You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
After installing dask and distributed with conda-forge
If I run python -m dask...
$ python -m dask
shows what we want:
Usage: python -m dask [OPTIONS] COMMAND [ARGS]...
Dask command line interface.
Options:
--version Show the version and exit.
-h, --help Show this message and exit.
Commands:
docs Open Dask documentation (https://docs.dask.org/) in a web browser.
info Information about your dask installation.
scheduler Launch a distributed scheduler.
ssh Launch a distributed cluster over SSH.
worker Launch a distributed worker attached to an existing SCHEDULER.
but
$ dask
shows
Usage: dask [OPTIONS] COMMAND [ARGS]...
Dask command line interface.
Options:
--version Show the version and exit.
-h, --help Show this message and exit.
Commands:
docs Open Dask documentation (https://docs.dask.org/) in a web browser.
info Information about your dask installation.
$ python -m dask is running dask.__main__:main while $ dask is running dask.cli:cli. (note the pip(setuptools) installation uses dask.__main__:main). I think the conda-forge entry point should be dask.__main__:main
Given the pain around that, would like to propose hardening the Click requirement in Dask going forward ( dask/dask#9595 ). Ideally would like to include that in this release
We haven't quite gotten dask/distributed#5648 over the finish line yet, so I'm going to push up PRs to put an upper bound of bokeh < 3 for dask and distributed given that we know there are compatibility issues with the bokeh=3 release scheduled to come out later today (cc @fjetter@crusaderky)
Alright, PyPI and conda-forge packages are released.
We ran into a problem building the Python 3.8 dask-notebook image over in dask-docker (xref dask/dask-docker#255) due to an issue in the underlying jupyter/base-notebook notebook (xref jupyter/docker-stacks#1810). I've attempted a couple of possible fixes, but haven't gotten those build to work yet. I've proposed a temporary workaround in dask/dask-docker#256 where we drop Python 3.8 builds. This is a possible workaround, but admittedly feels a bit heavy handed. I'm on PTO next week -- @jacobtomlinson@jakirkham@charlesbluca could I ask you to handle docker images for this release by either finding an actual fix, or by merging the PR that temporarily drops Python 3.8 builds?
There isn't anything I'm aware of that would prevent a hotfix, though dask/distributed#7224 is a non-trivial change. Perhaps @gjoseph92 can comment on whether it's likely to be an issue (I suspect he'd be fine with it)
I think @gjoseph92 is comfortable including that change has he asked for it to be included in the 2022.10.1 release, but it just didn't make it in time (xref #283 (comment))
EDIT: queuing is also still behind a feature flag, so I think it's safe to move forward with that change included
could I ask you to handle docker images for this release by either finding an actual fix, or by merging the PR that temporarily drops Python 3.8 builds?
Any opposition to unblocking the 3.8 Docker builds locally with dask/dask-docker#257 until the upstream issue is resolved? This would involve patching the impacted Jupyter dockerfile, which could get hairy in the long run, but it doesn't seem like CI is running very often on dask-docker for this to be an issue.
As to Jupyter docker-stacks, outlined a path forward in comment ( jupyter/docker-stacks#1810 (comment) ). If anyone has bandwidth to try, should be a couple line change
Updating this thread, Charles' workaround was merged yesterday. Mamba released 1.0.0 early today. This subsequently fixed Jupyter docker-stacks ( jupyter/docker-stacks#1810 (comment) ). With that fixed, Charles reverted the workaround ( dask/dask-docker#260 ).
Edit: Also merged Charles PR yesterday to mark conda-forge packages broken.
Activity
douglasdavis commentedon Oct 25, 2022
Digging a bit with the CLI issue..
After installing
daskanddistributedwith conda-forgeIf I run
python -m dask...shows what we want:
but
shows
$ python -m daskis runningdask.__main__:mainwhile$ daskis runningdask.cli:cli. (note the pip(setuptools) installation usesdask.__main__:main). I think the conda-forge entry point should bedask.__main__:maindouglasdavis commentedon Oct 25, 2022
Opened a PR conda-forge/dask-feedstock#200fixed in dask-core-feedstock!jakirkham commentedon Oct 25, 2022
Thanks all for helping dig into the CLI issues! 🙏
Given the pain around that, would like to propose hardening the Click requirement in Dask going forward ( dask/dask#9595 ). Ideally would like to include that in this release
jrbourbeau commentedon Oct 27, 2022
I've opened this issue around requiring
python<3.11dask/dask#9605. If folks have thoughts on the topic I'd appreciate feedback on that issue.jrbourbeau commentedon Oct 28, 2022
We haven't quite gotten dask/distributed#5648 over the finish line yet, so I'm going to push up PRs to put an upper bound of
bokeh < 3fordaskanddistributedgiven that we know there are compatibility issues with thebokeh=3release scheduled to come out later today (cc @fjetter @crusaderky)mrocklin commentedon Oct 28, 2022
@gjoseph92 @fjetter are we turning on task queuing on the scheduler by default in this release?
