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/pull/7494#issuecomment-1458453929,https://api.github.com/repos/pydata/xarray/issues/7494,1458453929,IC_kwDOAMm_X85W7j2p,5179430,2023-03-07T16:22:21Z,2023-03-07T16:22:21Z,CONTRIBUTOR,Thanks @Illviljan and @dcherian for helping to see this through.,"{""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1563270549
https://github.com/pydata/xarray/pull/7494#issuecomment-1456506306,https://api.github.com/repos/pydata/xarray/issues/7494,1456506306,IC_kwDOAMm_X85W0IXC,2448579,2023-03-06T16:52:13Z,2023-03-06T16:52:13Z,MEMBER,Thanks @agoodm this work prompted a bunch of internal cleanup!,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1563270549
https://github.com/pydata/xarray/pull/7494#issuecomment-1450003953,https://api.github.com/repos/pydata/xarray/issues/7494,1450003953,IC_kwDOAMm_X85WbU3x,10194086,2023-03-01T11:55:41Z,2023-03-01T11:55:41Z,MEMBER,"I think that's in the tests themselves
https://github.com/pydata/xarray/blob/6531b57f8c5cb7f3c564ff895c2e4b6573bb5521/xarray/tests/test_coding_times.py#L778
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1563270549
https://github.com/pydata/xarray/pull/7494#issuecomment-1449323880,https://api.github.com/repos/pydata/xarray/issues/7494,1449323880,IC_kwDOAMm_X85WYu1o,2448579,2023-03-01T04:30:54Z,2023-03-01T04:30:54Z,MEMBER,Seems like we're passing a DataArray instead of a Variable somewhere.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1563270549
https://github.com/pydata/xarray/pull/7494#issuecomment-1411206291,https://api.github.com/repos/pydata/xarray/issues/7494,1411206291,IC_kwDOAMm_X85UHUyT,5179430,2023-01-31T23:17:38Z,2023-01-31T23:17:38Z,CONTRIBUTOR,"@Illviljan I gave your update a quick test, it seems to work well enough and still maintains the performance improvement. It looks fine to me though I guess it looks like you still need to fix this failing mypy stuff now?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1563270549
https://github.com/pydata/xarray/pull/7494#issuecomment-1411177667,https://api.github.com/repos/pydata/xarray/issues/7494,1411177667,IC_kwDOAMm_X85UHNzD,14371165,2023-01-31T22:49:24Z,2023-01-31T22:49:24Z,MEMBER,"@agoodm, what you think of this version? Using xr.Variable directly seems a little easier to work with than trying to guess which type of array (cupy, dask, pint, backendarray, etc) is in the variable.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1563270549
https://github.com/pydata/xarray/pull/7494#issuecomment-1410253782,https://api.github.com/repos/pydata/xarray/issues/7494,1410253782,IC_kwDOAMm_X85UDsPW,5179430,2023-01-31T12:22:02Z,2023-01-31T12:26:37Z,CONTRIBUTOR,"> Thanks for the PR. However, does that actually make a difference? To me it looks like `_contains_cftime_datetimes` also only considers one element of the array.
>
> https://github.com/pydata/xarray/blob/b4515582ffc8b7f63632bfccd109d19889d00384/xarray/core/common.py#L1779-L1780
This isn't actually the line of code that's causing the performance bottleneck, it's the access to `var.data` in the function call that is actually problematic as I explained in the issue thread. You can verify this yourself running this simple example before and after applying the changes in this PR:
```python
import numpy as np
import xarray as xr
str_array = np.arange(100000000).astype(str)
ds = xr.DataArray(dims=('x',), data=str_array).to_dataset(name='str_array')
ds = ds.chunk(x=10000)
ds['str_array'] = ds.str_array.astype('O') # Needs to actually be object dtype to show the problem
ds.to_zarr('str_array.zarr')
%time xr.open_zarr('str_array.zarr')
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1563270549
https://github.com/pydata/xarray/pull/7494#issuecomment-1410233955,https://api.github.com/repos/pydata/xarray/issues/7494,1410233955,IC_kwDOAMm_X85UDnZj,10194086,2023-01-31T12:06:00Z,2023-01-31T12:06:00Z,MEMBER,"Thanks for the PR. However, does that actually make a difference? To me it looks like `_contains_cftime_datetimes` also only considers one element of the array.
https://github.com/pydata/xarray/blob/b4515582ffc8b7f63632bfccd109d19889d00384/xarray/core/common.py#L1779-L1780","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1563270549