issue_comments: 366833780

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https://github.com/pydata/xarray/issues/1914#issuecomment-366833780 https://api.github.com/repos/pydata/xarray/issues/1914 366833780 MDEyOklzc3VlQ29tbWVudDM2NjgzMzc4MA== 10928117 2018-02-20T00:27:36Z 2018-02-20T00:27:36Z NONE

After preparing list similar to [{'x': 0, 'y': 'a'}, {'x': 1, 'y': 'a'}, ...] interaction with cluster is quite efficient. One can easily pass such a thing to async_map of ipyparallel.

Thanks for your suggestion, I need to try few things. I also want to try to extend it to function that computes few different things that could be multi-valued, e.g. ```python def dummy(x, y): ds = xr.Dataset( {'out1': ('n', [1x, 2x, 3*x]), 'out2': ('m', [x, y])}, coords = {'x': x, 'y': y, 'n': range(3), 'm': range(2)} )

return ds

``` and then group together such outputs... Ok, I know. I go from simple problem to much more complicated one, but isn't it the case usually?

 
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