html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/1375#issuecomment-520675205,https://api.github.com/repos/pydata/xarray/issues/1375,520675205,MDEyOklzc3VlQ29tbWVudDUyMDY3NTIwNQ==,1217238,2019-08-13T03:31:14Z,2019-08-13T03:31:14Z,MEMBER,"This is working now on the `master` branch!

Once we get a few more kinks worked out, it will be in the next release.

I've started another issue for discussing how xarray could integrate sparse arrays better into its API: https://github.com/pydata/xarray/issues/3213","{""total_count"": 4, ""+1"": 4, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,221858543
https://github.com/pydata/xarray/issues/1375#issuecomment-504777412,https://api.github.com/repos/pydata/xarray/issues/1375,504777412,MDEyOklzc3VlQ29tbWVudDUwNDc3NzQxMg==,1217238,2019-06-23T18:54:33Z,2019-06-23T18:54:33Z,MEMBER,"It will need some experimentation, but I think things should be pretty close after NumPy 1.17 is released. Potentially it could be as easy as adjusting the rules xarray uses for casting in `xarray.core.variable.as_compatible_data`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,221858543
https://github.com/pydata/xarray/issues/1375#issuecomment-403155235,https://api.github.com/repos/pydata/xarray/issues/1375,403155235,MDEyOklzc3VlQ29tbWVudDQwMzE1NTIzNQ==,1217238,2018-07-06T21:49:27Z,2018-07-06T21:49:27Z,MEMBER,"> Would it be an option to use dask's sparse support?
http://dask.pydata.org/en/latest/array-sparse.html
This way xarray could let dask do the main work.

In principle this would work, though I would prefer to support it directly in xarray, too.

> I know that NetCDF4 has some conventions how to store sparse data, but do we have to implement our own conversion mechanisms for each sparse type?

Yes, we would need to implement a convention for handling sparse array data.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,221858543
https://github.com/pydata/xarray/issues/1375#issuecomment-395223735,https://api.github.com/repos/pydata/xarray/issues/1375,395223735,MDEyOklzc3VlQ29tbWVudDM5NTIyMzczNQ==,1217238,2018-06-06T21:43:40Z,2018-06-06T21:43:40Z,MEMBER,"See also: https://github.com/pydata/xarray/issues/1938

The major challenge now is the dispatching mechanism, which hopefully http://www.numpy.org/neps/nep-0018-array-function-protocol.html will solve.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,221858543
https://github.com/pydata/xarray/issues/1375#issuecomment-294250748,https://api.github.com/repos/pydata/xarray/issues/1375,294250748,MDEyOklzc3VlQ29tbWVudDI5NDI1MDc0OA==,1217238,2017-04-14T22:46:10Z,2017-04-14T22:47:01Z,MEMBER,"Yes, I would say this is in scope, as long as we can keep most of the data-type specific logic out of xarray's core (which seems doable).

Currently, we define most of our operations on duck arrays in https://github.com/pydata/xarray/blob/master/xarray/core/duck_array_ops.py

There are a few other hacks throughout the codebase, which can find by searching for ""dask_array_type"": https://github.com/pydata/xarray/search?p=1&q=dask_array_type&type=&utf8=%E2%9C%93

It's pretty crude, but basically this would need to be extended to implement many of these methods on for sparse arrays, too. Ideally we would define xarray's adapter logic into more cleanly separated submodules, perhaps using multiple dispatch. Even better, we would make this public API, so you can write something like `xarray.register_data_type(MySparseArray)` to register a type as valid for xarray's `.data` attribute.

It looks like `__array_ufunc__` will actually finally land in NumPy 1.13, which might make this easier.

See also https://github.com/pydata/xarray/pull/1118","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,221858543