html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue https://github.com/pydata/xarray/issues/1721#issuecomment-345384115,https://api.github.com/repos/pydata/xarray/issues/1721,345384115,MDEyOklzc3VlQ29tbWVudDM0NTM4NDExNQ==,6628425,2017-11-17T22:33:37Z,2017-11-17T22:33:37Z,MEMBER,"Thanks @shoyer, I think it's the files written by the 'scipy' engine and read by the 'netcdf4' engine. Here is a minimal example: ``` In [1]: import xarray as xr In [2]: da = xr.DataArray([1, 2, 3], dims=['x']) In [3]: da.to_netcdf('test_netcdf4.nc', format='NETCDF3_CLASSIC', engine='netcdf4') In [4]: ds = xr.open_dataset('test_netcdf4.nc', engine='netcdf4') In [5]: ds = xr.open_dataset('test_netcdf4.nc', engine='scipy') In [6]: da.to_netcdf('test_scipy.nc', format='NETCDF3_CLASSIC', engine='scipy') In [7]: ds = xr.open_dataset('test_scipy.nc', engine='scipy') In [8]: ds = xr.open_dataset('test_scipy.nc', engine='netcdf4') --------------------------------------------------------------------------- IOError Traceback (most recent call last) in () ----> 1 ds = xr.open_dataset('test_scipy.nc', engine='netcdf4') //anaconda/envs/research/lib/python2.7/site-packages/xarray/backends/api.pyc in open_dataset(filename_or_obj, group, decode_cf, mask_and_scale, decode_times, autoclose, concat_characters, decode_coords, engine, chunks, lock, cache, drop_variables) 280 if engine == 'netcdf4': 281 store = backends.NetCDF4DataStore(filename_or_obj, group=group, --> 282 autoclose=autoclose) 283 elif engine == 'scipy': 284 store = backends.ScipyDataStore(filename_or_obj, //anaconda/envs/research/lib/python2.7/site-packages/xarray/backends/netCDF4_.pyc in __init__(self, filename, mode, format, group, writer, clobber, diskless, persist, autoclose) 208 diskless=diskless, persist=persist, 209 format=format) --> 210 self.ds = opener() 211 self._autoclose = autoclose 212 self._isopen = True //anaconda/envs/research/lib/python2.7/site-packages/xarray/backends/netCDF4_.pyc in _open_netcdf4_group(filename, mode, group, **kwargs) 183 import netCDF4 as nc4 184 --> 185 ds = nc4.Dataset(filename, mode=mode, **kwargs) 186 187 with close_on_error(ds): netCDF4/_netCDF4.pyx in netCDF4._netCDF4.Dataset.__init__() netCDF4/_netCDF4.pyx in netCDF4._netCDF4._ensure_nc_success() IOError: [Errno -36] NetCDF: Invalid argument: '/Users/skc/test_scipy.nc' ``` Here's a link to the issue upstream: https://github.com/Unidata/netcdf-c/issues/657.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,274392275 https://github.com/pydata/xarray/issues/1721#issuecomment-345317906,https://api.github.com/repos/pydata/xarray/issues/1721,345317906,MDEyOklzc3VlQ29tbWVudDM0NTMxNzkwNg==,6628425,2017-11-17T18:02:29Z,2017-11-17T18:30:44Z,MEMBER,"@ocefpaf thanks, empirically the original did the trick, but I have edited it for correctness.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,274392275 https://github.com/pydata/xarray/issues/1721#issuecomment-345316396,https://api.github.com/repos/pydata/xarray/issues/1721,345316396,MDEyOklzc3VlQ29tbWVudDM0NTMxNjM5Ng==,6628425,2017-11-17T17:56:29Z,2017-11-17T18:02:18Z,MEMBER,"@shoyer I initially ran into that too. I think depending on the libraries you have installed (or seek to install) conda may not let you upgrade to libnetcdf 4.5.0. To get libnetcdf 4.5.0 I created a clean environment with the following specification file: ``` name: test_xarray_libnetcdf45 channels: - conda-forge dependencies: - python=3.6 - netcdf4 - libnetcdf=4.5.0 - numpy - mock - pandas - pytest - pip - dask - scipy ``` Then from within that environment I did an editable install of the xarray master branch and ran the test suite.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,274392275