fix(deps): raise exception when pandas is installed but db-dtypes is not

google/cloud/bigquery/_pandas_helpers.py

@@ -24,16 +24,25 @@
 
 try:
     import pandas  # type: ignore
-except ImportError:  # pragma: NO COVER
+
+    pandas_import_exception = None
+except ImportError as exc:  # pragma: NO COVER
     pandas = None
-    date_dtype_name = time_dtype_name = ""  # Use '' rather than None because pytype
+    pandas_import_exception = exc
 else:
     import numpy
 
-    from db_dtypes import DateDtype, TimeDtype  # type: ignore
+try:
+    import db_dtypes  # type: ignore
+
+    date_dtype_name = db_dtypes.DateDtype.name
+    time_dtype_name = db_dtypes.TimeDtype.name
+    db_dtypes_import_exception = None
+except ImportError as exc:  # pragma: NO COVER
+    db_dtypes = None
+    db_dtypes_import_exception = exc
+    date_dtype_name = time_dtype_name = ""  # Use '' rather than None because pytype
 
-    date_dtype_name = DateDtype.name
-    time_dtype_name = TimeDtype.name
 
 import pyarrow  # type: ignore
 import pyarrow.parquet  # type: ignore
@@ -84,6 +93,9 @@ def _to_wkb(v):
 
 _MAX_QUEUE_SIZE_DEFAULT = object()  # max queue size sentinel for BQ Storage downloads
 
+_NO_PANDAS_ERROR = "Please install the 'pandas' package to use this function."
+_NO_DB_TYPES_ERROR = "Please install the 'db-dtypes' package to use this function."
+
 _PANDAS_DTYPE_TO_BQ = {
     "bool": "BOOLEAN",
     "datetime64[ns, UTC]": "TIMESTAMP",
@@ -290,13 +302,13 @@ def types_mapper(arrow_data_type):
             not date_as_object
             and pyarrow.types.is_date(arrow_data_type)
         ):
-            return DateDtype()
+            return db_dtypes.DateDtype()
 
         elif pyarrow.types.is_integer(arrow_data_type):
             return pandas.Int64Dtype()
 
         elif pyarrow.types.is_time(arrow_data_type):
-            return TimeDtype()
+            return db_dtypes.TimeDtype()
 
     return types_mapper
 
@@ -970,3 +982,10 @@ def dataframe_to_json_generator(dataframe):
             output[column] = value
 
         yield output
+
+
+def verify_pandas_imports():
+    if pandas is None:
+        raise ValueError(_NO_PANDAS_ERROR) from pandas_import_exception
+    if db_dtypes is None:
+        raise ValueError(_NO_DB_TYPES_ERROR) from db_dtypes_import_exception

google/cloud/bigquery/table.py

@@ -28,8 +28,6 @@
     import pandas  # type: ignore
 except ImportError:  # pragma: NO COVER
     pandas = None
-else:
-    import db_dtypes  # type: ignore # noqa
 
 import pyarrow  # type: ignore
 
@@ -69,10 +67,6 @@
     from google.cloud.bigquery.dataset import DatasetReference
 
 
-_NO_PANDAS_ERROR = (
-    "The pandas library is not installed, please install "
-    "pandas to use the to_dataframe() function."
-)
 _NO_GEOPANDAS_ERROR = (
     "The geopandas library is not installed, please install "
     "geopandas to use the to_geodataframe() function."
@@ -1818,8 +1812,8 @@ def to_dataframe_iterable(
             ValueError:
                 If the :mod:`pandas` library cannot be imported.
         """
-        if pandas is None:
-            raise ValueError(_NO_PANDAS_ERROR)
+        _pandas_helpers.verify_pandas_imports()
+
         if dtypes is None:
             dtypes = {}
 
@@ -1928,8 +1922,8 @@ def to_dataframe(
                 :mod:`shapely` library cannot be imported.
 
