types fixup for #25

countess/core/plugins.py

@@ -453,7 +453,7 @@ class PandasTransformSingleToTuplePlugin(
 ):
     """Transformer which takes a single column and returns a tuple of values"""
 
-    def process_value(self, value, logger: Logger):
+    def process_value(self, value, logger: Logger) -> Optional[Iterable]:
         raise NotImplementedError(f"{self.__class__}.process_value()")
 
 
@@ -462,7 +462,7 @@ class PandasTransformSingleToDictPlugin(
 ):
     """Transformer which takes a single column and returns a dictionary of values"""
 
-    def process_value(self, value, logger: Logger):
+    def process_value(self, value, logger: Logger) -> Optional[Dict]:
         raise NotImplementedError(f"{self.__class__}.process_value()")
 
 

countess/plugins/regex.py

@@ -54,10 +54,6 @@ def process_dataframe(self, dataframe: pd.DataFrame, logger: Logger) -> pd.DataF
         assert isinstance(self.parameters["output"], ArrayParam)
         df = super().process_dataframe(dataframe, logger)
 
-        #if self.parameters["drop_unmatch"].value:
-        #    output_names = [pp.name.value for pp in self.parameters["output"]]
-        #    df = df.dropna(subset=output_names, how="all")
-
         if self.parameters["drop_column"].value:
             column_name = self.parameters["column"].value
             if column_name in df.columns:
@@ -75,7 +71,7 @@ def process_dataframe(self, dataframe: pd.DataFrame, logger: Logger) -> pd.DataF
 
         return df
 
-    def process_value(self, value: str, logger: Logger) -> Iterable:
+    def process_value(self, value: str, logger: Logger) -> Optional[Iterable]:
         assert self.compiled_re is not None
         assert isinstance(self.parameters["output"], ArrayParam)
         if value is not None:
@@ -90,7 +86,7 @@ def process_value(self, value: str, logger: Logger) -> Iterable:
         # If dropping unmatched values, return a simple None which will
         # be filtered out in series_to_dataframe below, otherwise return
         # a tuple of Nones which will fill in the unmatched row.
-        
+
         if self.parameters["drop_unmatch"].value:
             return None
         else:
@@ -103,6 +99,7 @@ def series_to_dataframe(self, series: pd.Series) -> pd.DataFrame:
             series.dropna(inplace=True)
         return super().series_to_dataframe(series)
 
+
 class RegexReaderPlugin(PandasInputPlugin):
     name = "Regex Reader"
     description = "Loads arbitrary data from line-delimited files"