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.,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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257643746,MDExOlB1bGxSZXF1ZXN0MTQxMDE3NTcw,1573,DOC: Update broken link to dask blog post,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/,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1573/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull