test: Add test of datetime and time pandas load (#895)

Author: Jim Fulton

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 +798,50 @@ 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(