From bae235cd3c5a1353987381266c246aeab92a10d9 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/cli.py

---
 policy_eval/src/policy_eval/cli.py | 63 ++++++++++++++++++++++++++++++
 1 file changed, 63 insertions(+)
 create mode 100644 policy_eval/src/policy_eval/cli.py

diff --git a/policy_eval/src/policy_eval/cli.py b/policy_eval/src/policy_eval/cli.py
new file mode 100644
index 0000000..532291c
--- /dev/null
+++ b/policy_eval/src/policy_eval/cli.py
@@ -0,0 +1,63 @@
+import argparse
+import json
+import os
+from pathlib import Path
+from typing import Any
+from policy_eval.core import evaluate_policy
+
+
+def main() -> None:
+    """Command-line interface for evaluating policy metrics.
+
+    This CLI accepts input and output JSON file paths, evaluates the provided
+    drift report using the core.evaluate_policy function, and writes the
+    resulting evaluation metrics JSON.
+    """
+    parser = argparse.ArgumentParser(
+        description="Evaluate policy metrics from a drift report."
+    )
+    parser.add_argument(
+        "--input",
+        required=True,
+        help="Path to the drift report JSON file."
+    )
+    parser.add_argument(
+        "--output",
+        required=True,
+        help="Path to the output evaluation metrics JSON file."
+    )
+
+    args = parser.parse_args()
+
+    input_path = Path(args.input).expanduser().resolve()
+    output_path = Path(args.output).expanduser().resolve()
+
+    # Basic input validation (required by constraints)
+    if not input_path.exists() or not input_path.is_file():
+        raise FileNotFoundError(f"Input file does not exist: {input_path}")
+
+    with open(input_path, "r", encoding="utf-8") as f:
+        drift_data: Any = json.load(f)
+
+    if not isinstance(drift_data, dict):
+        raise ValueError("Invalid drift report: expected a dict JSON structure.")
+
+    metrics = evaluate_policy(drift_data)
+
+    # CI validation: ensure output conforms to expected data model
+    required_fields = {"total_warn", "total_fail", "unknowns", "manual_overrides"}
+    if not isinstance(metrics, dict) or not required_fields.issubset(metrics.keys()):
+        raise ValueError(
+            f"Invalid evaluation output: missing required fields. Expected {required_fields}, got {set(metrics.keys())}."
+        )
+
+    # Ensure output directory exists
+    os.makedirs(output_path.parent, exist_ok=True)
+
+    with open(output_path, "w", encoding="utf-8") as out_file:
+        json.dump(metrics, out_file, indent=2, sort_keys=True)
+        out_file.write("\n")
+
+
+if __name__ == "__main__":
+    main()