Add data_analysis/tests/test_core.py

data_analysis/tests/test_core.py

@@ -0,0 +1,55 @@
+import pytest
+from datetime import datetime, timedelta
+from data_analysis import core
+
+
+@pytest.fixture
+def sample_run_data():
+    base_time = datetime(2024, 1, 1, 12, 0, 0)
+    return [
+        {
+            'run_id': 'r1',
+            'timestamp': base_time,
+            'delta_t': 0.5,
+            'expiring_at': base_time + timedelta(hours=1)
+        },
+        {
+            'run_id': 'r2',
+            'timestamp': base_time + timedelta(seconds=5),
+            'delta_t': -0.2,
+            'expiring_at': base_time + timedelta(hours=2)
+        },
+        {
+            'run_id': 'r3',
+            'timestamp': base_time + timedelta(seconds=10),
+            'delta_t': 0.0,
+            'expiring_at': base_time + timedelta(hours=3)
+        }
+    ]
+
+
+def test_analyze_runs_structure(sample_run_data):
+    result = core.analyze_runs(sample_run_data)
+    assert isinstance(result, dict), 'Result must be a dict'
+    expected_keys = {'total_runs', 'negative_dt_count', 'negative_dt_ratio'}
+    for key in expected_keys:
+        assert key in result, f'Missing key: {key}'
+
+
+def test_analyze_runs_negative_count(sample_run_data):
+    result = core.analyze_runs(sample_run_data)
+    assert result['negative_dt_count'] == 1
+    assert result['total_runs'] == 3
+    assert result['negative_dt_ratio'] == pytest.approx(1/3, rel=1e-3)
+
+
+def test_analyze_runs_empty_list():
+    result = core.analyze_runs([])
+    assert result['total_runs'] == 0
+    assert result['negative_dt_count'] == 0
+    assert result['negative_dt_ratio'] == 0.0
+
+
+def test_analyze_runs_type_validation():
+    with pytest.raises((TypeError, AssertionError)):
+        core.analyze_runs('invalid_input')