kiszk commented on a change in pull request #11686:
URL: https://github.com/apache/arrow/pull/11686#discussion_r749827236
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File path: python/pyarrow/tests/test_pandas.py
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@@ -4328,9 +4328,14 @@ def make_df_with_timestamps():
})
# Not part of what we're testing, just ensuring that the inputs are what we
# expect.
+ if sys.byteorder == "little":
+ datetime_dtype = "<M8[ns]"
+ else:
+ datetime_dtype = ">M8[ns]"
assert (df.dateTimeMs.dtype, df.dateTimeNs.dtype) == (
- # O == object, <M8[ns] == timestamp64[ns]
- np.dtype("O"), np.dtype("<M8[ns]")
Review comment:
Thank you for your comment. This approach looks to work well.
```
>>> import numpy
>>> dt64 = numpy.datetime64('2002-06-28T01:00:00.000000000+0100', 's')
<stdin>:1: DeprecationWarning: parsing timezone aware datetimes is
deprecated; this will raise an error in the future
>>> dt64.dtype
dtype('>M8[s]')
>>> dt = numpy.dtype('M8[s]')
>>> print(dt64.dtype == dt)
True
>>> dtbe = numpy.dtype('>M8[s]')
>>> print(dt64.dtype == dtbe)
True
>>> dtle = numpy.dtype('<M8[s]')
>>> print(dt64.dtype == dtle)
False
```
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