pre-commit post spark rebase

graph_adapter_tests/h_spark/test_h_spark.py

@@ -5,12 +5,12 @@
 import pyspark.pandas as ps
 import pytest
 from pyspark import Row
-from pyspark.sql import Column, DataFrame, SparkSession
-from pyspark.sql import types
+from pyspark.sql import Column, DataFrame, SparkSession, types
 from pyspark.sql.functions import column
 
 from hamilton import base, driver, htypes, node
 from hamilton.experimental import h_spark
+
 from .resources import example_module, smoke_screen_module
 from .resources.spark import (
     basic_spark_dag,
@@ -304,10 +304,7 @@ def test_python_to_spark_type_invalid(invalid_python_type):
     ],
 )
 def test_get_spark_type_basic_types(return_type, expected_spark_type):
-    assert (
-        h_spark.get_spark_type(return_type)
-        == expected_spark_type
-    )
+    assert h_spark.get_spark_type(return_type) == expected_spark_type
 
 
 # 2. Lists of basic Python types
@@ -322,14 +319,9 @@ def test_get_spark_type_basic_types(return_type, expected_spark_type):
         (bytes, types.ArrayType(types.BinaryType())),
     ],
 )
-def test_get_spark_type_list_types(
-    return_type, expected_spark_type
-):
+def test_get_spark_type_list_types(return_type, expected_spark_type):
     return_type = list[return_type]  # type: ignore
-    assert (
-        h_spark.get_spark_type(return_type)
-        == expected_spark_type
-    )
+    assert h_spark.get_spark_type(return_type) == expected_spark_type
 
 
 # 3. Numpy types (assuming you have a numpy_to_spark_type function that handles these)
@@ -341,13 +333,8 @@ def test_get_spark_type_list_types(
         (np.bool_, types.BooleanType()),
     ],
 )
-def test_get_spark_type_numpy_types(
-    return_type, expected_spark_type
-):
-    assert (
-        h_spark.get_spark_type(return_type)
-        == expected_spark_type
-    )
+def test_get_spark_type_numpy_types(return_type, expected_spark_type):
+    assert h_spark.get_spark_type(return_type) == expected_spark_type
 
 
 # 4. Unsupported types
@@ -379,6 +366,7 @@ def dummyfunc(x: int) -> int:
 
     return dummyfunc
 
+
 def test_base_spark_executor_end_to_end(spark_session):
     # TODO -- make this simpler to call, and not require all these constructs
     dr = (

hamilton/experimental/h_spark.py

@@ -215,7 +215,6 @@ def python_to_spark_type(python_type: Type[Union[int, float, bool, str, bytes]])
     _list = (list[int], list[float], list[bool], list[str], list[bytes])
 
 
-
 def get_spark_type(return_type: Any) -> types.DataType:
     if return_type in (int, float, bool, str, bytes):
         return python_to_spark_type(return_type)