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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
146812468 MDU6SXNzdWUxNDY4MTI0Njg= 820 Dataset.__repr__ causing dask to be computed. andrewdhicks 15901813 closed 0     3 2016-04-08T04:43:18Z 2019-10-01T04:18:38Z 2019-10-01T04:18:37Z NONE      

Printing a Dataset object will show array values (#206), but it will also cause a dask-backed array to be computed so that the data variable values can be computed:

<xarray.Dataset> Dimensions: (time: 182, x: 420, y: 489) Coordinates: * time (time) datetime64[ns] 1990-03-02T23:11:16 1990-03-02T23:11:39 ... * y (y) float64 -3.919e+06 -3.919e+06 -3.919e+06 -3.919e+06 ... * x (x) float64 1.538e+06 1.538e+06 1.538e+06 1.538e+06 1.538e+06 ... Data variables: band_20 (time, y, x) float64 729.0 612.0 579.0 629.0 862.0 1.027e+03 ... band_10 (time, y, x) float64 476.0 375.0 357.0 416.0 586.0 708.0 730.0 ... band_50 (time, y, x) float64 2.175e+03 634.0 245.0 546.0 1.788e+03 ... ...

When a DataArray is printed, it doesn't compute values when using dask:

<xarray.DataArray u'ls5_nbar_albers' (time: 182, y: 489, x: 420)> dask.array<concate..., shape=(182, 489, 420), dtype=float64, chunksize=(1, 489, 420)> Coordinates: * time (time) datetime64[ns] 1990-03-02T23:11:16 1990-03-02T23:11:39 ... * y (y) float64 -3.919e+06 -3.919e+06 -3.919e+06 -3.919e+06 ... * x (x) float64 1.538e+06 1.538e+06 1.538e+06 1.538e+06 1.538e+06 ...

There is a check to make sure the data is not remote, but not based on dask status, see: https://github.com/pydata/xarray/blob/master/xarray/core/formatting.py#L173 Is there a way to indicate that computing a particular dask is an expensive operation and it should not be calculated?

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  completed xarray 13221727 issue
257643746 MDExOlB1bGxSZXF1ZXN0MTQxMDE3NTcw 1573 DOC: Update broken link to dask blog post andrewdhicks 15901813 closed 0     1 2017-09-14T08:56:27Z 2017-09-14T17:04:22Z 2017-09-14T17:04:21Z NONE   0 pydata/xarray/pulls/1573

Blog post now at https://www.anaconda.com/blog/developer-blog/xray-dask-out-core-labeled-arrays-python/

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    xarray 13221727 pull

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