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
1710752209,PR_kwDOAMm_X85QjIMH,7844,Improve to_dask_dataframe performance,14371165,closed,0,,,1,2023-05-15T20:08:24Z,2023-05-25T20:08:54Z,2023-05-25T20:08:54Z,MEMBER,,0,pydata/xarray/pulls/7844,"* ds.chunks loops all the variables, do it once.
* Faster to create a meta dataframe once than letting dask guess 2000 times.
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1718427036,PR_kwDOAMm_X85Q88zP,7857,Avoid explicit loop when updating OrderedSet,14371165,closed,0,,,0,2023-05-21T09:06:58Z,2023-05-25T20:08:35Z,2023-05-25T20:08:34Z,MEMBER,,0,pydata/xarray/pulls/7857,"Following recommendation from: https://github.com/pydata/xarray/pull/7824#discussion_r1196114696

```python
# main:
a = tuple(f""dim_{i}"" for i in range(500))
%timeit OrderedSet(a)
46 µs ± 2.26 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)

# This PR:
a = tuple(f""dim_{i}"" for i in range(500))
%timeit OrderedSet(a)
28.9 µs ± 476 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)
```
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