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/2995#issuecomment-497066189,https://api.github.com/repos/pydata/xarray/issues/2995,497066189,MDEyOklzc3VlQ29tbWVudDQ5NzA2NjE4OQ==,868027,2019-05-29T18:56:17Z,2019-05-29T18:56:17Z,CONTRIBUTOR,"Thanks @rabernat I had forgotten about the other netcdf storage engines... do you know if h5netcdf stable enough that I should use in ""production"" outside of xarray for my netcdf4 reading/writing needs?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,449706080
https://github.com/pydata/xarray/issues/2995#issuecomment-497026828,https://api.github.com/repos/pydata/xarray/issues/2995,497026828,MDEyOklzc3VlQ29tbWVudDQ5NzAyNjgyOA==,868027,2019-05-29T17:11:10Z,2019-05-29T17:12:51Z,CONTRIBUTOR,"Hi @Non-Descript-Individual 

I've found that the netcdf4-python library really wants to have direct access to a disk/filesystem to work, it also really wants to do its own file access management. I've always attributed this to the python library being a wrapper for the netcdf C library. 

My guess would be that the easiest way to do what you want is to separate the writing of the netcdf file step in xarray from the putting the file into S3. Something like this:

```python
x.to_netcdf('temp_file.nc')
s3.upload_file('temp_file.nc', 'bucketname', 'real_name_for_temp_file.nc')
```

The netcdf4-python library does seem to provide an interface for the ""diskless"" flags. In this case, from the examples it looks to give you a bunch of bytes in a `memoryview` object on calling `close()`. I'm not sure this is accessible from xarray though.

Alternatively, @rabernat is an advocate of using zarr when putting netcdf compatible data into cloud storage, the zarr docs [provide an example using s3fs ](https://zarr.readthedocs.io/en/stable/tutorial.html#distributed-cloud-storage)

Quick edit: [Here is the `to_zarr` docs in xarray](http://xarray.pydata.org/en/stable/generated/xarray.Dataset.to_zarr.html)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,449706080