gjoseph92 commentedon Oct 28, 2022
No, it won't be ready in time. See dask/distributed#7213.
jrbourbeau commentedon Oct 28, 2022
bokeh < 3PRs:bokeh<3dask#9607bokeh<3distributed#7219gjoseph92 commentedon Oct 28, 2022
@jrbourbeau not critical, but could be good to get dask/distributed#7224 in if CI passes and you have time to review.
jrbourbeau commentedon Oct 28, 2022
Ah, sorry @gjoseph92 I need to start pushing out the release. Unfortunately I think that one will have to get in in the next release
gjoseph92 commentedon Oct 28, 2022
No worries, queuing is still behind a feature flag so it's not too big of a deal.
jrbourbeau commentedon Oct 28, 2022
2022.10.1 is out on PyPI and conda-forge PRs are open:
jrbourbeau commentedon Oct 29, 2022
Alright, PyPI and conda-forge packages are released.
We ran into a problem building the Python 3.8
dask-notebookimage over indask-docker(xref dask/dask-docker#255) due to an issue in the underlyingjupyter/base-notebooknotebook (xref jupyter/docker-stacks#1810). I've attempted a couple of possible fixes, but haven't gotten those build to work yet. I've proposed a temporary workaround in dask/dask-docker#256 where we drop Python 3.8 builds. This is a possible workaround, but admittedly feels a bit heavy handed. I'm on PTO next week -- @jacobtomlinson @jakirkham @charlesbluca could I ask you to handle docker images for this release by either finding an actual fix, or by merging the PR that temporarily drops Python 3.8 builds?jakirkham commentedon Oct 29, 2022
FWIW commented on the upstream (Jupyter) issue.
mrocklin commentedon Oct 31, 2022
mrocklin commentedon Oct 31, 2022
Pushing out a hotfix #284
If there is anything I should know folks should jump in very soon.
ian-r-rose commentedon Oct 31, 2022
There isn't anything I'm aware of that would prevent a hotfix, though dask/distributed#7224 is a non-trivial change. Perhaps @gjoseph92 can comment on whether it's likely to be an issue (I suspect he'd be fine with it)
jrbourbeau commentedon Oct 31, 2022
I think @gjoseph92 is comfortable including that change has he asked for it to be included in the
2022.10.1release, but it just didn't make it in time (xref #283 (comment))EDIT: queuing is also still behind a feature flag, so I think it's safe to move forward with that change included
mrocklin commentedon Oct 31, 2022
I've already chatted with @gjoseph92 and he confirmed.
I've yanked this release from PyPI. Can someone (maybe @jakirkham) help with yanking from conda-forge channels?
charlesbluca commentedon Oct 31, 2022
Any opposition to unblocking the 3.8 Docker builds locally with dask/dask-docker#257 until the upstream issue is resolved? This would involve patching the impacted Jupyter dockerfile, which could get hairy in the long run, but it doesn't seem like CI is running very often on dask-docker for this to be an issue.
jakirkham commentedon Oct 31, 2022
Would follow these steps for marking packages broken in conda-forge. Unfortunately I don't have bandwidth for this atm
charlesbluca commentedon Oct 31, 2022
Thanks @jakirkham! Opened up conda-forge/admin-requests#504 to request the packages be marked as broken
jakirkham commentedon Oct 31, 2022
As to Jupyter docker-stacks, outlined a path forward in comment ( jupyter/docker-stacks#1810 (comment) ). If anyone has bandwidth to try, should be a couple line change
jakirkham commentedon Nov 2, 2022
Updating this thread, Charles' workaround was merged yesterday. Mamba released 1.0.0 early today. This subsequently fixed Jupyter docker-stacks ( jupyter/docker-stacks#1810 (comment) ). With that fixed, Charles reverted the workaround ( dask/dask-docker#260 ).
Edit: Also merged Charles PR yesterday to mark conda-forge packages broken.
jakirkham commentedon Nov 2, 2022
Sounds like there is nothing more to do here. So going to close this out, but please feel free to reopen if I've missed something.
Thanks all! 🙏