethod
def from_dict(data: Dict[str, Any]) -> 'LogEntry':
required_fields = {"timestamp", "expected_artifact_path", "artifact_key", "status"}
missing = required_fields - data.keys()
if missing:
raise LogAnalysisError(f"Missing fields in log entry: {missing}")
try:
timestamp = datetime.fromisoformat(str(data["timestamp"]))
except Exception as exc:
raise LogAnalysisError(f"Invalid timestamp format: {data['timestamp']}") from exc
status = str(data["status"]).lower()
if status not in {"missing", "present", "delayed", "unknown"}:
raise LogAnalysisError(f"Invalid status value: {status}")
return LogEntry(
timestamp=timestamp,
expected_artifact_path=str(data["expected_artifact_path"]),
artifact_key=str(data["artifact_key"]),
status=status,
)
def analyze_log(log_file_path: str) -> Dict[str, Any]:
"""Analysiert eine Logdatei mit Artefakt-Daten und erstellt eine Zusammenfassung über fehlende oder verspätete Artefakte."""
path = Path(log_file_path)
if not path.exists():
raise FileNotFoundError(f"Log file not found: {log_file_path}")
try:
with path.open("r", encoding="utf-8") as f:
raw_data = json.load(f)
except json.JSONDecodeError as exc:
raise LogAnalysisError(f"Invalid JSON in log file: {exc}") from exc
if not isinstance(raw_data, list):
raise LogAnalysisError("Expected a list of log entries in JSON file.")
entries: List[LogEntry] = []
for i, item in enumerate(raw_data):
try:
entry = LogEntry.from_dict(item)
entries.append(entry)
except LogAnalysisError as exc:
logging.warning(f"Skipping invalid entry #{i}: {exc}")
total = len(entries)
if total == 0:
raise LogAnalysisError("No valid log entries found in file.")
missing_count = sum(1 for e in entries if e.status == "missing")
delayed_count = sum(1 for e in entries if e.status == "delayed")
present_count = sum(1 for e in entries if e.status == "present")
missing_rate = missing_count / total
delayed_rate = delayed_count / total
timestamps = [e.timestamp.timestamp() for e in entries if e.status == "present"]
avg_interval = None
if len(timestamps) > 1:
intervals = [t2 - t1 for t1, t2 in zip(timestamps, timestamps[1:]) if t2 >= t1]
if intervals:
avg_interval = mean(intervals)
summary = {
"total_entries": total,
"missing_count": missing_count,
"delayed_count": delayed_count,
"present_count": present_count,
"missing_rate": round(missing_rate, 3),
"delayed_rate": round(delayed_rate, 3),
"avg_present_interval_sec": round(avg_interval, 3) if avg_interval is not None else None,
"summary_text": (
f"Logs analyzed: {total}. Missing: {missing_count} ({missing_rate:.1%}), "
f"Delayed: {delayed_count} ({delayed_rate:.1%}), Present: {present_count}."
)
}
assert 0.0 <= summary["missing_rate"] <= 1.0, "Missing rate out of range"
assert 0.0 <= summary["delayed_rate"] <= 1.0, "Delayed rate out of range"
logging.info(summary["summary_text"])
return summary