pull_requests: 784291700
This data as json
| id | node_id | number | state | locked | title | user | body | created_at | updated_at | closed_at | merged_at | merge_commit_sha | assignee | milestone | draft | head | base | author_association | auto_merge | repo | url | merged_by |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 784291700 | PR_kwDOAMm_X84uv1d0 | 6007 | closed | 0 | Use condas dask-core in ci instead of dask to speedup ci and reduce dependencies | 12237157 | <!-- Feel free to remove check-list items aren't relevant to your change --> - [ ] Closes #xxxx - [ ] Tests added - [ ] Passes `pre-commit run --all-files` - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` Tried to reduce dependencies from installing dask via conda which installs like pip install dask[complete]. dask-core is like pip install dask. https://github.com/xgcm/xhistogram/pull/71#discussion_r752738286 Why? dask[complete] includes bokeh etc which are not needed here and likely speed up CI setup/install times but now dask and dask-core are conda installed :( seems like iris installs dask https://github.com/conda-forge/iris-feedstock/blob/master/recipe/meta.yaml, so this would require an iris-feedstock PR first linking https://github.com/SciTools/iris/pull/4434 and https://github.com/conda-forge/iris-feedstock/pull/77 | 2021-11-19T02:02:41Z | 2021-11-28T21:01:36Z | 2021-11-28T04:40:34Z | 2021-11-28T04:40:34Z | cc03589dadfef8d7ebcb95f7adc302895cf0fcbc | 0 | 7f3cefb1af8942f837572c246553bbb55b962035 | 95394d5bcbd7d73bae34c091a080c42bcfc9f07d | CONTRIBUTOR | 13221727 | https://github.com/pydata/xarray/pull/6007 |
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