feat(SIMPL-24642): migrate tests from 3 source repos with updated imports

tests/dataframe_level_anonymisation/test_ops.py

@@ -0,0 +1,230 @@
+import pytest
+import pandas as pd
+from unittest.mock import patch
+from dagster import DagsterInvalidInvocationError, build_op_context
+
+from template_code_location.dataframe_level_anonymisation.ops import (
+    apply_k_anonymity,
+    apply_l_diversity,
+    apply_t_closeness,
+)
+from template_code_location.dataframe_level_anonymisation.config_models import (
+    KAnonymityConfiguration,
+    LDiversityConfiguration,
+    TClosenessConfiguration,
+)
+
+
+# ---------------------------
+# Fixtures
+# ---------------------------
+@pytest.fixture
+def fake_df():
+    return pd.DataFrame({"id": [1, 2], "age": [30, 40]})
+
+
+@pytest.fixture
+def k_config():
+    return KAnonymityConfiguration(
+        ident=["id"],
+        quasi_identifiers=["age"],
+        sensitive_attributes=["age"],
+        k=2,
+        supp_level=0.0,
+        generalisation_hierarchies={"age": "simpl_age"},
+    )
+
+
+@pytest.fixture
+def l_config():
+    return LDiversityConfiguration(
+        ident=["id"],
+        quasi_identifiers=["age"],
+        sensitive_attribute="age",
+        k=2,
+        l=1,
+        supp_level=0.0,
+        generalisation_hierarchies={"age": "simpl_age"},
+    )
+
+
+@pytest.fixture
+def t_config():
+    return TClosenessConfiguration(
+        ident=["id"],
+        quasi_identifiers=["age"],
+        sensitive_attribute="age",
+        k=2,
+        t=0.5,
+        supp_level=0.0,
+        generalisation_hierarchies={"age": "simpl_age"},
+    )
+
+
+@pytest.fixture
+def op_context():
+    return build_op_context()
+
+
+# ---------------------------
+# Helper for patching external functions
+# ---------------------------
+@pytest.fixture(autouse=True)
+def patch_external_ops():
+    with (
+        patch(
+            "dataframe_level_anonymisation.ops.get_all_hierarchies",
+            return_value={"simpl_age": {0: [30, 40]}},
+        ),
+        patch(
+            "dataframe_level_anonymisation.ops.k_anonymity",
+            return_value=pd.DataFrame({"id": [1, 2], "age": [30, 40]}),
+        ),
+        patch(
+            "dataframe_level_anonymisation.ops.l_diversity",
+            return_value=pd.DataFrame({"id": [1, 2], "age": [30, 40]}),
+        ),
+        patch(
+            "dataframe_level_anonymisation.ops.t_closeness",
+            return_value=pd.DataFrame({"id": [1, 2], "age": [30, 40]}),
+        ),
+    ):
+        yield
+
+
+# ---------------------------
+# Tests for apply_k_anonymity
+# ---------------------------
+def test_apply_k_anonymity_outputs(op_context, k_config, fake_df):
+    results = list(apply_k_anonymity(op_context, k_config, fake_df))
+    assert len(results) == 2
+
+    data_output = results[0].value
+    metrics_output = results[1].value
+
+    # Check types
+    assert isinstance(data_output, pd.DataFrame)
+    assert isinstance(metrics_output, dict)
+    assert "k_anon" in metrics_output
+    assert "l_div" in metrics_output
+    assert "t_clos" in metrics_output
+
+
+# ---------------------------
+# Tests for apply_l_diversity
+# ---------------------------
+def test_apply_l_diversity_outputs(op_context, l_config, fake_df):
+    results = list(apply_l_diversity(op_context, l_config, fake_df))
+    assert len(results) == 2
+
+    data_output = results[0].value
+    metrics_output = results[1].value
+
+    assert isinstance(data_output, pd.DataFrame)
+    assert isinstance(metrics_output, dict)
+    assert "k_anon" in metrics_output
+    assert "l_div" in metrics_output
+    assert "t_clos" in metrics_output
+
+
+def test_apply_l_diversity_empty_raises(op_context, l_config):
+    with patch("dataframe_level_anonymisation.ops.l_diversity", return_value=pd.DataFrame()):
+
+        with pytest.raises(DagsterInvalidInvocationError):
+            list(apply_l_diversity(op_context, l_config, pd.DataFrame({"id": [1], "age": [30]})))
+
+
