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  • dcherian · 2 ✖

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  • apply_ufunc(dask='parallelized') with multiple outputs · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
628088800 https://github.com/pydata/xarray/issues/1815#issuecomment-628088800 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDYyODA4ODgwMA== dcherian 2448579 2020-05-13T16:04:20Z 2020-05-13T16:04:20Z MEMBER

So would you be re-doing the same computation by running .compute() separately on these objects?

Yes. but you can do dask.compute(xarray_obj1, xarray_obj2,...) or combine those objects appropriately into a Dataset and then call compute on that.

 
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   apply_ufunc(dask='parallelized') with multiple outputs 287223508
628050521 https://github.com/pydata/xarray/issues/1815#issuecomment-628050521 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDYyODA1MDUyMQ== dcherian 2448579 2020-05-13T15:02:01Z 2020-05-13T15:02:01Z MEMBER

Still needs to be implemented. Stephan's comment suggests a path forward (https://github.com/pydata/xarray/issues/1815#issuecomment-440089606) 

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   apply_ufunc(dask='parallelized') with multiple outputs 287223508

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