From ebe506aa225e63031c771d880b4e80030221e11c Mon Sep 17 00:00:00 2001
From: Mika <kontakt@donau2space.de>
Date: Sun, 12 Apr 2026 02:07:09 +0000
Subject: [PATCH] Add
 temperature_data_analysis/src/temperature_data_analysis/core.py

---
 .../src/temperature_data_analysis/core.py     | 57 +++++++++++++++++++
 1 file changed, 57 insertions(+)
 create mode 100644 temperature_data_analysis/src/temperature_data_analysis/core.py

diff --git a/temperature_data_analysis/src/temperature_data_analysis/core.py b/temperature_data_analysis/src/temperature_data_analysis/core.py
new file mode 100644
index 0000000..d632aa9
--- /dev/null
+++ b/temperature_data_analysis/src/temperature_data_analysis/core.py
@@ -0,0 +1,57 @@
+from __future__ import annotations
+
+import statistics
+from dataclasses import dataclass, asdict
+from typing import List, Dict
+
+
+@dataclass
+class AnalysisResult:
+    """Repräsentiert das Ergebnis einer Temperaturdatenanalyse."""
+
+    mean_temperature: float
+    temperature_variance: float
+
+    def to_dict(self) -> Dict[str, float]:
+        """Konvertiert das Analyseergebnis in ein Dictionary."""
+        return asdict(self)
+
+
+def analyze_temperature_data(data: List[float]) -> Dict[str, float]:
+    """Analysiert eine Liste von Temperaturwerten und berechnet Mittelwert und Varianz.
+
+    Args:
+        data: Liste von Temperaturwerten in Grad Celsius.
+
+    Returns:
+        Dictionary mit Schlüsseln 'mean_temperature' und 'temperature_variance'.
+
+    Raises:
+        ValueError: Wenn die Eingabeliste leer ist oder ungültige Werte enthält.
+    """
+    # Eingabevalidierung
+    if not isinstance(data, list):
+        raise ValueError("Input data must be a list of floats.")
+    if not data:
+        raise ValueError("Input data list cannot be empty.")
+
+    validated_values = []
+    for v in data:
+        if not isinstance(v, (int, float)):
+            raise ValueError(f"Invalid value in data (not numeric): {v}")
+        validated_values.append(float(v))
+
+    # Berechnungen
+    try:
+        mean_val = statistics.mean(validated_values)
+        variance_val = statistics.pvariance(validated_values)
+    except statistics.StatisticsError as e:
+        raise ValueError(f"Error calculating statistics: {e}")
+
+    result = AnalysisResult(mean_temperature=mean_val, temperature_variance=variance_val)
+
+    # CI-Readiness: Assertions für Datenintegrität
+    assert isinstance(result.mean_temperature, float)
+    assert isinstance(result.temperature_variance, float)
+
+    return result.to_dict()
\ No newline at end of file