Add trace_agg/tests/test_core.py

trace_agg/tests/test_core.py

@@ -0,0 +1,51 @@
+import json
+import pytest
+from trace_agg import core
+
+@pytest.fixture
+def sample_trace_data():
+    # Simuliert TraceData-Struktur gemäss data_model
+    return [
+        {
+            "entry_time": 100.0,
+            "first_read_time": 150.0,
+            "baseline_recalc_time": 200.0,
+            "delta": 0.0
+        },
+        {
+            "entry_time": 110.0,
+            "first_read_time": 160.0,
+            "baseline_recalc_time": 215.0,
+            "delta": 0.0
+        }
+    ]
+
+def test_aggregate_traces_returns_list(sample_trace_data):
+    result = core.aggregate_traces(sample_trace_data)
+    assert isinstance(result, list)
+
+def test_aggregate_traces_computes_deltas(sample_trace_data):
+    result = core.aggregate_traces(sample_trace_data)
+    assert all(isinstance(item, dict) for item in result)
+    # Überprüft Delta-Kettenlogik: Differenzen sollen positiv sein
+    for chain in result:
+        if 'd_entry_first' in chain:
+            assert chain['d_entry_first'] > 0
+        if 'd_first_recalc' in chain:
+            assert chain['d_first_recalc'] > 0
+
+def test_aggregate_traces_handles_empty_list():
+    result = core.aggregate_traces([])
+    assert result == []
+
+def test_aggregate_traces_maintains_trace_order(sample_trace_data):
+    result = core.aggregate_traces(sample_trace_data)
+    # Sicherstellen, dass Reihenfolge analog Input bleibt
+    assert len(result) == len(sample_trace_data)
+
+
+def test_trace_data_format_integrity(sample_trace_data):
+    # Inputdaten sind valide nach data_model
+    for td in sample_trace_data:
+        assert set(td.keys()) == {"entry_time", "first_read_time", "baseline_recalc_time", "delta"}
+        assert all(isinstance(td[k], float) for k in td)