BUG: output of pandas.util.hash_pandas_object() changed in pandas 2.2.x

[hagenw]

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

import pandas as pd

index = pd.Index([0, 1, 2], dtype="Int64")  # without `dtype="Int64"` the bug doesn't appear
df = pd.DataFrame([0, 1, 2], index=index)
pd.util.hash_pandas_object(df)

Issue Description

Under pandas 2.1.0 we get:

0    17186048303505514001
1    10757116890508915594
2    14391254723460080955
dtype: uint64

Under pandas 2.2.0 and 2.2.2 we get:

0    3713087409444908179
1    7554402398462747209
2    1687604933839263903
dtype: uint64

Expected Behavior

Hashing should always return the same values, independent of the used pandas version.

Installed Versions

INSTALLED VERSIONS

commit : d9cdd2e
python : 3.10.12.final.0
python-bits : 64
OS : Linux
OS-release : 6.5.0-1023-oem
Version : #24-Ubuntu SMP PREEMPT_DYNAMIC Tue May 7 14:26:31 UTC 2024
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8

pandas : 2.2.2 [7/2907]
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : 59.6.0
pip : 22.0.2
Cython : None
pytest : 8.1.1
hypothesis : None
sphinx : 5.3.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.3
IPython : 8.24.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 15.0.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None

[mroeschke]

Thanks for the report, but this was (unfortunately) an intended change noted in the release notes: https://pandas.pydata.org/docs/whatsnew/v2.2.0.html#other-api-changes so closing as an expected change

[hagenw]

Ah, thanks, I overlooked this. It's also a big change for a minor version, as hashes might be used for caching. But it's ok, it might be anyway a better approach to not rely on pandas.utils.hash_pandas_object() for this.