From a1c7919db3622658109d34cffd036d9f27ab170a Mon Sep 17 00:00:00 2001
From: Mika <kontakt@donau2space.de>
Date: Sun, 15 Feb 2026 11:41:27 +0000
Subject: [PATCH] Add measure_latency/src/measure_latency/core.py

---
 measure_latency/src/measure_latency/core.py | 109 ++++++++++++++++++++
 1 file changed, 109 insertions(+)
 create mode 100644 measure_latency/src/measure_latency/core.py

diff --git a/measure_latency/src/measure_latency/core.py b/measure_latency/src/measure_latency/core.py
new file mode 100644
index 0000000..19bb546
--- /dev/null
+++ b/measure_latency/src/measure_latency/core.py
@@ -0,0 +1,109 @@
+from __future__ import annotations
+
+import time
+import json
+import os
+from pathlib import Path
+from datetime import datetime
+from statistics import median, quantiles, variance
+from typing import List, Dict, Any
+
+
+class LatencyResult:
+    """Repräsentiert eine einzelne Messung der Latenzzeit-Komponenten."""
+
+    def __init__(
+        self,
+        upload_end_time: datetime,
+        api_response_time: datetime,
+        fs_mtime: datetime,
+    ) -> None:
+        assert isinstance(upload_end_time, datetime), "upload_end_time muss datetime sein"
+        assert isinstance(api_response_time, datetime), "api_response_time muss datetime sein"
+        assert isinstance(fs_mtime, datetime), "fs_mtime muss datetime sein"
+        
+        self.upload_end_time = upload_end_time
+        self.api_response_time = api_response_time
+        self.fs_mtime = fs_mtime
+        self.offsets: Dict[str, float] = self.compute_offsets()
+
+    def compute_offsets(self) -> Dict[str, float]:
+        """Berechnet Zeitdifferenzen zwischen den Messpunkten in Sekunden."""
+        upload_to_api = (self.api_response_time - self.upload_end_time).total_seconds()
+        api_to_fs = (self.fs_mtime - self.api_response_time).total_seconds()
+        upload_to_fs = (self.fs_mtime - self.upload_end_time).total_seconds()
+        return {
+            "upload_to_api": upload_to_api,
+            "api_to_fs": api_to_fs,
+            "upload_to_fs": upload_to_fs,
+        }
+
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            "upload_end_time": self.upload_end_time.isoformat(),
+            "api_response_time": self.api_response_time.isoformat(),
+            "fs_mtime": self.fs_mtime.isoformat(),
+            "offsets": self.offsets,
+        }
+
+
+def measure_latencies(n_runs: int) -> List[LatencyResult]:
+    """Führt n wiederholte Messungen aus und protokolliert Zeitpunkte pro Messung."""
+    assert isinstance(n_runs, int) and n_runs > 0, "n_runs muss eine positive ganze Zahl sein"
+    results: List[LatencyResult] = []
+
+    tmp_file = Path("/tmp/latency_probe.txt")
+    for _ in range(n_runs):
+        upload_end = datetime.now()
+        # simulierte API-Response nach kurzer Pause
+        time.sleep(0.01)
+        api_response = datetime.now()
+        # simuliertes Datei-Schreiben
+        tmp_file.write_text(str(upload_end.timestamp()))
+        fs_stat = os.stat(tmp_file)
+        fs_mtime = datetime.fromtimestamp(fs_stat.st_mtime)
+        result = LatencyResult(upload_end, api_response, fs_mtime)
+        results.append(result)
+
+    output_dir = Path("output")
+    output_dir.mkdir(exist_ok=True)
+    json_path = output_dir / "latency_results.json"
+    with json_path.open("w", encoding="utf-8") as f:
+        json.dump([r.to_dict() for r in results], f, indent=2)
+
+    return results
+
+
+def analyze_results(latency_results: List[LatencyResult]) -> Dict[str, Any]:
+    """Analysiert Latenzergebnisse und berechnet Statistiken."""
+    assert isinstance(latency_results, list) and all(isinstance(r, LatencyResult) for r in latency_results), (
+        "latency_results muss eine Liste von LatencyResult sein"
+    )
+
+    all_upload_to_fs = [r.offsets["upload_to_fs"] for r in latency_results]
+    if not all_upload_to_fs:
+        return {}
+
+    median_val = median(all_upload_to_fs)
+    try:
+        q50 = quantiles(all_upload_to_fs, n=100)[49]
+        q95 = quantiles(all_upload_to_fs, n=100)[94]
+    except Exception:
+        q50 = median_val
+        q95 = max(all_upload_to_fs)
+
+    summary: Dict[str, Any] = {
+        "count": len(all_upload_to_fs),
+        "p50": q50,
+        "p95": q95,
+        "max": max(all_upload_to_fs),
+        "variance": variance(all_upload_to_fs) if len(all_upload_to_fs) > 1 else 0.0,
+    }
+
+    output_dir = Path("output")
+    output_dir.mkdir(exist_ok=True)
+    summary_path = output_dir / "analysis_summary.json"
+    with summary_path.open("w", encoding="utf-8") as f:
+        json.dump(summary, f, indent=2)
+
+    return summary