Fix: Error handling for forward() to only take one pandas dataframe

evadb/functions/decorators/utils.py

@@ -15,6 +15,7 @@
 from typing import List, Type
 
 from evadb.catalog.models.function_io_catalog import FunctionIOCatalogEntry
+from evadb.executor.executor_utils import ExecutorError
 from evadb.functions.abstract.abstract_function import AbstractFunction
 
 
@@ -47,6 +48,10 @@ def load_io_from_function_decorators(
         io_signature is not None
     ), f"Cannot infer io signature from the decorator for {function}."
 
+    # added error check when forward() takes more than one pandas dataframe
+    if len(io_signature) > 1:
+        raise ExecutorError("forward() only takes one pandas dataframe as input.")
+
     result_list = []
     for io in io_signature:
         result_list.extend(io.generate_catalog_entries(is_input))

evadb/functions/test_bad_fuzzyjoin_udf.py

@@ -0,0 +1,81 @@
+# coding=utf-8
+# Copyright 2018-2023 EvaDB
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+# coding=utf-8
+# Copyright 2018-2022 EVA
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import numpy as np
+import pandas as pd
+from thefuzz import fuzz
+
+from evadb.catalog.catalog_type import 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 FuzzDistance(AbstractFunction):
+    @setup(cacheable=False, function_type="FeatureExtraction", batchable=False)
+    def setup(self):
+        pass
+
+    @property
+    def name(self) -> str:
+        return "FuzzDistance"
+
+    @forward(
+        input_signatures=[
+            PandasDataframe(
+                columns=["data1", "data2"],
+                column_types=[NdArrayType.STR, NdArrayType.STR],
+                column_shapes=[(1), (1)],
+            ),
+            # Incorrectly tries to use multiple DataFrames
+            PandasDataframe(
+                columns=["data3", "data4"],
+                column_types=[NdArrayType.STR, NdArrayType.STR],
+                column_shapes=[(1), (1)],
+            ),
+        ],
+        output_signatures=[
+            PandasDataframe(
+                columns=["distance"],
+                column_types=[NdArrayType.FLOAT32],
+                column_shapes=[(1)],
+            )
+        ],
+    )
+    def forward(self, df: pd.DataFrame) -> pd.DataFrame:
+        def _forward(row: pd.Series) -> np.ndarray:
+            data1 = row.iloc[0]
+            data2 = row.iloc[1]
+            distance = fuzz.ratio(data1, data2)
+            return distance
+
+        ret = pd.DataFrame()
+        ret["distance"] = df.apply(_forward, axis=1)
+        return ret

test/integration_tests/long/test_function_executor.py

@@ -322,6 +322,22 @@ def test_should_raise_if_function_file_is_modified(self):
             # with self.assertRaises(AssertionError):
             execute_query_fetch_all(self.evadb, select_query)
 
+    def test_should_raise_error_for_multiple_dataframes(self):
+        # Checks for an error when multiple dataframes are used
+        create_function_query = """
+            CREATE FUNCTION IF NOT EXISTS FuzzDistance
+            IMPL 'evadb/functions/test_bad_fuzzyjoin_udf.py'
+        """
+        # Expect ExecutorError
+        with self.assertRaises(ExecutorError) as cm:
+            execute_query_fetch_all(
+                self.evadb, create_function_query, do_not_print_exceptions=True
+            )
+
+        # Check if the expected error message is in the exception
+        expected_error_msg = "forward() only takes one pandas dataframe as input."
+        self.assertIn(expected_error_msg, str(cm.exception))
+
     def test_create_function_with_decorators(self):
         execute_query_fetch_all(
             self.evadb, "DROP FUNCTION IF EXISTS DummyObjectDetectorDecorators;"