Pandas version checks
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[X] I have checked that this issue has not already been reported.
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[X] I have confirmed this bug exists on the latest version of pandas.
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[X] I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
from datetime import timedelta
pd.Timedelta("1s") < pd.Timedelta.max # succeeds, returns True
pd.Timedelta("1s") < timedelta.max # fails, raises OverflowError
Issue Description
It looks like timedelta.max is too large to be represented as a pd.Timedelta.
pandas._libs.tslibs.np_datetime.OutOfBoundsTimedelta: Python int too large to convert to C long
As a workaround, I convert the pandas Timedelta to a datetime.timedelta instead:
pd.Timedelta("1s").to_pytimedelta() < timedelta.max # succeeds, returns True
The issue also occurs when comparing a pd.Timedelta to timedelta.min.
Expected Behavior
In case this could be easily addressed in a fix, I'd be happy to work on it. It looks like the relevant part of the Pandas codebase is timedeltas.pyx, which already has a # TODO: watch out for overflows. One idea would be to except the OverflowError and do the comparison with datetime.timedelta objects (by converting self.value to a datetime.timedelta rather than ots.value to a pd.Timedelta). I believe this would imply losing the nanosecond precision (but keeping microsecond precision) when comparing pd.Timedelta values to datetime.timedelta values larger than pd.Timedelta.max.
In case it is not easily fixed, perhaps we could consider what a useful addition would be to the documentation of pd.Timedelta and/or pd.Timedelta.max.