BUG: read_parquet doesn't convert categories to pd.CategoricalDtype when dtype_backend="pyarrow"

[nachomaiz]

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Reproducible Example

import pandas as pd

# prepare test data
test_data = pd.DataFrame({"categorical": ["a", "b", "c", "a", "b", "c"]}, dtype="category")

# confirm correct categorical dtype
print(test_data.select_dtypes("category").shape)  # (6, 1)
print(test_data.select_dtypes(pd.CategoricalDtype).shape)  # (6, 1) [warns]
print(test_data["categorical"].dtype)  # category

# parquet round trip with pyarrow backend
test_data.to_parquet("test.parquet")
loaded_data = pd.read_parquet("test.parquet", dtype_backend="pyarrow")

# check categorical dtype
print(loaded_data.select_dtypes("category").shape)  # (6, 0) [doesn't recognize categorical column]
print(loaded_data.select_dtypes(pd.CategoricalDtype).shape)  # (6, 0) [warns and doesn't recognize categorical column]
print(loaded_data["categorical"].dtype)  # dictionary<values=string, indices=int32, ordered=0>[pyarrow]

# this check works
from pandas.core.dtypes.dtypes import CategoricalDtypeType
print(loaded_data.select_dtypes(CategoricalDtypeType).shape)  # (6, 1) [recognizes categorical column]

Issue Description

The read_parquet function with dtype_backend="pyarrow" parameter doesn't seem to be assigning CategoricalDtype correctly to categorical columns.

Instead, they remain as Arrow dictionaries, and are not searchable with df.select_dtypes("category").

Expected Behavior

I expected the round trip of df.to_parquet and pd.read_parquet to maintain the categorical dtype, and for the loaded dtype to be selected when using df.select_dtypes("category").

Installed Versions

INSTALLED VERSIONS

commit : d9cdd2e
python : 3.12.1.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19045
machine : AMD64
processor : Intel64 Family 6 Model 140 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 2.2.2
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.8.2
setuptools : 69.0.3
pip : 24.0
Cython : None
pytest : 8.0.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.3
IPython : 8.21.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.3
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 15.0.2
pyreadstat : 1.2.7
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.12.0
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None