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  • Create `xarray.Dataset` from a `netCDF4.Dataset` object · 5 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
347906958 https://github.com/pydata/xarray/issues/1304#issuecomment-347906958 https://api.github.com/repos/pydata/xarray/issues/1304 MDEyOklzc3VlQ29tbWVudDM0NzkwNjk1OA== shoyer 1217238 2017-11-29T16:02:03Z 2017-11-29T16:02:03Z MEMBER 
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   Create `xarray.Dataset` from a `netCDF4.Dataset` object 213082731
285745464 https://github.com/pydata/xarray/issues/1304#issuecomment-285745464 https://api.github.com/repos/pydata/xarray/issues/1304 MDEyOklzc3VlQ29tbWVudDI4NTc0NTQ2NA== shoyer 1217238 2017-03-10T18:22:26Z 2017-03-10T18:22:26Z MEMBER

Yes, from_ncdataset would be better.

 
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   Create `xarray.Dataset` from a `netCDF4.Dataset` object 213082731
285737819 https://github.com/pydata/xarray/issues/1304#issuecomment-285737819 https://api.github.com/repos/pydata/xarray/issues/1304 MDEyOklzc3VlQ29tbWVudDI4NTczNzgxOQ== andreas-h 358378 2017-03-10T17:52:22Z 2017-03-10T17:52:22Z CONTRIBUTOR

Sounds good. However, maybe from_ncdataset would avoid possible name confusion given that there's a Dataset in both xarray and netCDF4? On the other hand, at least in this context one of the options wouldn't make sense ... What do you think?

 
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   Create `xarray.Dataset` from a `netCDF4.Dataset` object 213082731
285730870 https://github.com/pydata/xarray/issues/1304#issuecomment-285730870 https://api.github.com/repos/pydata/xarray/issues/1304 MDEyOklzc3VlQ29tbWVudDI4NTczMDg3MA== shoyer 1217238 2017-03-10T17:25:36Z 2017-03-10T17:26:12Z MEMBER

This does seem like a reasonable thing to do in the advanced API. I would suggest adding another constructor in the form of a classmethod, maybe NetCDF4DataStore.from_dataset?

 
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   Create `xarray.Dataset` from a `netCDF4.Dataset` object 213082731
285398877 https://github.com/pydata/xarray/issues/1304#issuecomment-285398877 https://api.github.com/repos/pydata/xarray/issues/1304 MDEyOklzc3VlQ29tbWVudDI4NTM5ODg3Nw== fmaussion 10050469 2017-03-09T16:16:58Z 2017-03-09T16:16:58Z MEMBER

I also needed something like this but @shoyer decided against this change until there is a cleaner datastore API.

A (very) dirty workaround it to subclass xarray.backends.NetCDF4DataStore and redefine __init__ to accept netcdf datasets as argument:

``` class _NetCDF4DataStore(NetCDF4DataStore): """Just another way to init xarray's datastore.""" def init(self, filename, mode='r', format='NETCDF4', group=None, writer=None, clobber=True, diskless=False, persist=False, ds=None): import netCDF4 as nc4 if format is None: format = 'NETCDF4' if ds is None: ds = nc4.Dataset(filename, mode=mode, clobber=clobber, diskless=diskless, persist=persist, format=format) with close_on_error(ds): self.ds = _nc4_group(ds, group, mode) self.format = format self.is_remote = False self._filename = filename super(NetCDF4DataStore, self).init(writer)

nc = netCDF4.Dataset(filename) ds = xr.open_dataset(_NetCDF4DataStore(filename, ds=nc)) ```

 
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   Create `xarray.Dataset` from a `netCDF4.Dataset` object 213082731

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