COMPAT: Use actual isinstance check for pyarrow.Array instead of hasattr(.. 'type') duck typing

pandas/compat/pyarrow.py

@@ -4,6 +4,8 @@
 
 from pandas.util.version import Version
 
+PYARROW_INSTALLED = None
+
 try:
     import pyarrow as pa
 
@@ -14,9 +16,21 @@
     pa_version_under9p0 = _palv < Version("9.0.0")
     pa_version_under10p0 = _palv < Version("10.0.0")
     pa_version_under11p0 = _palv < Version("11.0.0")
+
+    PYARROW_INSTALLED = True
 except ImportError:
+    pa = None
+
     pa_version_under7p0 = True
     pa_version_under8p0 = True
     pa_version_under9p0 = True
     pa_version_under10p0 = True
     pa_version_under11p0 = True
+
+    PYARROW_INSTALLED = False
+
+
+def is_pyarrow_array(obj) -> bool:
+    if PYARROW_INSTALLED:
+        return isinstance(obj, (pa.Array, pa.ChunkedArray))
+    return False

pandas/core/arrays/string_.py

@@ -14,7 +14,10 @@
     missing as libmissing,
 )
 from pandas._libs.arrays import NDArrayBacked
-from pandas.compat import pa_version_under7p0
+from pandas.compat import (
+    is_pyarrow_array,
+    pa_version_under7p0,
+)
 from pandas.compat.numpy import function as nv
 from pandas.util._decorators import doc
 
@@ -356,7 +359,7 @@ def _from_sequence(cls, scalars, *, dtype: Dtype | None = None, copy: bool = Fal
             result[na_values] = libmissing.NA
 
         else:
-            if hasattr(scalars, "type"):
+            if is_pyarrow_array(scalars):
                 # pyarrow array; we cannot rely on the "to_numpy" check in
                 #  ensure_string_array because calling scalars.to_numpy would set
                 #  zero_copy_only to True which caused problems see GH#52076