Refactor test_complex.py to use HDFStore directly

Author: AnonToky

pandas/tests/io/pytables/test_complex.py

@@ -7,7 +7,7 @@
     Series,
 )
 import pandas._testing as tm
-from pandas.tests.io.pytables.common import ensure_clean_store
+from pandas import HDFStore
 
 from pandas.io.pytables import read_hdf
 
@@ -103,7 +103,8 @@ def test_complex_mixed_table(tmp_path, setup_path):
         index=list("abcd"),
     )
 
-    with ensure_clean_store(setup_path) as store:
+    path = tmp_path / setup_path
+    with HDFStore(path) as store:
         store.append("df", df, data_columns=["A", "B"])
         result = store.select("df", where="A>2")
         tm.assert_frame_equal(df.loc[df.A > 2], result)
@@ -139,7 +140,7 @@ def test_complex_across_dimensions(tmp_path, setup_path):
     tm.assert_frame_equal(df, reread)
 
 
-def test_complex_indexing_error(setup_path):
+def test_complex_indexing_error(tmp_path, setup_path):
     complex128 = np.array(
         [1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex128
     )
@@ -156,7 +157,8 @@ def test_complex_indexing_error(setup_path):
         "values to data_columns when initializing the table."
     )
 
-    with ensure_clean_store(setup_path) as store:
+    path = tmp_path / setup_path
+    with HDFStore(path) as store:
         with pytest.raises(TypeError, match=msg):
             store.append("df", df, data_columns=["C"])
 
@@ -183,15 +185,16 @@ def test_complex_series_error(tmp_path, setup_path):
     tm.assert_series_equal(s, reread)
 
 
-def test_complex_append(setup_path):
+def test_complex_append(tmp_path, setup_path):
     df = DataFrame(
         {
             "a": np.random.default_rng(2).standard_normal(100).astype(np.complex128),
             "b": np.random.default_rng(2).standard_normal(100),
         }
     )
 
-    with ensure_clean_store(setup_path) as store:
+    path = tmp_path / setup_path
+    with HDFStore(path) as store:
         store.append("df", df, data_columns=["b"])
         store.append("df", df)
         result = store.select("df")