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/2560#issuecomment-445524755,https://api.github.com/repos/pydata/xarray/issues/2560,445524755,MDEyOklzc3VlQ29tbWVudDQ0NTUyNDc1NQ==,2622379,2018-12-09T10:06:24Z,2018-12-09T10:06:24Z,NONE,"I have done a bit more testing on this, and I believe the issue may not necessarily be with ``xarray`` but with ``rasterio`` (disclaimer: I haven't tested your pull request yet). I can reproduce the following on Ubuntu and on Travis CI. On Mac OS none of these errors occur. Minimum example: ```python import xarray as xr import numpy as np import rasterio # The rasterio import makes the last line of this code fail. ds = xr.Dataset() ds['data'] = (('y', 'x'), np.ones((10, 10))) ds.to_netcdf('test.nc', engine='netcdf4') ``` I was able to fix the error by prepending a ```python import netCDF4 ``` at the very top of the script. A very similar thing happens with ``engine='h5netcdf'``. The same script works without ``rasterio``, fails with ``rasterio``, and can be fixed by inserting ``import h5netcdf`` at the top of the script.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,383057458 https://github.com/pydata/xarray/issues/2560#issuecomment-445270674,https://api.github.com/repos/pydata/xarray/issues/2560,445270674,MDEyOklzc3VlQ29tbWVudDQ0NTI3MDY3NA==,2622379,2018-12-07T15:39:05Z,2018-12-07T15:39:05Z,NONE,I am having the exact same problem. Have you found a solution/workaround?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,383057458 https://github.com/pydata/xarray/issues/2159#issuecomment-410361639,https://api.github.com/repos/pydata/xarray/issues/2159,410361639,MDEyOklzc3VlQ29tbWVudDQxMDM2MTYzOQ==,2622379,2018-08-03T20:03:21Z,2018-08-03T20:14:17Z,NONE,"Yes, `xarray` should support that very easily -- assuming you have `dask` installed: ```python ds = auto_merge('*.nc') ds.to_netcdf('larger_than_memory.nc') ``` `auto_merge` conserves the chunk sizes resulting from the individual files. If the single files are still too large to fit into memory individually you can rechunk to smaller chunk sizes. The same goes of course for the original `xarray.open_mfdataset`. I tested it on a ~25 GB dataset (on a machine with less memory than that). *Note*: `ds = auto_merge('*.nc')` actually runs in a matter of milliseconds, as it merely provides a view of the merged dataset. Only once you call `ds.to_netcdf('larger_than_memory.nc')` all the disk I/O happens.","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 0, ""eyes"": 0}",,324350248 https://github.com/pydata/xarray/issues/2159#issuecomment-410348249,https://api.github.com/repos/pydata/xarray/issues/2159,410348249,MDEyOklzc3VlQ29tbWVudDQxMDM0ODI0OQ==,2622379,2018-08-03T19:07:10Z,2018-08-03T19:12:21Z,NONE,"I just had the exact same problem, and while I didn't yet have time to dig into the source code of `xarray.open_mfdataset`, I wrote my own function to achieve this: https://gist.github.com/jnhansen/fa474a536201561653f60ea33045f4e2 Maybe it's helpful to some of you. Note that I make the following assumptions (which are reasonable for my use case): * the data variables in each part are identical * equality of the first element of two coordinate arrays is sufficient to assume equality of the two coordinate arrays","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,324350248