adds explanatory error message to check_input decorator (#86)

* adds explanatory error message to check decorators and tests

* adds more explicit error message

pandera/pandera.py

@@ -999,7 +999,21 @@ def check_input(
     def _wrapper(fn, instance, args, kwargs):
         args = list(args)
         if isinstance(obj_getter, int):
-            args[obj_getter] = schema.validate(args[obj_getter])
+            try:
+                args[obj_getter] = schema.validate(args[obj_getter])
+            except IndexError as e:
+                raise SchemaError(
+                        "error in check_input decorator of function '%s': the "
+                        "index '%s' was supplied to the check but this "
+                        "function accepts '%s' arguments, so the maximum "
+                        "index is '%s'. The full error is: '%s'" %
+                        (fn.__name__,
+                         obj_getter,
+                         len(_get_fn_argnames(fn)),
+                         max(0, len(_get_fn_argnames(fn))-1),
+                         e
+                         )
+                        )
         elif isinstance(obj_getter, str):
             if obj_getter in kwargs:
                 kwargs[obj_getter] = schema.validate(kwargs[obj_getter])

tests/test_pandera.py

@@ -230,6 +230,9 @@ def test_func4(x, dataframe):
 
 
 def test_check_function_decorator_errors():
+    """Test that the check_input and check_output decorators error properly."""
+    # case 1: checks that the input and output decorators error when different
+    # types are passed in and out
     @check_input(DataFrameSchema({"column1": Column(Int)}))
     @check_output(DataFrameSchema({"column2": Column(Float)}))
     def test_func(df):
@@ -245,6 +248,19 @@ def test_func(df):
             match=r"^error in check_output decorator of function"):
         test_func(pd.DataFrame({"column1": [1, 2, 3]}))
 
+    # case 2: check that if the input decorator refers to an index that's not
+    # in the function signature, it will fail in a way that's easy to interpret
+    @check_input(DataFrameSchema({"column1": Column(Int)}), 1)
+    def test_incorrect_check_input_index(df):
+        return df
+
+    with pytest.raises(
+            SchemaError,
+            match=r"^error in check_input decorator of function"
+            ):
+        test_incorrect_check_input_index(pd.DataFrame({"column1": [1, 2, 3]})
+                                         )
+
 
 def test_check_function_decorator_transform():
     """Test that transformer argument is in effect in check_input decorator."""