issues: 143551401

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
143551401 MDU6SXNzdWUxNDM1NTE0MDE= 804 Compute multiple dask backed arrays at once 2783717 closed 0     5 2016-03-25T17:48:03Z 2018-03-07T01:40:49Z 2018-03-07T01:40:42Z NONE      

In dask, a user can compute multiple arrays in a single scheduler run using the dask.compute function:

``` python

a_computed, b_computed = dask.compute(a, b) ```

This is nice for when a and b might share intermediates. The same can be done currently in xarray if a and b are first put into a dataset:

``` python

both = xr.Dataset(dict(a=a, b=b)) both.load() # Compute all the arrays in a single pass ```

This is fine, but it might also be nice to be able to do this without first putting everything into a dataset. I'm not sure what a good api is here, as xarray objects mutate when computed. Perhaps just adding an xr.compute(*args) function that fully realizes all dask backed variables.

``` python

xr.compute(a, b) # a and b now contain numpy arrays, not dask arrays ```

 
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