Fixes a crash you can run into with postgres array columns.

piicatcher_spacy/detectors/spacy.py

@@ -15,32 +15,35 @@
 @register_detector
 class SpacyDetector(DatumDetector):
     pii_cls_map = {
-        'FAC': Address,      # Buildings, airports, highways, bridges, etc.
-        'GPE': Address,      # Countries, cities, states.
-        'LOC': Address,      # Non-GPE locations, mountain ranges, bodies of water.
-        'PERSON': Person,       # People, including fictional.
-        'PER': Person,          # Bug in french model
-        'DATE': BirthDate,  # Dates within the period 18 to 100 years ago.
+        "FAC": Address,  # Buildings, airports, highways, bridges, etc.
+        "GPE": Address,  # Countries, cities, states.
+        "LOC": Address,  # Non-GPE locations, mountain ranges, bodies of water.
+        "PERSON": Person,  # People, including fictional.
+        "PER": Person,  # Bug in french model
+        "DATE": BirthDate,  # Dates within the period 18 to 100 years ago.
     }
-    name = 'DatumSpacyDetector'
+    name = "DatumSpacyDetector"
 
     def __init__(self, model: str = "en_core_web_md"):
         super(SpacyDetector, self).__init__()
 
         # Fixes a warning message from transformers that is pulled in via spacy
         import os
-        os.environ['TOKENIZERS_PARALLELISM'] = 'false'
+
+        os.environ["TOKENIZERS_PARALLELISM"] = "false"
         self.check_spacy_version()
 
         if not self.check_spacy_model(model):
-            raise ValueError("Unable to find spacy model '{}'. Is your language supported? "
-                             "Check the list of models available here: "
-                             "https://github.com/explosion/spacy-models ".format(self.model))
+            raise ValueError(
+                "Unable to find spacy model '{}'. Is your language supported? "
+                "Check the list of models available here: "
+                "https://github.com/explosion/spacy-models ".format(self.model)
+            )
 
         self.nlp = spacy.load(model)
 
         # If the model doesn't support named entity recognition
-        if 'ner' not in [step[0] for step in self.nlp.pipeline]:
+        if "ner" not in [step[0] for step in self.nlp.pipeline]:
             raise ValueError(
                 "The spacy model '{}' doesn't support named entity recognition, "
                 "please choose another model.".format(self.model)
@@ -49,16 +52,28 @@ def __init__(self, model: str = "en_core_web_md"):
     @staticmethod
     def check_spacy_version() -> bool:
         """Ensure that the version of spaCy is v3."""
-        spacy_version = spacy.__version__  # spacy_info.get('spaCy version', spacy_info.get('spacy_version', None))
+        spacy_version = (
+            spacy.__version__
+        )  # spacy_info.get('spaCy version', spacy_info.get('spacy_version', None))
 
         if spacy_version is None:
-            raise ImportError('Spacy v3 needs to be installed. Unable to detect spacy version.')
+            raise ImportError(
+                "Spacy v3 needs to be installed. Unable to detect spacy version."
+            )
         try:
-            spacy_major = int(spacy_version.split('.')[0])
+            spacy_major = int(spacy_version.split(".")[0])
         except Exception:
-            raise ImportError('Spacy v3 needs to be installed. Spacy version {} is unknown.'.format(spacy_version))
+            raise ImportError(
+                "Spacy v3 needs to be installed. Spacy version {} is unknown.".format(
+                    spacy_version
+                )
+            )
         if spacy_major != 3:
-            raise ImportError('Spacy v3 needs to be installed. Detected version {}.'.format(spacy_version))
+            raise ImportError(
+                "Spacy v3 needs to be installed. Detected version {}.".format(
+                    spacy_version
+                )
+            )
 
         return True
 
@@ -67,10 +82,12 @@ def check_spacy_model(model) -> bool:
         """Ensure that the spaCy model is installed."""
         spacy_info = spacy.info()
         if isinstance(spacy_info, str):
-            raise ValueError('Unable to detect spacy models.')
-        models = list(spacy_info.get('pipelines', spacy_info.get('models', None)).keys())
+            raise ValueError("Unable to detect spacy models.")
+        models = list(
+            spacy_info.get("pipelines", spacy_info.get("models", None)).keys()
+        )
         if models is None:
-            raise ValueError('Unable to detect spacy models.')
+            raise ValueError("Unable to detect spacy models.")
 
         if model not in models:
             LOGGER.info("Downloading spacy model {}".format(model))
@@ -83,6 +100,12 @@ def check_spacy_model(model) -> bool:
         return model in models
 
     def detect(self, column: CatColumn, datum: str) -> Optional[PiiType]:
+        # if datum can be a list, like in postgres arrays, recurse, otherwise we crash in language.py from spacy.
+        if isinstance(datum, list):
+            for d in datum:
+                result = self.detect(column, d)
+                if result:
+                    return result
         doc = self.nlp(datum)
         for ent in doc.ents:
             LOGGER.debug("Found %s", ent.label_)