default to raising error when column to be renamed cannot be found

pyterrier/apply.py

@@ -117,18 +117,19 @@ def _features(row):
     """
     return ApplyDocFeatureTransformer(fn, *args, **kwargs)
 
-def rename(columns : Dict[str,str], *args, **kwargs) -> Transformer:
+def rename(columns : Dict[str,str], *args, errors='raise', **kwargs) -> Transformer:
     """
         Creates a transformer that renames columns in a dataframe. 
 
         Args:
-            columns(dict): A dictionary mapping from old column name to new column name 
+            columns(dict): A dictionary mapping from old column name to new column name
+            errors(str): Maps to df.rename() errors kwarg - default to 'raise', alternatively can be 'ignore'
 
         Example::
             
             pipe = pt.BatchRetrieve(index, metadata=["docno", "body"]) >> pt.apply.rename({'body':'text'})
     """
-    return ApplyGenericTransformer(lambda df: df.rename(columns=columns), *args, **kwargs)
+    return ApplyGenericTransformer(lambda df: df.rename(columns=columns, errors=errors), *args, **kwargs)
 
 def generic(fn : Callable[[pd.DataFrame], pd.DataFrame], *args, batch_size=None, **kwargs) -> Transformer:
     """

tests/test_apply.py

@@ -38,6 +38,11 @@ def test_rename_columns(self):
         rtr = p(testDF)
         self.assertTrue("Bla2" in rtr.columns)
         self.assertFalse("Bla" in rtr.columns)
+        with self.assertRaises(KeyError):
+            testDF2 = pd.DataFrame([["q1", "the bear and the wolf", 1]], columns=["qid", "query", "Bla2"])
+            rtr = p(testDF2)
+        p_ignore = pt.apply.rename({'Bla' : "Bla2"}, errors='ignore')
+        rtr = p_ignore(testDF2)
 
     def test_query_apply(self):
         stops=set(["and", "the"])