xarray v 2023.9.0: ```ValueError: unable to infer dtype on variable 'time'; xarray cannot serialize arbitrary Python objects```
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评估
调研方向
从提供的最小示例开始,跟踪 datetime 值 time 变量的 Dataset.to_netcdf 路径。通过一个针对性的回归测试确认该行为,并在示例能够在没有 dtype 错误的情况下成功序列化为兼容 CF 的 netCDF 文件后,将 issue 视为完成。
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描述
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
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.
- 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:
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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