Error handling sanitize bug (#85)

* fix molsanitize exception error catching

* linting

* isort on other stuff

molpipeline/estimators/chemprop/models.py

@@ -15,9 +15,7 @@
 
 try:
     from chemprop.data import MoleculeDataset, build_dataloader
-    from chemprop.nn.predictors import (
-        BinaryClassificationFFNBase,
-    )
+    from chemprop.nn.predictors import BinaryClassificationFFNBase
     from lightning import pytorch as pl
 except ImportError as error:
     logger.error(
@@ -31,9 +29,9 @@
     MPNN,
     BinaryClassificationFFN,
     BondMessagePassing,
+    MulticlassClassificationFFN,
     RegressionFFN,
     SumAggregation,
-    MulticlassClassificationFFN,
 )
 from molpipeline.estimators.chemprop.neural_fingerprint import ChempropNeuralFP
 

molpipeline/pipeline/_molpipeline.py

@@ -349,7 +349,7 @@ def transform_single(self, input_value: Any) -> Any:
                 elif isinstance(p_element, FilterReinserter):
                     iter_value = p_element.transform_single(iter_value)
             except MolSanitizeException as err:
-                return InvalidInstance(
+                iter_value = InvalidInstance(
                     p_element.uuid,
                     f"RDKit MolSanitizeException: {err.args}",
                     p_element.name,

test_extras/test_chemprop/test_chemprop_pipeline.py

@@ -22,8 +22,8 @@
 from molpipeline.estimators.chemprop.models import (
     ChempropClassifier,
     ChempropModel,
-    ChempropRegressor,
     ChempropMulticlassClassifier,
+    ChempropRegressor,
 )
 from molpipeline.mol2any.mol2chemprop import MolToChemprop
 from molpipeline.pipeline import Pipeline

test_extras/test_chemprop/test_models.py

@@ -28,10 +28,10 @@
 # pylint: disable=relative-beyond-top-level
 from test_extras.test_chemprop.chemprop_test_utils.compare_models import compare_params
 from test_extras.test_chemprop.chemprop_test_utils.constant_vars import (
-    NO_IDENTITY_CHECK,
-    DEFAULT_SET_PARAMS,
     DEFAULT_BINARY_CLASSIFICATION_PARAMS,
     DEFAULT_MULTICLASS_CLASSIFICATION_PARAMS,
+    DEFAULT_SET_PARAMS,
+    NO_IDENTITY_CHECK,
 )
 from test_extras.test_chemprop.chemprop_test_utils.default_models import (
     get_chemprop_model_binary_classification_mpnn,

tests/test_elements/test_error_handling.py

@@ -4,12 +4,16 @@
 from typing import Any
 
 import numpy as np
-from rdkit import RDLogger
+from rdkit import Chem, RDLogger
+from rdkit.Chem.rdchem import MolSanitizeException
 from sklearn.base import clone
 
 from molpipeline import ErrorFilter, FilterReinserter, Pipeline, PostPredictionWrapper
+from molpipeline.abstract_pipeline_elements.core import MolToMolPipelineElement
 from molpipeline.any2mol import SmilesToMol
+from molpipeline.any2mol.auto2mol import AutoToMol
 from molpipeline.mol2any import MolToMorganFP, MolToRDKitPhysChem, MolToSmiles
+from molpipeline.utils.molpipeline_types import OptionalMol, RDKitMol
 from tests.utils.mock_element import MockTransformingPipelineElement
 
 rdlog = RDLogger.logger()
@@ -247,3 +251,43 @@ def test_replace_mixed_datatypes_expected_failures(self) -> None:
         self.assertRaises(ValueError, pipeline.fit, test_values)
         self.assertRaises(ValueError, pipeline.transform, test_values)
         self.assertRaises(ValueError, pipeline2.fit_transform, test_values)
+
+    def test_molsanitize_error(self) -> None:
+        """Test if MolSanitizeException is caught and catched by ErrorFilter."""
+
+        class DummyMolSanitizeExc(MolToMolPipelineElement):
+            """MolToMolPipelineElement with dummy molsanitize exception."""
+
+            def pretransform_single(self, value: RDKitMol) -> OptionalMol:
+                """Dummy Mol.
+
+                Parameters
+                ----------
+                value: RDKitMol
+                    Molecule.
+
+                Returns
+                -------
+                OptionalMol
+                    Molecule.
+                """
+                if Chem.MolToSmiles(value) == "c1ccccc1":
+                    raise MolSanitizeException("This is a dummy exception.")
+                return value
+
+        pipeline = Pipeline(
+            [
+                ("autotosmiles", AutoToMol()),
+                ("atomneutralizer", DummyMolSanitizeExc()),
+                ("moltosmiles", MolToSmiles()),
+                ("errorfilter", error_filter := ErrorFilter()),
+                (
+                    "filterreinserter",
+                    FilterReinserter.from_error_filter(error_filter, None),
+                ),
+            ],
+            n_jobs=-1,
+        )
+
+        result = pipeline.transform(["c1ccccc1", "CCCCCCC", "c1cc"])
+        self.assertEqual(result, [None, "CCCCCCC", None])