chore: move unit test utilities to bigframes.testing module, remove unnecessary skip_legacy_pandas (#1623)

Author: tswast

bigframes/testing/__init__.py

@@ -0,0 +1,19 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""[Experimental] Utilities for testing BigQuery DataFrames.
+
+These modules are provided for testing the BigQuery DataFrames package. The
+interface is not considered stable.
+"""

tests/unit/resources.py bigframes/testing/mocks.pytests/unit/resources.py renamed to bigframes/testing/mocks.py

@@ -36,12 +36,17 @@
 
 
 def create_bigquery_session(
+    *,
     bqclient: Optional[mock.Mock] = None,
     session_id: str = "abcxyz",
     table_schema: Sequence[google.cloud.bigquery.SchemaField] = TEST_SCHEMA,
     anonymous_dataset: Optional[google.cloud.bigquery.DatasetReference] = None,
     location: str = "test-region",
 ) -> bigframes.Session:
+    """[Experimental] Create a mock BigQuery DataFrames session that avoids making Google Cloud API calls.
+
+    Intended for unit test environments that don't have access to the network.
+    """
     credentials = mock.create_autospec(
         google.auth.credentials.Credentials, instance=True
     )
@@ -108,8 +113,12 @@ def query_and_wait_mock(query, *args, **kwargs):
 
 
 def create_dataframe(
-    monkeypatch: pytest.MonkeyPatch, session: Optional[bigframes.Session] = None
+    monkeypatch: pytest.MonkeyPatch, *, session: Optional[bigframes.Session] = None
 ) -> bigframes.dataframe.DataFrame:
+    """[Experimental] Create a mock DataFrame that avoids making Google Cloud API calls.
+
+    Intended for unit test environments that don't have access to the network.
+    """
     if session is None:
         session = create_bigquery_session()
 

tests/system/small/operations/test_datetimes.py

@@ -20,7 +20,7 @@
 import pytest
 
 import bigframes.series
-from tests.system.utils import assert_series_equal, skip_legacy_pandas
+from tests.system.utils import assert_series_equal
 
 DATETIME_COL_NAMES = [("datetime_col",), ("timestamp_col",)]
 DATE_COLUMNS = [
@@ -34,8 +34,9 @@
     ("col_name",),
     DATE_COLUMNS,
 )
-@skip_legacy_pandas
 def test_dt_day(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_series: bigframes.series.Series = scalars_df[col_name]
     bf_result = bf_series.dt.day.to_pandas()
@@ -51,8 +52,9 @@ def test_dt_day(scalars_dfs, col_name):
     ("col_name",),
     DATETIME_COL_NAMES,
 )
-@skip_legacy_pandas
 def test_dt_date(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_series: bigframes.series.Series = scalars_df[col_name]
     bf_result = bf_series.dt.date.to_pandas()
@@ -68,8 +70,9 @@ def test_dt_date(scalars_dfs, col_name):
     ("col_name",),
     DATE_COLUMNS,
 )
-@skip_legacy_pandas
 def test_dt_dayofweek(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_series: bigframes.series.Series = scalars_df[col_name]
     bf_result = bf_series.dt.dayofweek.to_pandas()
@@ -82,8 +85,9 @@ def test_dt_dayofweek(scalars_dfs, col_name):
     ("col_name",),
     DATETIME_COL_NAMES,
 )
-@skip_legacy_pandas
 def test_dt_hour(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_series: bigframes.series.Series = scalars_df[col_name]
     bf_result = bf_series.dt.hour.to_pandas()
@@ -99,8 +103,9 @@ def test_dt_hour(scalars_dfs, col_name):
     ("col_name",),
     DATETIME_COL_NAMES,
 )
-@skip_legacy_pandas
 def test_dt_minute(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_series: bigframes.series.Series = scalars_df[col_name]
     bf_result = bf_series.dt.minute.to_pandas()
@@ -116,8 +121,9 @@ def test_dt_minute(scalars_dfs, col_name):
     ("col_name",),
     DATE_COLUMNS,
 )
-@skip_legacy_pandas
 def test_dt_month(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_series: bigframes.series.Series = scalars_df[col_name]
     bf_result = bf_series.dt.month.to_pandas()
@@ -133,8 +139,9 @@ def test_dt_month(scalars_dfs, col_name):
     ("col_name",),
     DATE_COLUMNS,
 )
-@skip_legacy_pandas
 def test_dt_quarter(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_series: bigframes.series.Series = scalars_df[col_name]
     bf_result = bf_series.dt.quarter.to_pandas()
@@ -150,8 +157,9 @@ def test_dt_quarter(scalars_dfs, col_name):
     ("col_name",),
     DATETIME_COL_NAMES,
 )
-@skip_legacy_pandas
 def test_dt_second(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_series: bigframes.series.Series = scalars_df[col_name]
     bf_result = bf_series.dt.second.to_pandas()
@@ -167,8 +175,9 @@ def test_dt_second(scalars_dfs, col_name):
     ("col_name",),
     DATETIME_COL_NAMES,
 )
-@skip_legacy_pandas
 def test_dt_time(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_series: bigframes.series.Series = scalars_df[col_name]
     bf_result = bf_series.dt.time.to_pandas()
@@ -184,8 +193,9 @@ def test_dt_time(scalars_dfs, col_name):
     ("col_name",),
     DATE_COLUMNS,
 )
-@skip_legacy_pandas
 def test_dt_year(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_series: bigframes.series.Series = scalars_df[col_name]
     bf_result = bf_series.dt.year.to_pandas()
@@ -201,8 +211,9 @@ def test_dt_year(scalars_dfs, col_name):
     ("col_name",),
     DATETIME_COL_NAMES,
 )
-@skip_legacy_pandas
 def test_dt_tz(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_series: bigframes.series.Series = scalars_df[col_name]
     bf_result = bf_series.dt.tz
@@ -215,8 +226,9 @@ def test_dt_tz(scalars_dfs, col_name):
     ("col_name",),
     DATETIME_COL_NAMES,
 )
-@skip_legacy_pandas
 def test_dt_unit(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_series: bigframes.series.Series = scalars_df[col_name]
     bf_result = bf_series.dt.unit
@@ -234,8 +246,9 @@ def test_dt_unit(scalars_dfs, col_name):
         ("datetime_col", "%H:%M"),
     ],
 )
-@skip_legacy_pandas
 def test_dt_strftime(scalars_df_index, scalars_pandas_df_index, column, date_format):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     bf_result = scalars_df_index[column].dt.strftime(date_format).to_pandas()
     pd_result = scalars_pandas_df_index[column].dt.strftime(date_format)
     pd.testing.assert_series_equal(bf_result, pd_result, check_dtype=False)
@@ -276,8 +289,9 @@ def test_dt_strftime_time():
     ("col_name",),
     DATETIME_COL_NAMES,
 )
-@skip_legacy_pandas
 def test_dt_normalize(scalars_dfs, col_name):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_result = scalars_df[col_name].dt.normalize().to_pandas()
     pd_result = scalars_pandas_df[col_name].dt.normalize()
@@ -297,8 +311,9 @@ def test_dt_normalize(scalars_dfs, col_name):
         ("datetime_col", "us"),
     ],
 )
-@skip_legacy_pandas
 def test_dt_floor(scalars_dfs, col_name, freq):
+    # TODO: supply a reason why this isn't compatible with pandas 1.x
+    pytest.importorskip("pandas", minversion="2.0.0")
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_result = scalars_df[col_name].dt.floor(freq).to_pandas()
     pd_result = scalars_pandas_df[col_name].dt.floor(freq)