String dtype: disallow specifying the 'str' dtype with storage in [..] in string alias (#60661)

Author: jorisvandenbossche

pandas/core/dtypes/dtypes.py

@@ -2339,7 +2339,7 @@ def construct_from_string(cls, string: str) -> ArrowDtype:
             )
         if not string.endswith("[pyarrow]"):
             raise TypeError(f"'{string}' must end with '[pyarrow]'")
-        if string == "string[pyarrow]":
+        if string in ("string[pyarrow]", "str[pyarrow]"):
             # Ensure Registry.find skips ArrowDtype to use StringDtype instead
             raise TypeError("string[pyarrow] should be constructed by StringDtype")
         if pa_version_under10p1:

pandas/tests/dtypes/test_common.py

@@ -837,6 +837,26 @@ def test_pandas_dtype_string_dtypes(string_storage):
     assert result == pd.StringDtype(string_storage, na_value=pd.NA)
 
 
+def test_pandas_dtype_string_dtype_alias_with_storage():
+    with pytest.raises(TypeError, match="not understood"):
+        pandas_dtype("str[python]")
+
+    with pytest.raises(TypeError, match="not understood"):
+        pandas_dtype("str[pyarrow]")
+
+    result = pandas_dtype("string[python]")
+    assert result == pd.StringDtype("python", na_value=pd.NA)
+
+    if HAS_PYARROW:
+        result = pandas_dtype("string[pyarrow]")
+        assert result == pd.StringDtype("pyarrow", na_value=pd.NA)
+    else:
+        with pytest.raises(
+            ImportError, match="required for PyArrow backed StringArray"
+        ):
+            pandas_dtype("string[pyarrow]")
+
+
 @td.skip_if_installed("pyarrow")
 def test_construct_from_string_without_pyarrow_installed():
     # GH 57928

pandas/tests/strings/test_get_dummies.py

@@ -6,6 +6,7 @@
 import pandas.util._test_decorators as td
 
 from pandas import (
+    ArrowDtype,
     DataFrame,
     Index,
     MultiIndex,
@@ -113,15 +114,17 @@ def test_get_dummies_with_str_dtype(any_string_dtype):
 # GH#47872
 @td.skip_if_no("pyarrow")
 def test_get_dummies_with_pa_str_dtype(any_string_dtype):
+    import pyarrow as pa
+
     s = Series(["a|b", "a|c", np.nan], dtype=any_string_dtype)
-    result = s.str.get_dummies("|", dtype="str[pyarrow]")
+    result = s.str.get_dummies("|", dtype=ArrowDtype(pa.string()))
     expected = DataFrame(
         [
             ["true", "true", "false"],
             ["true", "false", "true"],
             ["false", "false", "false"],
         ],
         columns=list("abc"),
-        dtype="str[pyarrow]",
+        dtype=ArrowDtype(pa.string()),
     )
     tm.assert_frame_equal(result, expected)