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 1954809370,I_kwDOAMm_X850hAYa,8353,Update benchmark suite for asv 0.6.1,2448579,open,0,,,0,2023-10-20T18:13:22Z,2023-12-19T05:53:21Z,,MEMBER,,,,"The new asv version comes with decorators for parameterizing and skipping, and the ability to use `mamba` to create environments. https://github.com/airspeed-velocity/asv/releases https://asv.readthedocs.io/en/v0.6.1/writing_benchmarks.html#skipping-benchmarks This might help us reduce benchmark times a bit, or at least simplify the code some. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8353/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1954445639,I_kwDOAMm_X850fnlH,8350,optimize align for scalars at least,2448579,open,0,,,5,2023-10-20T14:48:25Z,2023-10-20T19:17:39Z,,MEMBER,,,,"### What happened? Here's a simple rescaling calculation: ```python import numpy as np import xarray as xr ds = xr.Dataset( {""a"": ((""x"", ""y""), np.ones((300, 400))), ""b"": ((""x"", ""y""), np.ones((300, 400)))} ) mean = ds.mean() # scalar std = ds.std() # scalar rescaled = (ds - mean) / std ``` The profile for the last line shows 30% (!!!) time spent in `align` (really `reindex_like`) except there's nothing to reindex when only scalars are involved! This is a small example inspired by a ML pipeline where this normalization is happening very many times in a tight loop. cc @benbovy ### What did you expect to happen? A fast path for when no reindexing needs to happen. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8350/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1954535213,PR_kwDOAMm_X85dZT47,8351,"[skip-ci] Add benchmarks for Dataset binary ops, chunk",2448579,closed,0,,,1,2023-10-20T15:31:36Z,2023-10-20T18:08:40Z,2023-10-20T18:08:38Z,MEMBER,,0,pydata/xarray/pulls/8351,"xref #8339 xref #8350 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8351/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1954360112,PR_kwDOAMm_X85dYtpz,8349,[skip-ci] dev whats-new,2448579,closed,0,,,1,2023-10-20T14:02:07Z,2023-10-20T17:28:19Z,2023-10-20T14:54:30Z,MEMBER,,0,pydata/xarray/pulls/8349," - [ ] Closes #xxxx - [ ] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8349/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull