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1 row where repo = 13221727, "updated_at" is on date 2019-08-30 and user = 6645714 sorted by updated_at descending

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  • xarray · 1 ✖
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
199032440 MDU6SXNzdWUxOTkwMzI0NDA= 1193 Reading netcdf containing empty N-d string arrays causes exception petercable 6645714 closed 0     4 2017-01-05T19:00:22Z 2019-08-30T23:18:04Z 2019-08-30T23:18:04Z CONTRIBUTOR      

For example:

``` import xarray as xr import numpy as np

a = np.array([[]], 'str')

ds = xr.Dataset() ds['x'] = (['dim0', 'dim1'], a, {}) ds.to_netcdf('test.nc')

ds = xr.open_dataset('test.nc') ds.load() ```

The exception occurs in the call to conventions.char_to_string:

def char_to_string(arr): """Like netCDF4.chartostring, but faster and more flexible. """ # based on: http://stackoverflow.com/a/10984878/809705 arr = np.array(arr, copy=False, order='C') kind = arr.dtype.kind if kind not in ['U', 'S']: raise ValueError('argument must be a string') return arr.view(kind + str(arr.shape[-1]))[..., 0]

... return arr.view(kind + str(arr.shape[-1]))[..., 0] TypeError: data-type must not be 0-sized

I am able to avoid the exception locally by testing that the last dimension is > 0 prior to creating a view:

def char_to_string(arr): """Like netCDF4.chartostring, but faster and more flexible. """ # based on: http://stackoverflow.com/a/10984878/809705 arr = np.array(arr, copy=False, order='C') kind = arr.dtype.kind if kind not in ['U', 'S']: raise ValueError('argument must be a string') if arr.shape[-1] > 0: return arr.view(kind + str(arr.shape[-1]))[..., 0] return arr

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  completed xarray 13221727 issue

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