Add spike_classifier/tests/test_core.py

spike_classifier/tests/test_core.py

@@ -0,0 +1,43 @@
+import json
+import os
+import pytest
+from spike_classifier import core
+
+
+def load_test_data():
+    data_path = os.path.join(os.path.dirname(__file__), 'data', 'test_spikes.json')
+    with open(data_path, 'r', encoding='utf-8') as f:
+        return json.load(f)
+
+
+def test_classify_spikes_returns_list():
+    json_data = load_test_data()
+    result = core.classify_spikes(json_data)
+    assert isinstance(result, list), 'Ergebnis sollte eine Liste sein.'
+    for item in result:
+        assert isinstance(item, dict), 'Jedes Element in der Liste sollte ein Dict sein.'
+
+
+def test_spike_fields_present_and_types():
+    json_data = load_test_data()
+    results = core.classify_spikes(json_data)
+    required_fields = {'spike_id': str, 'cpu_path': str, 'reorder_score': float, 'timestamp': str, 'signature': str}
+    for spike in results:
+        for field, expected_type in required_fields.items():
+            assert field in spike, f"Feld {field} fehlt im Ergebnis."
+            assert isinstance(spike[field], expected_type), f"Feld {field} hat falschen Typ: {type(spike[field])} statt {expected_type}."
+
+
+def test_reorder_score_range():
+    json_data = load_test_data()
+    results = core.classify_spikes(json_data)
+    for spike in results:
+        score = spike.get('reorder_score')
+        assert 0.0 <= score <= 1.0, 'reorder_score sollte zwischen 0.0 und 1.0 liegen.'
+
+
+def test_unique_spike_ids():
+    json_data = load_test_data()
+    results = core.classify_spikes(json_data)
+    spike_ids = [s['spike_id'] for s in results]
+    assert len(spike_ids) == len(set(spike_ids)), 'spike_id-Werte sollten eindeutig sein.'