Add unknowns_analysis/tests/test_core.py

unknowns_analysis/tests/test_core.py

@@ -0,0 +1,73 @@
+import pytest
+import pandas as pd
+from unknowns_analysis import core
+
+@pytest.fixture
+def simple_unknowns_data():
+    return [
+        {"window": 1, "unknowns": 3},
+        {"window": 2, "unknowns": 0},
+        {"window": 3, "unknowns": 2}
+    ]
+
+
+@pytest.fixture
+def simple_warn_data():
+    return [
+        {"window": 1, "warn_rate": 0.3},
+        {"window": 2, "warn_rate": 0.2},
+        {"window": 3, "warn_rate": 0.25}
+    ]
+
+
+def test_analyze_unknowns_basic(simple_unknowns_data, simple_warn_data):
+    result = core.analyze_unknowns(simple_unknowns_data, simple_warn_data)
+    assert isinstance(result, dict), "Result must be a dict"
+    assert set(result.keys()) == {"total_unknowns", "warn_increases", "warn_stable"}
+    assert result["total_unknowns"] == sum(u["unknowns"] for u in simple_unknowns_data)
+    assert isinstance(result["warn_increases"], int)
+    assert isinstance(result["warn_stable"], int)
+
+
+def test_analyze_unknowns_empty_inputs():
+    with pytest.raises(ValueError):
+        core.analyze_unknowns([], [])
+
+
+def test_analyze_unknowns_invalid_inputs():
+    bad_unknowns = [{"window": 1, "no_field": 10}]
+    warn_data = [{"window": 1, "warn_rate": 0.2}]
+    with pytest.raises(ValueError):
+        core.analyze_unknowns(bad_unknowns, warn_data)
+
+
+def test_result_model_structure():
+    data = {"total_unknowns": 10, "warn_increases": 2, "warn_stable": 1}
+    model = core.UnknownAnalysisResult(**data)
+    assert model.total_unknowns == 10
+    assert model.warn_increases == 2
+    assert model.warn_stable == 1
+
+
+def test_integration_like_analysis(simple_unknowns_data, simple_warn_data):
+    result = core.analyze_unknowns(simple_unknowns_data, simple_warn_data)
+    df_unknowns = pd.DataFrame(simple_unknowns_data)
+    df_warns = pd.DataFrame(simple_warn_data)
+    total_unknowns = df_unknowns["unknowns"].sum()
+    assert result["total_unknowns"] == total_unknowns
+    assert 0 <= result["warn_increases"] <= len(df_warns)
+    assert 0 <= result["warn_stable"] <= len(df_warns)
+
+
+def test_warn_increase_and_stable_logic(monkeypatch, simple_unknowns_data, simple_warn_data):
+    def fake_warn_data():
+        return [
+            {"window": 1, "warn_rate": 0.2},
+            {"window": 2, "warn_rate": 0.3},
+            {"window": 3, "warn_rate": 0.3},
+        ]
+
+    result = core.analyze_unknowns(simple_unknowns_data, fake_warn_data())
+    assert isinstance(result, dict)
+    assert result["warn_increases"] >= 0
+    assert result["warn_stable"] >= 0