From 9f092d44cc0242527e4739b0bfb455e665e5f166 Mon Sep 17 00:00:00 2001
From: Mika <kontakt@donau2space.de>
Date: Fri, 13 Feb 2026 12:26:33 +0000
Subject: [PATCH] Add 1.logging_analysis/src/logging_analysis/core.py

---
 .../src/logging_analysis/core.py              | 112 ++++++++++++++++++
 1 file changed, 112 insertions(+)
 create mode 100644 1.logging_analysis/src/logging_analysis/core.py

diff --git a/1.logging_analysis/src/logging_analysis/core.py b/1.logging_analysis/src/logging_analysis/core.py
new file mode 100644
index 0000000..639617f
--- /dev/null
+++ b/1.logging_analysis/src/logging_analysis/core.py
@@ -0,0 +1,112 @@
+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