issue_comments

Just wanted to link to a somewhat related discussion happening in brian-rose/climlab#50.

Have you considered implementing a custom datastore for your model? Datastores just have to provide variables. This might be the most straightforward option.

On Mar 9, 2017, at 6:07 AM, Benoit Bovy notifications@github.com wrote:

Is it safe to use xarray.core.variable.as_variable() externally? I guess that currently it is not.

I have a specific use case where this would be very useful.

I'm working on a package that heavily uses and extends xarray for landscape evolution modeling, and inside a custom class for model parameters I want to be able to create xarray.Variable objects on the fly from any provided object, e.g., a scalar value, an array-like, a (dims, data[, attrs]) tuple, another xarray.Variable, a xarray.DataArray... exactly what xarray.core.variable.as_variable() does.

Although I know that Variable objects are not needed in most use cases, in this specific case a clean solution would be the following

import xarray as xr

class Parameter(object):

def to_variable(self, obj):
    return xr.as_variable(obj)
    # ... some validation logic on, e.g., data type, value bounds, dimensions...
    # ... add default attributes to the

I don't think it is a viable option to copy as_variable() and all its dependent code in my package as it seems to have quite a lot of logic implemented.

A workaround using only public API would be something like:

class Parameter(object):

def to_variable(self, obj):
    return xr.Dataset(data_vars={'v': obj}).variables['v']

but it feels a bit hacky.

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