issues: 756425955
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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 |
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| 756425955 | MDU6SXNzdWU3NTY0MjU5NTU= | 4648 | Comprehensive benchmarking suite | 2448579 | open | 0 | 6 | 2020-12-03T18:01:57Z | 2023-06-15T16:56:00Z | MEMBER | I think a good "infrastructure" target for the NASA OSS call would be to expand our benchmarking suite (https://pandas.pydata.org/speed/xarray/#/) AFAIK running these in a useful manner on CI is still unsolved (please correct me if I'm wrong). But we can always run it on an NCAR machine using a cron job. Thoughts? cc @scottyhq A quick survey of work needed (please append): - [ ] indexing & slicing #3382 #2799 #2227 - [ ] DataArray construction #4744 - [ ] attribute access #4741, #4742 - [ ] property access #3514 - [ ] reindexing? https://github.com/pydata/xarray/issues/1385#issuecomment-297539517 - [x] alignment #3755, #7738 - [ ] assignment #1771 - [ ] coarsen - [x] groupby #659 #7795 #7796 - [x] resample #4498 #7795 - [ ] weighted #4482 #3883 - [ ] concat #7824 - [ ] merge - [ ] open_dataset, open_mfdataset #1823 - [ ] stack / unstack - [ ] apply_ufunc? - [x] interp #4740 #7843 - [ ] reprs #4744 - [x] to_(dask)_dataframe #7844 #7474 Related: #3514 |
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13221727 | issue |