googleapis · tswast · May 30, 2024 · May 29, 2024 · May 29, 2024 · May 30, 2024
@@ -14,6 +14,7 @@
 
 from __future__ import annotations
 
+import collections.abc
 import hashlib
 import inspect
 import logging
@@ -1043,6 +1044,8 @@ def wrapper(func):
                         "Types are required to use @remote_function."
                     )
                 input_types.append(param_type)
+        elif not isinstance(input_types, collections.abc.Sequence):
+            input_types = [input_types]
 
         if output_type is None:
             if (output_type := signature.return_annotation) is inspect.Signature.empty:
@@ -1055,9 +1058,12 @@ def wrapper(func):
         # The function will actually be receiving a pandas Series, but allow both
         # BigQuery DataFrames and pandas object types for compatibility.
         is_row_processor = False
-        if input_types == bigframes.series.Series or input_types == pandas.Series:
+        if len(input_types) == 1 and (
+            (input_type := input_types[0]) == bigframes.series.Series
+            or input_type == pandas.Series
+        ):
             warnings.warn(
-                "input_types=Series scenario is in preview.",
+                "input_types=Series is in preview.",
                 stacklevel=1,
                 category=bigframes.exceptions.PreviewWarning,
             )

@@ -727,7 +727,7 @@ def add_ints(row):
 
     with pytest.warns(
         bigframes.exceptions.PreviewWarning,
-        match="input_types=Series scenario is in preview.",
+        match="input_types=Series is in preview.",
     ):
         add_ints_remote = session.remote_function(bigframes.series.Series, int)(
             add_ints

@@ -23,6 +23,7 @@
 import pytest
 
 import bigframes
+import bigframes.clients
 import bigframes.core as core
 import bigframes.core.ordering
 import bigframes.dataframe
@@ -97,6 +98,9 @@ def query_mock(query, *args, **kwargs):
 
     bqoptions = bigframes.BigQueryOptions(credentials=credentials, location=location)
     session = bigframes.Session(context=bqoptions, clients_provider=clients_provider)
+    session._bq_connection_manager = mock.create_autospec(
+        bigframes.clients.BqConnectionManager, instance=True
+    )
     return session
 
 

@@ -12,15 +12,53 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import re
+
 import bigframes_vendored.ibis.backends.bigquery.datatypes as third_party_ibis_bqtypes
 from ibis.expr import datatypes as ibis_types
+import pandas
 import pytest
 
 import bigframes.dtypes
 import bigframes.functions.remote_function
+import bigframes.series
 from tests.unit import resources
 
 
+@pytest.mark.parametrize(
+    "series_type",
+    (
+        pytest.param(
+            pandas.Series,
+            id="pandas.Series",
+        ),
+        pytest.param(
+            bigframes.series.Series,
+            id="bigframes.series.Series",
+        ),
+    ),
+)
+def test_series_input_types_to_str(series_type):
+    """Check that is_row_processor=True uses str as the input type to serialize a row."""
+    session = resources.create_bigquery_session()
+    remote_function_decorator = bigframes.functions.remote_function.remote_function(
+        session=session
+    )
+
+    with pytest.warns(
+        bigframes.exceptions.PreviewWarning,
+        match=re.escape("input_types=Series is in preview."),
+    ):
+
+        @remote_function_decorator
+        def axis_1_function(myparam: series_type) -> str:  # type: ignore
+            return "Hello, " + myparam["str_col"] + "!"  # type: ignore
+
+    # Still works as a normal function.
+    assert axis_1_function(pandas.Series({"str_col": "World"})) == "Hello, World!"
+    assert axis_1_function.ibis_node is not None
+
+
 def test_supported_types_correspond():
     # The same types should be representable by the supported Python and BigQuery types.
     ibis_types_from_python = {

@@ -3969,7 +3969,7 @@ def map(
 
         It also accepts a remote function:
 
-            >>> @bpd.remote_function
+            >>> @bpd.remote_function()
             ... def my_mapper(val: str) -> str:
             ...     vowels = ["a", "e", "i", "o", "u"]
             ...     if val: