refactor: Rename DataFrame fixtures and update test functions

- Renamed `df` fixture to `complex_window_df` for clarity.
- Renamed `simple_df` fixture to `count_window_df` to better reflect its purpose.
- Updated test functions to use the new fixture names, enhancing readability and maintainability.

Author: kosiew

python/tests/test_udwf.py

@@ -182,7 +182,7 @@ def ctx():
 
 
 @pytest.fixture
-def df(ctx):
+def complex_window_df(ctx):
     # create a RecordBatch and a new DataFrame from it
     batch = pa.RecordBatch.from_arrays(
         [
@@ -196,7 +196,7 @@ def df(ctx):
 
 
 @pytest.fixture
-def simple_df(ctx):
+def count_window_df(ctx):
     # create a RecordBatch and a new DataFrame from it
     batch = pa.RecordBatch.from_arrays(
         [pa.array([1, 2, 3]), pa.array([4, 4, 6])],
@@ -205,7 +205,7 @@ def simple_df(ctx):
     return ctx.create_dataframe([[batch]], name="test_table")
 
 
-def test_udwf_errors(df):
+def test_udwf_errors(complex_window_df):
     with pytest.raises(TypeError):
         udwf(
             NotSubclassOfWindowEvaluator,
@@ -225,13 +225,13 @@ def test_udwf_errors_with_message():
         )
 
 
-def test_udwf_basic_usage(simple_df):
+def test_udwf_basic_usage(count_window_df):
     """Test basic UDWF usage with a simple counting window function."""
     simple_count = udwf(
         SimpleWindowCount, pa.int64(), pa.int64(), volatility="immutable"
     )
 
-    df = simple_df.select(
+    df = count_window_df.select(
         simple_count(column("a"))
         .window_frame(WindowFrame("rows", None, None))
         .build()
@@ -241,13 +241,13 @@ def test_udwf_basic_usage(simple_df):
     assert result.column(0) == pa.array([0, 1, 2])
 
 
-def test_udwf_with_args(simple_df):
+def test_udwf_with_args(count_window_df):
     """Test UDWF with constructor arguments."""
     count_base10 = udwf(
         lambda: SimpleWindowCount(10), pa.int64(), pa.int64(), volatility="immutable"
     )
 
-    df = simple_df.select(
+    df = count_window_df.select(
         count_base10(column("a"))
         .window_frame(WindowFrame("rows", None, None))
         .build()
@@ -257,14 +257,14 @@ def test_udwf_with_args(simple_df):
     assert result.column(0) == pa.array([10, 11, 12])
 
 
-def test_udwf_decorator_basic(simple_df):
+def test_udwf_decorator_basic(count_window_df):
     """Test UDWF used as a decorator."""
 
     @udwf([pa.int64()], pa.int64(), "immutable")
     def window_count() -> WindowEvaluator:
         return SimpleWindowCount()
 
-    df = simple_df.select(
+    df = count_window_df.select(
         window_count(column("a"))
         .window_frame(WindowFrame("rows", None, None))
         .build()
@@ -274,14 +274,14 @@ def window_count() -> WindowEvaluator:
     assert result.column(0) == pa.array([0, 1, 2])
 
 
-def test_udwf_decorator_with_args(simple_df):
+def test_udwf_decorator_with_args(count_window_df):
     """Test UDWF decorator with constructor arguments."""
 
     @udwf([pa.int64()], pa.int64(), "immutable")
     def window_count_base10() -> WindowEvaluator:
         return SimpleWindowCount(10)
 
-    df = simple_df.select(
+    df = count_window_df.select(
         window_count_base10(column("a"))
         .window_frame(WindowFrame("rows", None, None))
         .build()
@@ -291,7 +291,7 @@ def window_count_base10() -> WindowEvaluator:
     assert result.column(0) == pa.array([10, 11, 12])
 
 
-def test_register_udwf(ctx, simple_df):
+def test_register_udwf(ctx, count_window_df):
     """Test registering and using UDWF in SQL context."""
     window_count = udwf(
         SimpleWindowCount,
@@ -415,8 +415,8 @@ def test_register_udwf(ctx, simple_df):
 
 
 @pytest.mark.parametrize(("name", "expr", "expected"), data_test_udwf_functions)
-def test_udwf_functions(df, name, expr, expected):
-    df = df.select("a", "b", f.round(expr, lit(3)).alias(name))
+def test_udwf_functions(complex_window_df, name, expr, expected):
+    df = complex_window_df.select("a", "b", f.round(expr, lit(3)).alias(name))
 
     # execute and collect the first (and only) batch
     result = df.sort(column("a")).select(column(name)).collect()[0]