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BUG: Platform-dependent stringification of Period objects #48746

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@aulemahal

Description

@aulemahal

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

t = pd.Period('0064-07-18', 'D')  # Rome burns

str(t)
# '64-07-18'

# thus:
pd.Period(str(t), 'D')
# Period('2064-07-18', 'D'

Issue Description

Period objects do not always return a string version that would yield the same Period object when parsed.

For me the issue arises with dates before 100 AD, on Linux. The behaviour is as shown above.

I believe, the issue is not related to pandas, but rather to Python's C implementation of strftime, as indicated in this stackoverflow question: https://stackoverflow.com/a/43633945/9291575

Expected Behavior

However, I believe the default stringification in Pandas could be adapted to be platform-independent.

As Pandas sets the default format strings explicitly, we could use %4Y instead of %Y and, AFAIU the issue would go away.

Installed Versions

INSTALLED VERSIONS

commit : 44a4f16
python : 3.8.13.final.0
python-bits : 64
OS : Linux
OS-release : 5.19.9-200.fc36.x86_64
Version : #1 SMP PREEMPT_DYNAMIC Thu Sep 15 09:49:52 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : fr_CA.UTF-8
LOCALE : fr_CA.UTF-8

pandas : 1.6.0.dev0+199.g44a4f1619f
numpy : 1.22.4
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 65.3.0
pip : 22.2.2
Cython : 0.29.32
pytest : 7.1.3
hypothesis : 6.54.6
sphinx : 4.5.0
blosc : None
feather : None
xlsxwriter : 3.0.3
lxml.etree : 4.9.1
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : 2.9.3
jinja2 : 3.0.3
IPython : 8.5.0
pandas_datareader: 0.10.0
bs4 : 4.11.1
bottleneck : 1.3.5
brotli :
fastparquet : 0.8.3
fsspec : 2021.11.0
gcsfs : 2021.11.0
matplotlib : 3.6.0
numba : 0.55.2
numexpr : 2.8.3
odfpy : None
openpyxl : 3.0.10
pandas_gbq : 0.17.8
pyarrow : 9.0.0
pyreadstat : 1.1.9
pyxlsb : 1.0.9
s3fs : 2021.11.0
scipy : 1.9.1
snappy :
sqlalchemy : 1.4.41
tables : 3.7.0
tabulate : 0.8.10
xarray : 2022.6.0
xlrd : 2.0.1
xlwt : 1.3.0
zstandard : 0.18.0
tzdata : None

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