TST: xfail sparse roundtrip tests for Parquet and Feather (preserve_sparse flag)

Author: antznette1

pandas/tests/io/test_feather_sparse.py

@@ -0,0 +1,35 @@
+import numpy as np
+import pytest
+
+import pandas as pd
+
+pa = pytest.importorskip("pyarrow")
+
+xfail_sparse = pytest.mark.xfail(
+    reason="pending implementation of preserve_sparse for Feather",
+    strict=False,
+)
+
+
+@xfail_sparse
+@pytest.mark.parametrize(
+    "subtype, fill_value, data",
+    [
+        ("int64", 0, [0, 0, 3, 0, 5]),
+        ("float64", 0.0, [0.0, 0.0, 1.5, 0.0, 2.5]),
+        ("boolean", False, [False, False, True, False, True]),
+    ],
+)
+def test_feather_sparse_roundtrip(tmp_path, subtype, fill_value, data):
+    path = tmp_path / "out.feather"
+    s = pd.Series(pd.arrays.SparseArray(data, fill_value=fill_value))
+    df = pd.DataFrame({"s": s, "x": np.arange(len(s))})
+
+    df.to_feather(path, preserve_sparse=True)
+    df2 = pd.read_feather(path, preserve_sparse=True)
+
+    assert isinstance(df2["s"].dtype, pd.SparseDtype)
+    assert df2["s"].dtype.fill_value == fill_value
+    pd.testing.assert_series_equal(
+        df2["s"].sparse.to_dense(), s.sparse.to_dense(), check_dtype=False
+    )

pandas/tests/io/test_parquet_sparse.py

@@ -0,0 +1,35 @@
+import numpy as np
+import pytest
+
+import pandas as pd
+
+pa = pytest.importorskip("pyarrow")
+
+xfail_sparse = pytest.mark.xfail(
+    reason="pending implementation of preserve_sparse for Parquet",
+    strict=False,
+)
+
+
+@xfail_sparse
+@pytest.mark.parametrize(
+    "subtype, fill_value, data",
+    [
+        ("int64", 0, [0, 0, 3, 0, 5]),
+        ("float64", 0.0, [0.0, 0.0, 1.5, 0.0, 2.5]),
+        ("boolean", False, [False, False, True, False, True]),
+    ],
+)
+def test_parquet_sparse_roundtrip(tmp_path, subtype, fill_value, data):
+    path = tmp_path / "out.parquet"
+    s = pd.Series(pd.arrays.SparseArray(data, fill_value=fill_value))
+    df = pd.DataFrame({"s": s, "x": np.arange(len(s))})
+
+    df.to_parquet(path, preserve_sparse=True)
+    df2 = pd.read_parquet(path, preserve_sparse=True)
+
+    assert isinstance(df2["s"].dtype, pd.SparseDtype)
+    assert df2["s"].dtype.fill_value == fill_value
+    pd.testing.assert_series_equal(
+        df2["s"].sparse.to_dense(), s.sparse.to_dense(), check_dtype=False
+    )