issues: 2098252325

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
2098252325 I_kwDOAMm_X859EMol 8653 xarray v 2023.9.0: ```ValueError: unable to infer dtype on variable 'time'; xarray cannot serialize arbitrary Python objects``` 8382834 open 0     1 2024-01-24T13:18:55Z 2024-02-05T12:50:34Z   CONTRIBUTOR      

What happened?

I tried to save an xarray dataset with datetimes as data for its time dimension to a nc file with to_netcdf and got the error ValueError: unable to infer dtype on variable 'time'; xarray cannot serialize arbitrary Python objects.

What did you expect to happen?

I expected xarray to automatically detect these were datetimes, and convert them to whatever format xarray likes to work with internally to dump it into a CF compatible file, following what is described at https://github.com/pydata/xarray/issues/2512 .

Minimal Complete Verifiable Example

```Python import xarray as xr import datetime

times = [datetime.datetime(2024, 1, 1, 1, 1, 1, tzinfo=datetime.timezone.utc), datetime.datetime(2024, 1, 1, 1, 1, 2, tzinfo=datetime.timezone.utc)]

data = [1, 2]

xr_result = xr.Dataset( { 'time': xr.DataArray(dims=["time"], data=times, attrs={ "standard_name": "time", }), # 'data': xr.DataArray(dims=["time"], data=data, attrs={ "_FillValue": "NaN", "standard_name": "some_data", }), } )

xr_result.to_netcdf("test.nc") ```

MVCE confirmation

  • [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
  • [X] Complete example — the example is self-contained, including all data and the text of any traceback.
  • [ ] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
  • [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.
  • [ ] Recent environment — the issue occurs with the latest version of xarray and its dependencies.

Relevant log output

No response

Anything else we need to know?

The example is available as a notebook viewable at:

https://github.com/jerabaul29/public_bug_reports/blob/main/xarray/2024_01_24/xarray_and_datetimes.ipynb

Environment

INSTALLED VERSIONS ------------------ commit: None python: 3.11.5 (main, Sep 11 2023, 13:54:46) [GCC 11.2.0] python-bits: 64 OS: Linux OS-release: 6.5.0-14-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.12.1 libnetcdf: 4.8.1 xarray: 2023.9.0 pandas: 2.0.3 numpy: 1.25.2 scipy: 1.11.3 netCDF4: 1.6.2 pydap: None h5netcdf: None h5py: 3.10.0 Nio: None zarr: None cftime: 1.6.3 nc_time_axis: None PseudoNetCDF: None iris: None bottleneck: 1.3.5 dask: 2023.9.2 distributed: 2023.9.2 matplotlib: 3.7.2 cartopy: 0.21.1 seaborn: 0.13.0 numbagg: None fsspec: 2023.9.2 cupy: None pint: None sparse: None flox: None numpy_groupies: None setuptools: 68.0.0 pip: 23.2.1 conda: None pytest: None mypy: None IPython: 8.15.0 sphinx: None 
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     13221727 issue

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