format

altair/vegalite/v5/display.py

@@ -100,7 +100,7 @@ def jupyter_renderer(spec: dict, **metadata):
     JupyterChart.enable_offline(offline=offline)  # type: ignore[attr-defined]
 
     # propagate embed options
-    embed_options = metadata.get("embed_options", None)
+    embed_options = metadata.get("embed_options")
 
     # Need to ignore attr-defined mypy rule because mypy doesn't see _repr_mimebundle_
     # conditionally defined in AnyWidget

tests/utils/test_to_values_narwhals.py

@@ -1,11 +1,11 @@
-import re
-import sys
 from datetime import datetime
 
 import narwhals.stable.v1 as nw
 import pandas as pd
 import pytest
 
+from tests import skip_requires_pyarrow
+
 try:
     import pyarrow as pa
 except ImportError:

tests/utils/test_utils.py

@@ -1,6 +1,5 @@
 import io
 import json
-import sys
 import warnings
 
 import narwhals.stable.v1 as nw
@@ -13,6 +12,7 @@
     sanitize_narwhals_dataframe,
     sanitize_pandas_dataframe,
 )
+from tests import skip_requires_pyarrow
 
 try:
     import pyarrow as pa

tests/vegalite/v5/test_api.py

@@ -10,8 +10,9 @@
 import re
 import sys
 import tempfile
-from datetime import date
+from datetime import date, datetime
 from importlib.metadata import version as importlib_version
+from typing import Any
 
 import duckdb
 import jsonschema
@@ -24,15 +25,13 @@
 import altair as alt
 from altair.utils.core import use_signature
 from altair.utils.schemapi import Optional, SchemaValidationError, Undefined
-from tests import skip_requires_pyarrow, skip_requires_vl_convert, slow
+from tests import skip_requires_pyarrow
 
 try:
     import vl_convert as vlc
 except ImportError:
     vlc = None
 
-ibis.set_backend("polars")
-
 PANDAS_VERSION = Version(importlib_version("pandas"))
 
 
@@ -529,8 +528,6 @@ def test_when_labels_position_based_on_condition() -> None:
     import numpy as np
     import pandas as pd
 
-    from altair.utils.schemapi import SchemaValidationError
-
     rand = np.random.RandomState(42)
     df = pd.DataFrame({"xval": range(100), "yval": rand.randn(100).cumsum()})