ValueError: buffer source array is read-only on DatetimeIndex with one element

[mir06]

Code Sample

# Your code here
import pandas as pd
import numpy as np
times = np.array([np.datetime64('2012-02-15T12:00:00.000000000')])
times.setflags(write=False)

[d for d in pd.to_datetime(times)]

Problem description

The above code raises a ValueError: buffer source array is read-only during the iteration over the DatetimeIndex.

Note: This code snippet is just for demonstration. Read-only arrays are generated e.g. from an xarray broadcast.

This did not happen for pandas<=0.25.0

Expected Output

[Timestamp('2012-02-15 12:00:00')]

Output of pd.show_versions()

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.3.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.19.0-5-amd64
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.0
numpy            : 1.17.0
pytz             : 2019.2
dateutil         : 2.8.0
pip              : 19.2.2
setuptools       : 41.1.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : 7.7.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None

[TomAugspurger]

May need a fix similar to https://github.com/pandas-dev/pandas/pull/27946/files, but in ints_to_pydatetime. Care to submit a PR?

[jbrockmendel]

Looks like in pd._libs.tslib.ints_to_pydatetime the argument int64_t[:] arr needs to be changed to const int64_t[:] arr. PR welcome.

[TomAugspurger]

FYI @jorisvandenbossche I'm probably doing the release todayish, so I'm going to move this off the 0.25.1 milestone.

[jorisvandenbossche]

I prefer to keep those issue on a milestone. If you want to get the queue clear on 0.25.1, it can be 0.25.2 (but for me just a 0.25.x milestone could also do). If not for 0.25.1/2, then 1.0. By default, I think we should mark regressions for the next milestone, even if nobody is directly going to work on it.

[TomAugspurger]

Sounds good.

…

On Wed, Aug 21, 2019 at 1:46 PM Joris Van den Bossche < ***@***.***> wrote: I prefer to keep those issue on *a* milestone. If you want to get the queue clear on 0.25.1, it can be 0.25.2 (but for me just a 0.25.x milestone could also do). If not for 0.25.1/2, then 1.0. By default, I think we should mark regressions for the next milestone, even if nobody is directly going to work on it. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#28055?email_source=notifications&email_token=AAKAOIV5MK7T5TGUOYOQYRLQFWEQLA5CNFSM4IOCVAGKYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD42XZAQ#issuecomment-523598978>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AAKAOITTOR2VV7XIBZ7CWZLQFWEQLANCNFSM4IOCVAGA> .