[Python] Specify encoding/compression for many variables in xarray dataset when write to_netcdf

I have been writing out some xarray.Datasets that have multiple variables. Currently, in order to keep the size manageable I specify the encoding, e.g. zlib, but needs to be applied on a variable (dataArray) by variable basis.

What is the good way to apply the same encoding argument to all variables? e.g.

<xarray.Dataset>
Dimensions: (lat: 1440, lon: 2880)
Coordinates:
* lat (lat) float64 -90.0 -89.88 -89.75 -89.62 -89.5 -89.38 -89.25 ...
* lon (lon) float64 -180.0 -179.9 -179.8 -179.6 -179.5 -179.4 -179.2 ...
Data variables:
a1 (lat, lon) float64 nan nan nan nan nan nan nan nan 0.0 ...
b (lat, lon) float64 nan nan nan nan nan nan 0.0 0.0 0.0 ...
c (lat, lon) float64 nan nan nan nan nan nan nan nan 0.0 ...
d (lat, lon) float64 nan nan nan nan nan nan nan nan 0.0 ...
e (lat, lon) float64 nan nan nan nan nan nan nan nan 0.0 ...


when writing out this dataset, we would use:

ds.to_netcdf(filename, encoding={'a1':{'zlib': True,'complevel': 5},'b':{'zlib': True,'complevel': 5},'c':{'zlib': True,'complevel': 5},'d':{'zlib': True,'complevel': 5},'e':{'zlib': True,'complevel': 5}})


For more variables this gets very long winded. One option would be to write each dataarray to the netcdf in a sequential append basis, but this also seems convoluted when the dataset is ready to go.

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