New error cases for custom functions

evadb/expression/function_expression.py

@@ -187,6 +187,10 @@ def _apply_function_expression(self, func: Callable, batch: Batch, **kwargs):
         if not self._cache:
             return func_args.apply_function_expression(func)
 
+        for column_name, obj_column in zip(func_args.columns, self.function_obj.args):
+            if obj_column.name != column_name:
+                raise RuntimeError(f"Column name {column_name} is not matching")
+
         output_cols = [obj.name for obj in self.function_obj.outputs]
 
         # 1. check cache

evadb/functions/decorators/utils.py

@@ -16,6 +16,7 @@
 
 from evadb.catalog.models.function_io_catalog import FunctionIOCatalogEntry
 from evadb.functions.abstract.abstract_function import AbstractFunction
+from evadb.executor.executor_utils import ExecutorError
 
 
 def load_io_from_function_decorators(
@@ -45,7 +46,13 @@ def load_io_from_function_decorators(
 
     assert (
         io_signature is not None
-    ), f"Cannot infer io signature from the decorator for {function}."
+    ), f"No io signature was given for function {function}."
+
+    if len(io_signature) > 1:
+        if is_input:
+            raise ExecutorError("forward method can only have single DataFrame as input")
+        else:
+            raise ExecutorError("forward method can only output single DataFrame")
 
     result_list = []
     for io in io_signature:

evadb/functions/test_invalid_signature_input.py

@@ -0,0 +1,52 @@
+import pandas as pd
+
+from evadb.catalog.catalog_type import ColumnType, NdArrayType
+from evadb.functions.abstract.abstract_function import AbstractFunction
+from evadb.functions.decorators.decorators import forward, setup
+from evadb.functions.decorators.io_descriptors.data_types import PandasDataframe
+
+class InvalidSignatureInput(AbstractFunction):
+    """
+    Arguments:
+        None
+
+    Input Signatures:
+        multiple input dataframes which is an invalid input signature
+    """
+    @property
+    def name(self) -> str:
+        return "InvalidSignature"
+
+    @setup(cacheable=False)
+    def setup(self) -> None:
+        # Any setup or initialization can be done here if needed
+        pass
+
+    @forward(
+        input_signatures=[
+            PandasDataframe(
+                columns=["col1", "col2"],
+                column_types=[NdArrayType.STR, NdArrayType.STR],
+                column_shapes=[(None,), (None,)],
+            ),
+            PandasDataframe(
+                columns=["col1", "col2"],
+                column_types=[NdArrayType.STR, NdArrayType.STR],
+                column_shapes=[(None,), (None,)],
+            )
+        ],
+        output_signatures=[
+            PandasDataframe(
+                columns=["data1", "data2"],
+                column_types=[NdArrayType.STR, NdArrayType.STR],
+                column_shapes=[(None,), (None,)],
+            )
+        ],
+    )
+    def forward(self, input_df):
+        # Create a DataFrame from the parsed data
+        ans = []
+        ans.append({'data1': 'data1', 'data2': 'data2'})
+        output_dataframe = pd.DataFrame(ans, columns=['data1', 'data2'])
+
+        return output_dataframe

evadb/functions/test_invalid_signature_output.py

@@ -0,0 +1,53 @@
+import pandas as pd
+
+from evadb.catalog.catalog_type import ColumnType, NdArrayType
+from evadb.functions.abstract.abstract_function import AbstractFunction
+from evadb.functions.decorators.decorators import forward, setup
+from evadb.functions.decorators.io_descriptors.data_types import PandasDataframe
+
+class InvalidSignatureInput(AbstractFunction):
+    """
+    Arguments:
+        None
+
+    Input Signatures:
+        multiple input dataframes which is an invalid input signature
+    """
+    @property
+    def name(self) -> str:
+        return "InvalidSignature"
+
+    @setup(cacheable=False)
+    def setup(self) -> None:
+        # Any setup or initialization can be done here if needed
+        pass
+
+    @forward(
+        input_signatures=[
+            PandasDataframe(
+                columns=["col1", "col2"],
+                column_types=[NdArrayType.STR, NdArrayType.STR],
+                column_shapes=[(None,), (None,)],
+            )
+        ],
+        output_signatures=[
+            PandasDataframe(
+                columns=["data1", "data2"],
+                column_types=[NdArrayType.STR, NdArrayType.STR],
+                column_shapes=[(None,), (None,)],
+            ),
+            PandasDataframe(
+                columns=["data1", "data2"],
+                column_types=[NdArrayType.STR, NdArrayType.STR],
+                column_shapes=[(None,), (None,)],
+            )
+        ],
+    )
+    def forward(self, input_df):
+        # Create a DataFrame from the parsed data
+        ans = []
+        ans.append({'data1': 'data1', 'data2': 'data2'})
+        output_dataframe = pd.DataFrame(ans, columns=['data1', 'data2'])
+        output_df_2 = pd.DataFrame(ans, columns=['data1', 'data2'])
+
+        return output_dataframe, output_df_2

evadb/utils/generic_utils.py

@@ -84,9 +84,12 @@ def load_function_class_from_file(filepath, classname=None):
         spec = importlib.util.spec_from_file_location(abs_path.stem, abs_path)
         module = importlib.util.module_from_spec(spec)
         spec.loader.exec_module(module)
+    except ModuleNotFoundError as e:
+        err_msg = f"ModuleNotFoundError : Couldn't load function from {filepath} : {str(e)}. Not able to load the code provided in the file {abs_path}. Please ensure that the file contains the implementation code for the function."
+        raise ModuleNotFoundError(err_msg)
     except ImportError as e:
         # ImportError in the case when we are able to find the file but not able to load the module
-        err_msg = f"ImportError : Couldn't load function from {filepath} : {str(e)}. Not able to load the code provided in the file {abs_path}. Please ensure that the file contains the implementation code for the function."
+        err_msg = f"ImportError : Couldn't load function from {filepath} : {str(e)}. Please ensure that all the correct packages are installed correctly."
         raise ImportError(err_msg)
     except FileNotFoundError as e:
         # FileNotFoundError in the case when we are not able to find the file at all at the path.

test/integration_tests/long/test_function_executor.py

@@ -321,6 +321,20 @@ def test_should_raise_if_function_file_is_modified(self):
             # disabling warning for function modification for now
             # with self.assertRaises(AssertionError):
             execute_query_fetch_all(self.evadb, select_query)
+
+    def test_should_raise_with_multiple_input_dataframes(self):
+        with self.assertRaises(ExecutorError) as cm:
+            execute_query_fetch_all(
+                self.evadb, "CREATE FUNCTION IF NOT EXISTS InvalidInput IMPL 'evadb/functions/test_invalid_signature_input.py'"
+            )
+        self.assertEqual(str(cm.exception), "forward method can only have single DataFrame as input")
+
+    def test_should_raise_with_multiple_output_dataframes(self):
+        with self.assertRaises(ExecutorError) as cm:
+            execute_query_fetch_all(
+                self.evadb, "CREATE FUNCTION IF NOT EXISTS InvalidOutput IMPL 'evadb/functions/test_invalid_signature_output.py'"
+            )
+        self.assertEqual(str(cm.exception), "forward method can only output single DataFrame")
 
     def test_create_function_with_decorators(self):
         execute_query_fetch_all(