BUG: rolling does not work with timestamp[ns][pyarrow] index type

[mhabets]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

ts = ['2019-01-03 05:11', '2019-01-03 05:23',
      '2019-01-03 05:28', '2019-01-03 05:32',
      '2019-01-03 05:36']
arr = [True, False, False, True, True]
df = pd.DataFrame({'arr': arr, 'ts': ts})
df["ts"] = pd.to_datetime(df["ts"])
df = df.convert_dtypes(dtype_backend="pyarrow").set_index("ts")
print(df.rolling('5min').sum())

Issue Description

Error message: ValueError: window must be an integer 0 or greater

Expected Behavior

No error message

Installed Versions

INSTALLED VERSIONS

commit : a60ad39
python : 3.11.6.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22621
machine : AMD64
processor : Intel64 Family 6 Model 186 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en
LOCALE : English_United Kingdom.1252

pandas : 2.1.2
numpy : 1.26.0
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 23.3.1
Cython : None
pytest : None
hypothesis : None
sphinx : 7.2.6
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.9.7
jinja2 : 3.1.2
IPython : 8.17.2
pandas_datareader : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.1
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 13.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.3
sqlalchemy : 2.0.23
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : 2.4.1
pyqt5 : None

[hvsesha]

@mhabets Rolling function is having window of datatype integer
If you give string it will throw error as it is expected

So Kindly give window =5 and it will work

[hvsesha]

@mhabets
in rolling.py kindly find the validation

if not is_integer(self.window) or self.window < 0:
raise ValueError("window must be an integer 0 or greater")

[mhabets]

@hvsesha - please note that the following code (with str) works like a charm as describe in the documentation:

ts = ['2019-01-03 05:11', '2019-01-03 05:23',
      '2019-01-03 05:28', '2019-01-03 05:32',
      '2019-01-03 05:36']
arr = [True, False, False, True, True]
df = pd.DataFrame({'arr': arr, 'ts': ts})
df["ts"] = pd.to_datetime(df["ts"])
df = df.set_index("ts")
print(df.rolling('5min').sum())

The issue is related to the type of the index (Arrow timestamp type not being covered as yet)

[hvsesha]

@mhabets Able to change in cast.py by adding arrow in convert_dtypes

def convert_dtypes(
input_array: ArrayLike,
convert_string: bool = True,
convert_integer: bool = True,
convert_boolean: bool = True,
convert_floating: bool = True,
convert_pyarrow:bool= True,
infer_objects: bool = False,
dtype_backend: Literal["numpy_nullable"] = "numpy_nullable",
) -> DtypeObj:

Tested

[hvsesha]

@mroeschke Kindly review this fix .I am 20 years experienced in c++.Kindly let me know if this fix looks good