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
957432870,MDExOlB1bGxSZXF1ZXN0NzAwODYwMzY4,5661,Speed up _mapping_repr,14371165,closed,0,,,8,2021-08-01T08:44:17Z,2022-08-12T09:07:44Z,2021-08-02T19:45:16Z,MEMBER,,0,pydata/xarray/pulls/5661,"Creating a ordered list for filtering purposes using `.items()` turns out being rather slow. Use `.keys()` instead as that doesn't trigger a bunch of dataarray initializations.

- [x] Passes `pre-commit run --all-files`

Test case:

```python
import numpy as np
import xarray as xr

a = np.arange(0, 2000)
data_vars = dict()
for i in a:
    data_vars[f""long_variable_name_{i}""] = xr.DataArray(
        name=f""long_variable_name_{i}"",
        data=np.arange(0, 20),
        dims=[f""long_coord_name_{i}_x""],
        coords={f""long_coord_name_{i}_x"": np.arange(0, 20) * 2},
    )
ds0 = xr.Dataset(data_vars)
ds0.attrs = {f""attr_{k}"": 2 for k in a}
```


Before:
```python
%timeit print(ds0)
14.6 s ± 215 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
```

After:
```python
%timeit print(ds0)
120 ms ± 2.06 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)
```
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