update

google/cloud/bigquery/_pandas_helpers.py

@@ -47,13 +47,10 @@
     date_dtype_name = time_dtype_name = ""  # Use '' rather than None because pytype
 
 try:
-    import pyarrow  # type: ignore
-    import pyarrow.parquet  # type: ignore
-
-    pyarrow_import_exception = None
-except ImportError as exc:  # pragma: NO COVER
+    import pyarrow
+    import pyarrow.parquet
+except ImportError:  # pragma: NO COVER
     pyarrow = None
-    pyarrow_import_exception = exc
 
 try:
     # _BaseGeometry is used to detect shapely objevys in `bq_to_arrow_array`
@@ -93,6 +90,7 @@ def _to_wkb(v):
 
 from google.cloud.bigquery import schema
 
+pyarrow = _helpers.PYARROW_VERSIONS.try_import()
 
 _LOGGER = logging.getLogger(__name__)
 
@@ -104,6 +102,11 @@ def _to_wkb(v):
 _NO_DB_TYPES_ERROR = "Please install the 'db-dtypes' package to use this function."
 _NO_PYARROW_ERROR = "Please install the 'pyarrow' package to use this function."
 
+_NO_BQSTORAGE_ERROR = (
+    "The google-cloud-bigquery-storage library is not installed, "
+    "please install google-cloud-bigquery-storage to use bqstorage features."
+)
+
 _PANDAS_DTYPE_TO_BQ = {
     "bool": "BOOLEAN",
     "datetime64[ns, UTC]": "TIMESTAMP",
@@ -691,10 +694,9 @@ def dataframe_to_parquet(
 
             This argument is ignored for ``pyarrow`` versions earlier than ``4.0.0``.
     """
-    global pyarrow
-    if pyarrow is None:
-        raise ValueError("pyarrow is required for BigQuery schema conversion.")
-    import pyarrow.parquet  # type: ignore
+    pyarrow = _helpers.PYARROW_VERSIONS.try_import(raise_if_error=True)
+
+    import pyarrow.parquet
 
     kwargs = (
         {"use_compliant_nested_type": parquet_use_compliant_nested_type}
@@ -1019,8 +1021,6 @@ def dataframe_to_json_generator(dataframe):
 
 
 def verify_pandas_imports():
-    if pyarrow is None:
-        raise ValueError(_NO_PYARROW_ERROR) from pyarrow_import_exception
     if pandas is None:
         raise ValueError(_NO_PANDAS_ERROR) from pandas_import_exception
     if db_dtypes is None:

tests/unit/job/test_query_pandas.py

@@ -22,17 +22,16 @@
 # import google.cloud.bigquery_storage_v1.reader
 # import google.cloud.bigquery_storage_v1.services.big_query_read.client
 
-try:
-    import pyarrow
-except (ImportError, AttributeError):  # pragma: NO COVER
-    pyarrow = None
+
 try:
     from google.cloud import bigquery_storage
     import google.cloud.bigquery_storage_v1.reader
     import google.cloud.bigquery_storage_v1.services.big_query_read.client
 except (ImportError, AttributeError):  # pragma: NO COVER
     bigquery_storage = None
 
+from google.cloud.bigquery import _helpers
+
 try:
     import pandas
 except (ImportError, AttributeError):  # pragma: NO COVER
@@ -56,6 +55,8 @@
 
 pandas = pytest.importorskip("pandas")
 
+pyarrow = _helpers.PYARROW_VERSIONS.try_import()
+
 
 @pytest.fixture
 def table_read_options_kwarg():

tests/unit/test__pandas_helpers.py

@@ -44,10 +44,10 @@
 from google.cloud.bigquery import schema
 from google.cloud.bigquery._pandas_helpers import _BIGNUMERIC_SUPPORT
 
-try:
-    import pyarrow
+pyarrow = _helpers.PYARROW_VERSIONS.try_import()
+if pyarrow:
     import pyarrow.types
-except ImportError:  # pragma: NO COVER
+else:  # pragma: NO COVER
     # Mock out pyarrow when missing, because methods from pyarrow.types are
     # used in test parameterization.
     pyarrow = mock.Mock()

tests/unit/test_dbapi__helpers.py

@@ -21,6 +21,11 @@
 
 import pytest
 
+try:
+    import pyarrow
+except ImportError:  # pragma: NO COVER
+    pyarrow = None
+
 import google.cloud._helpers
 from google.cloud.bigquery import query, table
 from google.cloud.bigquery.dbapi import _helpers
@@ -210,6 +215,7 @@ def test_empty_iterable(self):
         result = _helpers.to_bq_table_rows(rows_iterable)
         self.assertEqual(list(result), [])
 
+    @unittest.skipIf(pyarrow is None, "Requires `pyarrow`")
     def test_non_empty_iterable(self):
         rows_iterable = [
             dict(

tests/unit/test_table.py

@@ -28,6 +28,7 @@
 from test_utils.imports import maybe_fail_import
 
 from google.cloud.bigquery.table import TableReference
+from google.cloud.bigquery.dataset import DatasetReference
 
 try:
     from google.cloud import bigquery_storage
@@ -38,14 +39,15 @@
     bigquery_storage = None
     big_query_read_grpc_transport = None
 
-try:
-    import pyarrow
+from google.cloud.bigquery import _helpers
+
+
+pyarrow = _helpers.PYARROW_VERSIONS.try_import()
+PYARROW_VERSION = pkg_resources.parse_version("0.0.1")
+if pyarrow:
     import pyarrow.types
 
     PYARROW_VERSION = pkg_resources.parse_version(pyarrow.__version__)
-except ImportError:  # pragma: NO COVER
-    pyarrow = None
-    PYARROW_VERSION = pkg_resources.parse_version("0.0.1")
 
 try:
     import pandas
@@ -62,8 +64,6 @@
 except (ImportError, AttributeError):  # pragma: NO COVER
     tqdm = None
 
-from google.cloud.bigquery.dataset import DatasetReference
-
 PYARROW_TIMESTAMP_VERSION = pkg_resources.parse_version("2.0.0")