test: Add test of datetime and time pandas load

tests/system/test_pandas.py

@@ -279,16 +279,14 @@ def test_load_table_from_dataframe_w_required(bigquery_client, dataset_id):
 
 def test_load_table_from_dataframe_w_explicit_schema(bigquery_client, dataset_id):
     # Schema with all scalar types.
-    # TODO: Uploading DATETIME columns currently fails, thus that field type
-    #       is temporarily  removed from the test.
     # See:
     #       https://github.com/googleapis/python-bigquery/issues/61
     #       https://issuetracker.google.com/issues/151765076
     scalars_schema = (
         bigquery.SchemaField("bool_col", "BOOLEAN"),
         bigquery.SchemaField("bytes_col", "BYTES"),
         bigquery.SchemaField("date_col", "DATE"),
-        # bigquery.SchemaField("dt_col", "DATETIME"),
+        bigquery.SchemaField("dt_col", "DATETIME"),
         bigquery.SchemaField("float_col", "FLOAT"),
         bigquery.SchemaField("geo_col", "GEOGRAPHY"),
         bigquery.SchemaField("int_col", "INTEGER"),
@@ -313,14 +311,14 @@ def test_load_table_from_dataframe_w_explicit_schema(bigquery_client, dataset_id
         ("bool_col", [True, None, False]),
         ("bytes_col", [b"abc", None, b"def"]),
         ("date_col", [datetime.date(1, 1, 1), None, datetime.date(9999, 12, 31)]),
-        # (
-        #     "dt_col",
-        #     [
-        #         datetime.datetime(1, 1, 1, 0, 0, 0),
-        #         None,
-        #         datetime.datetime(9999, 12, 31, 23, 59, 59, 999999),
-        #     ],
-        # ),
+        (
+            "dt_col",
+            [
+                datetime.datetime(1, 1, 1, 0, 0, 0),
+                None,
+                datetime.datetime(9999, 12, 31, 23, 59, 59, 999999),
+            ],
+        ),
         ("float_col", [float("-inf"), float("nan"), float("inf")]),
         (
             "geo_col",
@@ -800,6 +798,49 @@ def test_list_rows_max_results_w_bqstorage(bigquery_client):
     assert len(dataframe.index) == 100
 
 
+def test_upload_time_and_datetime_56(bigquery_client, dataset_id):
+    df = pandas.DataFrame(
+        dict(
+            dt=[
+                datetime.datetime(2020, 1, 8, 8, 0, 0),
+                datetime.datetime(
+                    2020,
+                    1,
+                    8,
+                    8,
+                    0,
+                    0,
+                    tzinfo=datetime.timezone(datetime.timedelta(hours=-7)),
+                ),
+            ],
+            t=[datetime.time(0, 0, 10, 100001), None],
+        )
+    )
+    table = f"{dataset_id}.test_upload_time_and_datetime"
+    bigquery_client.load_table_from_dataframe(df, table).result()
+    data = list(map(list, bigquery_client.list_rows(table)))
+    assert data == [
+        [
+            datetime.datetime(2020, 1, 8, 8, 0, tzinfo=datetime.timezone.utc),
+            datetime.time(0, 0, 10, 100001),
+        ],
+        [datetime.datetime(2020, 1, 8, 15, 0, tzinfo=datetime.timezone.utc), None],
+    ]
+
+    from google.cloud.bigquery import job, schema
+
+    table = f"{dataset_id}.test_upload_time_and_datetime_dt"
+    config = job.LoadJobConfig(
+        schema=[schema.SchemaField("dt", "DATETIME"), schema.SchemaField("t", "TIME")]
+    )
+
+    bigquery_client.load_table_from_dataframe(df, table, job_config=config).result()
+    data = list(map(list, bigquery_client.list_rows(table)))
+    assert data == [
+        [datetime.datetime(2020, 1, 8, 8, 0), datetime.time(0, 0, 10, 100001)],
+        [datetime.datetime(2020, 1, 8, 15, 0), None],
+
+
 def test_to_dataframe_geography_as_objects(bigquery_client, dataset_id):
     wkt = pytest.importorskip("shapely.wkt")
     bigquery_client.query(