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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
1427457128 I_kwDOAMm_X85VFURo 7234 Inspecting arguments with accessors ljstrnadiii 3171991 open 0     2 2022-10-28T15:52:51Z 2022-10-31T19:30:38Z   NONE      

What is your issue?

I recently read about the suggested approach to extending xarray here: Extending xarray 2

We have a lot of functions on xarray datasets that are domain-specific enough to spatial mosaics that I think I want to start using these.

One issue I am seeing so far is that when I use the accessor in jupyter notebook, the arguments and docs are inspected and returned, which makes it nice and usable. However, within vscode, it is unable to inspect the args. The side effect is slower development and no more type checking, which isn’t ideal. This is also an issue with the rio accessor.

Am I missing something here? Has anyone noticed this and is there an existing fix? This must also be an issue with pandas custom accessors, too. Is there a way to more officially register accessors within my packages entry points?

For example ```

inside notebooks

ds.sp.my_function() # I can inspect as usual ds.rio.write_crs() # I can inspect as usual

inside vscode

ds.sp.my_function() # I can not inspect the args or their types ds.rio.write_crs() # I can not inspect the args or their types

```

I have seen sphinx-autosummary-accessors — sphinx-autosummary-accessors documentation 1, but that only seems relevant for doc generation.

 
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     xarray 13221727 issue
1339129609 I_kwDOAMm_X85P0X8J 6916 Given zarr-backed Xarray determine store and group ljstrnadiii 3171991 open 0     3 2022-08-15T15:16:24Z 2022-09-12T18:40:07Z   NONE      

What is your issue?

Given a zarr-backed xarray dataset, it would be nice to know the store and group and if it is zarr-backed or not.

The .encoding attribute has the store, but does not have the group, which would be required to specify the exact dataset. ``` dset = xr.open_zarr( store="gs://some/path", group='subdir' )

dset.encoding

{'source': 'gs://some/path'} ```

 
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     xarray 13221727 issue

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