+# ---------------------------
+# Tests for apply_t_closeness
+# ---------------------------
+def test_apply_t_closeness_outputs(op_context, t_config, fake_df):
+    results = list(apply_t_closeness(op_context, t_config, fake_df))
+    assert len(results) == 2
+
+    data_output = results[0].value
+    metrics_output = results[1].value
+
+    assert isinstance(data_output, pd.DataFrame)
+    assert isinstance(metrics_output, dict)
+    assert "k_anon" in metrics_output
+    assert "l_div" in metrics_output
+    assert "t_clos" in metrics_output
+
+
+def test_apply_t_closeness_empty_raises(op_context, t_config):
+    with patch("dataframe_level_anonymisation.ops.t_closeness", return_value=pd.DataFrame()):
+        with pytest.raises(DagsterInvalidInvocationError):
+            list(apply_t_closeness(op_context, t_config, pd.DataFrame({"id": [1], "age": [30]})))
+
+
+# ---------------------------
+# Additional tests for _validate_and_get_hierarchies
+# ---------------------------
+def test_validate_hierarchies_dataset_too_small(k_config):
+    small_df = pd.DataFrame({"id": [1], "age": [30]})
+    from template_code_location.dataframe_level_anonymisation.ops import _validate_and_get_hierarchies
+
+    with pytest.raises(DagsterInvalidInvocationError):
+        _validate_and_get_hierarchies(k_config, small_df)
+
+
+def test_validate_hierarchies_missing_hierarchy(k_config, fake_df):
+    from template_code_location.dataframe_level_anonymisation.ops import _validate_and_get_hierarchies
+
+    bad_config = k_config.model_copy(update={"generalisation_hierarchies": {}})
+
+    with pytest.raises(DagsterInvalidInvocationError):
+        _validate_and_get_hierarchies(bad_config, fake_df)
+
+
+def test_validate_hierarchies_hierarchy_not_in_code(k_config, fake_df):
+    from template_code_location.dataframe_level_anonymisation.ops import _validate_and_get_hierarchies
+
+    with patch("dataframe_level_anonymisation.ops.get_all_hierarchies", return_value={}):
+        with pytest.raises(DagsterInvalidInvocationError):
+            _validate_and_get_hierarchies(k_config, fake_df)
+
+
+# ---------------------------
+# Additional tests for _calc_dataframe_metrics
+# ---------------------------
+def test_calc_dataframe_metrics_basic():
+    from template_code_location.dataframe_level_anonymisation.ops import _calc_dataframe_metrics
+
+    df_org = pd.DataFrame({"age": [30, 40], "id": [1, 2]})
+    df_anon = df_org.copy()
+
+    with (
+        patch("dataframe_level_anonymisation.ops.anonymity.k_anonymity", return_value=2),
+        patch("dataframe_level_anonymisation.ops.anonymity.l_diversity", return_value=1),
+        patch("dataframe_level_anonymisation.ops.anonymity.t_closeness", return_value=0.1),
+    ):
+
+        report, metrics = _calc_dataframe_metrics(df_anon, df_org, ["age"], ["age"])
+
+        assert "k-anonymity" in report
+        assert metrics["k_anon"] == 2
+        assert metrics["l_div"] == 1
+        assert metrics["t_clos"] == 0.1
+
+
+# ---------------------------
+# Tests for apply_t_closeness exception branches
+# ---------------------------
+def test_apply_t_closeness_value_error_quasi_identifiers(op_context, t_config, fake_df):
+    """Covers the branch where ValueError contains 'Cannot be quasi-identifiers'."""
+    with patch(
+        "dataframe_level_anonymisation.ops.t_closeness",
+        side_effect=ValueError("Cannot be quasi-identifiers invalid"),
+    ):
+        with pytest.raises(DagsterInvalidInvocationError):
+            list(apply_t_closeness(op_context, t_config, fake_df))
+
+
+def test_apply_t_closeness_value_error_other_message(op_context, t_config, fake_df):
+    """Covers the branch where ValueError is raised but message does NOT contain that substring."""
+    with patch(
+        "dataframe_level_anonymisation.ops.t_closeness", side_effect=ValueError("Some other error")
+    ):
+        with pytest.raises(DagsterInvalidInvocationError):
+            list(apply_t_closeness(op_context, t_config, fake_df))