Add policy_evaluation/tests/test_core.py

policy_evaluation/tests/test_core.py

@@ -0,0 +1,81 @@
+import pytest
+import pandas as pd
+import numpy as np
+from policy_evaluation import core
+
+@pytest.fixture
+def sample_log_data():
+    # Enthält pinned und unpinned-Einträge mit diversen Zeitwerten und Drifts
+    return [
+        {
+            't_publish': 1.0,
+            't_gate_read': 2.0,
+            't_index_visible': 3.0,
+            'pinned_flag': True,
+            'timeouts': 0,
+            'drift_signature': 'normal'
+        },
+        {
+            't_publish': 2.0,
+            't_gate_read': 3.5,
+            't_index_visible': 4.0,
+            'pinned_flag': False,
+            'timeouts': 1,
+            'drift_signature': 'mild_drift'
+        },
+        {
+            't_publish': 3.0,
+            't_gate_read': 6.0,
+            't_index_visible': 7.0,
+            'pinned_flag': True,
+            'timeouts': 0,
+            'drift_signature': 'outlier'
+        }
+    ]
+
+
+def test_evaluate_policies_returns_policyresults(sample_log_data):
+    result = core.evaluate_policies(sample_log_data)
+    assert isinstance(result, core.PolicyResults)
+
+
+def test_policyresults_fields_are_valid(sample_log_data):
+    result = core.evaluate_policies(sample_log_data)
+    data = result.to_json()
+    required_fields = ['p99_coverage', 'remaining_missing_cases', 'conversion_rates', 'max_wait_time']
+
+    # Überprüfen, dass alle Felder vorhanden sind und den erwarteten Typen entsprechen
+    for field in required_fields:
+        assert field in data, f"{field} fehlt im Resultat"
+
+    assert isinstance(data['p99_coverage'], float)
+    assert isinstance(data['remaining_missing_cases'], int)
+    assert isinstance(data['conversion_rates'], float)
+    assert isinstance(data['max_wait_time'], float)
+
+
+def test_evaluate_policies_values_are_reasonable(sample_log_data):
+    result = core.evaluate_policies(sample_log_data)
+    data = result.to_json()
+    # Da p99 Coverage und Zeit nicht genau definiert, prüfen wir nur Wertebereiche
+    assert 0.0 <= data['p99_coverage'] <= 1.0
+    assert data['remaining_missing_cases'] >= 0
+    assert 0.0 <= data['conversion_rates'] <= 1.0
+    assert data['max_wait_time'] >= 0.0
+
+
+def test_evaluate_policies_invalid_input_raises():
+    with pytest.raises((TypeError, ValueError)):
+        core.evaluate_policies(None)
+
+
+def test_evaluate_policies_empty_data():
+    result = core.evaluate_policies([])
+    # Bei leerem Input sollte gültiges PolicyResults-Objekt erstellt werden
+    data = result.to_json()
+    assert isinstance(data, dict)
+    assert all(k in data for k in ['p99_coverage', 'remaining_missing_cases', 'conversion_rates', 'max_wait_time'])
+    assert data['p99_coverage'] == 0.0
+    assert data['remaining_missing_cases'] == 0
+    assert data['conversion_rates'] == 0.0
+    assert data['max_wait_time'] == 0.0