         """
-        if pandas is None:
-            raise ValueError(_NO_PANDAS_ERROR)
+        _pandas_helpers.verify_pandas_imports()
+
         if geography_as_object and shapely is None:
             raise ValueError(_NO_SHAPELY_ERROR)
 
@@ -2181,8 +2175,7 @@ def to_dataframe(
         Returns:
             pandas.DataFrame: An empty :class:`~pandas.DataFrame`.
         """
-        if pandas is None:
-            raise ValueError(_NO_PANDAS_ERROR)
+        _pandas_helpers.verify_pandas_imports()
         return pandas.DataFrame()
 
     def to_geodataframe(
@@ -2238,8 +2231,7 @@ def to_dataframe_iterable(
             ValueError:
                 If the :mod:`pandas` library cannot be imported.
         """
-        if pandas is None:
-            raise ValueError(_NO_PANDAS_ERROR)
+        _pandas_helpers.verify_pandas_imports()
         return iter((pandas.DataFrame(),))
 
     def to_arrow_iterable(

tests/unit/test__pandas_helpers.py

@@ -1751,3 +1751,15 @@ def test_bq_to_arrow_field_metadata(module_under_test, field_type, metadata):
         ).metadata
         == metadata
     )
+
+
+def test_verify_pandas_imports_no_pandas(module_under_test, monkeypatch):
+    monkeypatch.setattr(module_under_test, "pandas", None)
+    with pytest.raises(ValueError, match="Please install the 'pandas' package"):
+        module_under_test.verify_pandas_imports()
+
+
+def test_verify_pandas_imports_no_db_dtypes(module_under_test, monkeypatch):
+    monkeypatch.setattr(module_under_test, "db_dtypes", None)
+    with pytest.raises(ValueError, match="Please install the 'db-dtypes' package"):
+        module_under_test.verify_pandas_imports()

tests/unit/test_table.py

@@ -1836,7 +1836,7 @@ def test_to_arrow_iterable(self):
         self.assertEqual(record_batch.num_rows, 0)
         self.assertEqual(record_batch.num_columns, 0)
 
-    @mock.patch("google.cloud.bigquery.table.pandas", new=None)
+    @mock.patch("google.cloud.bigquery._pandas_helpers.pandas", new=None)
     def test_to_dataframe_error_if_pandas_is_none(self):
         row_iterator = self._make_one()
         with self.assertRaises(ValueError):
@@ -1849,7 +1849,7 @@ def test_to_dataframe(self):
         self.assertIsInstance(df, pandas.DataFrame)
         self.assertEqual(len(df), 0)  # verify the number of rows
 
-    @mock.patch("google.cloud.bigquery.table.pandas", new=None)
+    @mock.patch("google.cloud.bigquery._pandas_helpers.pandas", new=None)
     def test_to_dataframe_iterable_error_if_pandas_is_none(self):
         row_iterator = self._make_one()
         with self.assertRaises(ValueError):
@@ -2967,7 +2967,7 @@ def test_to_dataframe_iterable_w_bqstorage_max_results_warning(self):
         assert isinstance(dataframes[0], pandas.DataFrame)
         assert isinstance(dataframes[1], pandas.DataFrame)
 
-    @mock.patch("google.cloud.bigquery.table.pandas", new=None)
+    @mock.patch("google.cloud.bigquery._pandas_helpers.pandas", new=None)
     def test_to_dataframe_iterable_error_if_pandas_is_none(self):
         from google.cloud.bigquery.schema import SchemaField
 
@@ -3339,7 +3339,7 @@ def test_to_dataframe_datetime_objects(self):
         self.assertEqual(df["ts"][0].date(), datetime.date(1336, 3, 23))
         self.assertEqual(df["date"][0], datetime.date(1111, 1, 1))
 
-    @mock.patch("google.cloud.bigquery.table.pandas", new=None)
+    @mock.patch("google.cloud.bigquery._pandas_helpers.pandas", new=None)
     def test_to_dataframe_error_if_pandas_is_none(self):
         from google.cloud.bigquery.schema import SchemaField