From ade86428c6d7062f503c7fce2e70aed34f27e785 Mon Sep 17 00:00:00 2001
From: Mika <kontakt@donau2space.de>
Date: Sat, 7 Feb 2026 11:55:55 +0000
Subject: [PATCH] Add policy_eval/src/policy_eval/core.py

---
 policy_eval/src/policy_eval/core.py | 69 +++++++++++++++++++++++++++++
 1 file changed, 69 insertions(+)
 create mode 100644 policy_eval/src/policy_eval/core.py

diff --git a/policy_eval/src/policy_eval/core.py b/policy_eval/src/policy_eval/core.py
new file mode 100644
index 0000000..0732bf1
--- /dev/null
+++ b/policy_eval/src/policy_eval/core.py
@@ -0,0 +1,69 @@
+from __future__ import annotations
+import json
+from collections.abc import Mapping
+from dataclasses import dataclass, asdict
+from typing import Any, Dict
+
+
+@dataclass
+class EvaluationMetrics:
+    total_warn: int
+    total_fail: int
+    unknowns: int
+    manual_overrides: int
+
+    def to_dict(self) -> Dict[str, int]:
+        """Return a dict with keys sorted alphabetically for diff-friendly output."""
+        data = asdict(self)
+        return {k: data[k] for k in sorted(data.keys())}
+
+
+def evaluate_policy(drift_report: Dict[str, Any]) -> Dict[str, int]:
+    """Aggregiert Metriken aus einem Drift-Report.
+
+    Erwartet ein Dictionary, das Metriken wie Warnungen, Fehler,
+    unbekannte Elemente oder manuelle Overrides enthält.
+    Fehlende Felder werden als 'unknown' gezählt.
+
+    Args:
+        drift_report: Strukturierter JSON-Report über Policy-Drifts.
+
+    Returns:
+        Dict mit aggregierten Metriken (total_warn, total_fail, unknowns, manual_overrides).
+    """
+    if not isinstance(drift_report, Mapping):
+        raise TypeError("drift_report must be a dict-like object")
+
+    # Extract known keys safely
+    warn = drift_report.get("warn") or drift_report.get("warnings") or 0
+    fail = drift_report.get("fail") or drift_report.get("errors") or 0
+    overrides = drift_report.get("manual_overrides") or drift_report.get("overrides") or 0
+
+    # Identify unknowns: fields not in known keys and missing expected ones
+    known_keys = {"warn", "warnings", "fail", "errors", "manual_overrides", "overrides"}
+    unknown_fields = [k for k in drift_report.keys() if k not in known_keys]
+
+    # Missing expected keys are also counted as unknown
+    missing_expected = [key for key in ("warn", "fail", "manual_overrides") if key not in drift_report]
+    unknown_total = len(unknown_fields) + len(missing_expected)
+
+    # Ensure numeric consistency
+    try:
+        metrics = EvaluationMetrics(
+            total_warn=int(warn),
+            total_fail=int(fail),
+            unknowns=int(unknown_total),
+            manual_overrides=int(overrides)
+        )
+    except (ValueError, TypeError) as e:
+        raise ValueError(f"Invalid field type in drift_report: {e}") from e
+
+    result = metrics.to_dict()
+
+    # Basic assertions for CI consistency
+    assert all(isinstance(v, int) for v in result.values()), "All metric values must be int"
+    assert all(k in {"manual_overrides", "total_fail", "total_warn", "unknowns"} for k in result), (
+        "Unexpected keys in result dict"
+    )
+
+    return result