Use get to avoid nesting ifs

sdmetrics/single_table/detection/base.py

@@ -52,22 +52,17 @@ def _drop_non_compute_columns(real_data, synthetic_data, metadata):
         if metadata is not None:
             drop_columns = []
             drop_columns.extend(get_alternate_keys(metadata))
-            if 'columns' in metadata:
-                for column in metadata['columns']:
-                    if ('primary_key' in metadata and
-                            (column == metadata['primary_key'] or
-                             column in metadata['primary_key'])):
-                        drop_columns.append(column)
-
-                    for field in metadata['columns'][column]:
-                        if field == 'sdtype':
-                            sdtype = metadata['columns'][column][field]
-                            if sdtype not in ['numerical', 'datetime', 'categorical']:
-                                drop_columns.append(column)
-
-                        if field == 'pii':
-                            if metadata['columns'][column][field]:
-                                drop_columns.append(column)
+            for column in metadata.get('columns', []):
+                if ('primary_key' in metadata and
+                        (column == metadata['primary_key'] or
+                         column in metadata['primary_key'])):
+                    drop_columns.append(column)
+
+                column_info = metadata['columns'].get(column, {})
+                sdtype = column_info.get('sdtype')
+                pii = column_info.get('pii')
+                if sdtype not in ['numerical', 'datetime', 'categorical'] or pii:
+                    drop_columns.append(column)
 
             if drop_columns:
                 transformed_real_data = real_data.drop(drop_columns, axis=1)