I find @shoyer 's suggestion about custom accessor attributes very interesting!

the simplest of my use cases would be quite easy to implement:

``` python

MyLib

class MyLibGis(object): def init(self, xray_obj): self.obj = xray_obj self.georef = read_georef(xray_obj)

def subset(self, shapefile=None, roi=None):
    """Return a subset of DataSet (or DataArray)"""
    # compute regions of interests
    slicex, slicey = self.georef(stuff...)
    # return a sel of DataSet
    return self.obj.sel(x=slicex, y=slicey)

xray.register_accessor('gis', MyLibGis)

user code

import mylib import xray ds = xray.DataArray(...) ds = ds.gis.subset(shapefile='/path/to/shape') ```

This would already be quite cool! But would the mechanism allow to pass arguments to the MyLibGis class at construction time? This might also be wordy, maybe something like

ds = xray.DataArray(data, gis={'arg1':42})?

I guess that with these two mechanisms, I would be able to do almost everything I want to do with my netcdf files.

However, one other very important use case for me would be to add lazy "diagnostic" variables to a netcdf dataset. For example, if an atmospheric model output file contains the variables P andPB, then the dataset automatically proposes a new variable TP, which is the sum of P andPB. From the user perspective, this variable is no different than a variable on file. Of course, the data should be computed only on demand. It doesn't seem possible to do this without subclassing, but maybe I missed something?