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3 rows where issue = 1657396474 and user = 2448579 sorted by updated_at descending

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  • dcherian · 3 ✖

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  • Continue to use nanosecond-precision Timestamps in precision-sensitive areas · 3 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1507124290 https://github.com/pydata/xarray/pull/7731#issuecomment-1507124290 https://api.github.com/repos/pydata/xarray/issues/7731 IC_kwDOAMm_X85Z1ORC dcherian 2448579 2023-04-13T14:58:20Z 2023-04-13T14:58:20Z MEMBER

Thanks for patiently working through this Spencer. I'll merge now, and then we can release tomorrow.

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  Continue to use nanosecond-precision Timestamps in precision-sensitive areas 1657396474
1506285455 https://github.com/pydata/xarray/pull/7731#issuecomment-1506285455 https://api.github.com/repos/pydata/xarray/issues/7731 IC_kwDOAMm_X85ZyBeP dcherian 2448579 2023-04-13T03:35:01Z 2023-04-13T03:35:01Z MEMBER

There are a bunch of warnings in the tests that could be silenced: D:\a\xarray\xarray\xarray\tests\test_dataset.py:516: UserWarning: Converting non-nanosecond precision datetime values to nanosecond precision. This behavior can eventually be relaxed in xarray, as it is an artifact from pandas which is now beginning to support non-nanosecond precision values. This warning is caused by passing non-nanosecond np.datetime64 or np.timedelta64 values to the DataArray or Variable constructor; it can be silenced by converting the values to nanosecond precision ahead of time.

But we can also just merge quickly to get a release out

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  Continue to use nanosecond-precision Timestamps in precision-sensitive areas 1657396474
1505399396 https://github.com/pydata/xarray/pull/7731#issuecomment-1505399396 https://api.github.com/repos/pydata/xarray/issues/7731 IC_kwDOAMm_X85ZupJk dcherian 2448579 2023-04-12T14:41:02Z 2023-04-12T14:41:17Z MEMBER

RTD failures are real: WARNING: [autosummary] failed to import xarray.CFTimeIndex.is_all_dates. Possible hints: * ImportError: * AttributeError: type object 'CFTimeIndex' has no attribute 'is_all_dates' * ModuleNotFoundError: No module named 'xarray.CFTimeIndex' WARNING: [autosummary] failed to import xarray.CFTimeIndex.is_mixed. Possible hints: * ImportError: * AttributeError: type object 'CFTimeIndex' has no attribute 'is_mixed' * ModuleNotFoundError: No module named 'xarray.CFTimeIndex' WARNING: [autosummary] failed to import xarray.CFTimeIndex.is_monotonic. Possible hints: * ImportError: * AttributeError: type object 'CFTimeIndex' has no attribute 'is_monotonic' * ModuleNotFoundError: No module named 'xarray.CFTimeIndex' WARNING: [autosummary] failed to import xarray.CFTimeIndex.is_type_compatible. Possible hints: * AttributeError: type object 'CFTimeIndex' has no attribute 'is_type_compatible' * ImportError: * ModuleNotFoundError: No module named 'xarray.CFTimeIndex' WARNING: [autosummary] failed to import xarray.CFTimeIndex.set_value. Possible hints: * ImportError: * AttributeError: type object 'CFTimeIndex' has no attribute 'set_value' * ModuleNotFoundError: No module named 'xarray.CFTimeIndex' WARNING: [autosummary] failed to import xarray.CFTimeIndex.to_native_types. Possible hints: * ImportError: * AttributeError: type object 'CFTimeIndex' has no attribute 'to_native_types' * ModuleNotFoundError: No module named 'xarray.CFTimeIndex'

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  Continue to use nanosecond-precision Timestamps in precision-sensitive areas 1657396474

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