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  • JackKelly · 2 ✖

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  • Time dtype encoding defaulting to `int64` when writing netcdf or zarr · 2 ✖

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  • NONE · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
965595392 https://github.com/pydata/xarray/issues/3942#issuecomment-965595392 https://api.github.com/repos/pydata/xarray/issues/3942 IC_kwDOAMm_X845jdEA JackKelly 460756 2021-11-10T17:56:41Z 2021-11-10T17:57:17Z NONE

Cool, I agree that an error and a documentation change is likely to be sufficient :slightly_smiling_face: (and I'd be keen to write a PR to help out!)

But, before we commit to that path: Please may I ask: Why not default to xarray encoding time as 'units': 'nanoseconds since 1970-01-01' to be consistent with np.datetime64[ns]? Sorry if I've missed something obvious!

 
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   Time dtype encoding defaulting to `int64` when writing netcdf or zarr 595492608
965562434 https://github.com/pydata/xarray/issues/3942#issuecomment-965562434 https://api.github.com/repos/pydata/xarray/issues/3942 IC_kwDOAMm_X845jVBC JackKelly 460756 2021-11-10T17:17:29Z 2021-11-10T17:49:22Z NONE

I think I've bumped into a symptom of this issue (my issue is described in #5969). And I think #3379 may be another symptom of this issue.

Perhaps I'm biased (because I work with timeseries which only span a few years) but I wonder if xarray should default to encoding time as 'units': 'nanoseconds since 1970-01-01' (to be consistent with np.datetime64[ns]) unless the timeseries includes dates before the year 1677, or after the year 2262 :slightly_smiling_face:? Would that work?

If that's no good, then let's definitely add a note to the documentation to say that it might be a good idea for users to manually specify the encoding for datetimes if they wish to append to Zarrs.

 
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   Time dtype encoding defaulting to `int64` when writing netcdf or zarr 595492608

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