TST(string dtype): Resolve HDF5 xfails

Author: rhshadrach

pandas/io/pytables.py

@@ -5297,6 +5297,8 @@ def _dtype_to_kind(dtype_str: str) -> str:
         kind = "integer"
     elif dtype_str == "object":
         kind = "object"
+    elif dtype_str == "str":
+        kind = "str"
     else:
         raise ValueError(f"cannot interpret dtype of [{dtype_str}]")
 

pandas/tests/io/pytables/test_subclass.py

@@ -1,8 +1,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
 from pandas import (
     DataFrame,
     Series,
@@ -19,7 +17,6 @@
 
 class TestHDFStoreSubclass:
     # GH 33748
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_supported_for_subclass_dataframe(self, tmp_path):
         data = {"a": [1, 2], "b": [3, 4]}
         sdf = tm.SubclassedDataFrame(data, dtype=np.intp)

pandas/tests/io/test_common.py

@@ -19,8 +19,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
 from pandas.compat import (
     WASM,
     is_platform_windows,
@@ -365,7 +363,6 @@ def test_write_fspath_all(self, writer_name, writer_kwargs, module):
                     expected = f_path.read()
                     assert result == expected
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string) hdf support")
     def test_write_fspath_hdf5(self):
         # Same test as write_fspath_all, except HDF5 files aren't
         # necessarily byte-for-byte identical for a given dataframe, so we'll