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  • jhamman · 2 ✖

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  • Stop loading tutorial data by default · 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
435738466 https://github.com/pydata/xarray/pull/2538#issuecomment-435738466 https://api.github.com/repos/pydata/xarray/issues/2538 MDEyOklzc3VlQ29tbWVudDQzNTczODQ2Ng== jhamman 2443309 2018-11-05T02:39:50Z 2018-11-05T02:39:50Z MEMBER

@shoyer - I think I was tracking with you. I've gone ahead and deprecated the current load_dataset in favor of the open_dataset name. The switch is accompanied by a change in behavior as well.

 
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   Stop loading tutorial data by default 377075253
435688104 https://github.com/pydata/xarray/pull/2538#issuecomment-435688104 https://api.github.com/repos/pydata/xarray/issues/2538 MDEyOklzc3VlQ29tbWVudDQzNTY4ODEwNA== jhamman 2443309 2018-11-04T17:19:15Z 2018-11-04T17:19:15Z MEMBER

@shoyer - absolutely we'll get better performance with numpy arrays in this case. So I'm trying to use our tutorial datasets for some examples with dask (dask/dask-examples#51). The docstring for the load_dataset function states that we can pass kwargs on to the open_dataset function but if we pass chunks to the load_dataset call currently, we still get data back as numpy arrays. We have some other options here:

  1. if chunks is a kwargs, return a dataset with data as persisted dask arrays
  2. provide a second function to handle returning datasets using the same logic as open_dataset (caching, dask arrays, lazy loading, etc.)
  3. tell people (like me) to rechunk the dataset after the fact

(3) won't require any changes but makes it a little harder to connect the typical use pattern of open_dataset with tutorial.load_dataset. 

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   Stop loading tutorial data by default 377075253

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