Jupyter Notebook plus dask-distributed libraries
500K+
Docker images for dask-distributed.
This images are built primarily for the Dask Helm Chart but they should work for more use cases.
A helper docker-compose file is provided to test functionality.
docker-compose up
Open the notebook using the URL that is printed by the output so it has the token.
On a new notebook run:
from dask.distributed import Client
client = Client('scheduler:8786')
client.ncores()
It should output something like this:
{'tcp://172.23.0.4:41269': 4}
The following environment variables are supported for both the base and notebook images:
$EXTRA_APT_PACKAGES - Space separated list of additional system packages to install with apt.$EXTRA_CONDA_PACKAGES - Space separated list of additional packages to install with conda.$EXTRA_PIP_PACKAGES - Space separated list of additional python packages to install with pip.The notebook image supports the following additional environment variables:
$JUPYTERLAB_ARGS - Extra arguments to pass to the jupyter lab command.Docker compose provides an easy way to building all the images with the right context
docker-compose build
# Just build one image e.g. notebook
docker-compose build notebook
Building and releasing new image versions is done automatically via Travis CI. When new commits are
pushed to the main branch images are built with the dev tag and pushed to Docker Hub.
When a new version of Dask is released a PR should be raised to bump the versions in
the Dockerfiles and then once that has been merged a new tag matching the Dask version
should be pushed. Travis will then build the images and push them with version tags and update
latest too.
$ git commit --allow-empty -m "bump version to x.x.x"
$ git tag -a x.x.x -m 'Version x.x.x'
$ git push upstream main --tags
Content type
Image
Digest
sha256:516409645…
Size
367.5 MB
Last updated
21 days ago
docker pull daskdev/dask-notebook