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vlt Launches "reproduce": A New Tool Challenging the Limits of Package Provenance
vlt's new "reproduce" tool verifies npm packages against their source code, outperforming traditional provenance adoption in the JavaScript ecosystem.
dask-labextension
Advanced tools
This package provides a JupyterLab extension to manage Dask clusters, as well as embed Dask's dashboard plots directly into JupyterLab panes.
JupyterLab >= 1.0 distributed >= 1.24.1
To install the Dask JupyterLab extension you will need both JupyterLab, and Node.js. These are available through a variety of sources. One source common to Python users is the conda package manager.
conda install jupyterlab nodejs
This extension includes both a client-side JupyterLab extension and a server-side Jupyter notebook extension. Install via pip or conda-forge:
pip install dask_labextension
conda install -c conda-forge dask-labextension
and build the extension as follows:
jupyter labextension install dask-labextension
jupyter serverextension enable dask_labextension
If you are running Notebook 5.2 or earlier, enable the server extension by running
jupyter serverextension enable --py --sys-prefix dask_labextension
This extension has the ability to launch and manage several kinds of Dask clusters,
including local clusters and kubernetes clusters.
Options for how to launch these clusters are set via the
dask configuration system,
typically a .yml
file on disk.
By default the extension launches a LocalCluster
, for which the configuration is:
labextension:
factory:
module: 'dask.distributed'
class: 'LocalCluster'
args: []
kwargs: {}
default:
workers: null
adapt:
null
# minimum: 0
# maximum: 10
initial:
[]
# - name: "My Big Cluster"
# workers: 100
# - name: "Adaptive Cluster"
# adapt:
# minimum: 0
# maximum: 50
In this configuration, factory
gives the module, class name, and arguments needed to create the cluster.
The default
key describes the initial number of workers for the cluster, as well as whether it is adaptive.
The initial
key gives a list of initial clusters to start upon launch of the notebook server.
In addition to LocalCluster
, this extension has been used to launch several other Dask cluster
objects, a few examples of which are:
labextension:
factory:
module: 'dask_jobqueue'
class: 'SLURMCluster'
args: []
kwargs: {}
labextension:
factory:
module: 'dask_jobqueue'
class: 'PBSCluster'
args: []
kwargs: {}
labextension:
factory:
module: dask_kubernetes
class: KubeCluster
args: []
kwargs: {}
As described in the JupyterLab documentation for a development install of the labextension you can run the following in this directory:
jlpm install # Install npm package dependencies
jlpm run build # Compile the TypeScript sources to Javascript
jupyter labextension install # Install the current directory as an extension
To rebuild the extension:
jlpm run build
If you run JupyterLab in watch mode (jupyter lab --watch
) it will automatically pick
up changes to the built extension and rebundle itself.
To run an editable install of the server extension, run
pip install -e .
jupyter serverextension enable --sys-prefix dask_labextension
This application is distributed as two subpackages.
The JupyterLab frontend part is published to npm, and the server-side part to PyPI.
Releases for both packages are done with the jlpm
tool, git
and Travis CI.
Note: Package versions are not prefixed with the letter v
. You will need to disable this.
$ jlpm config set version-tag-prefix ""
Making a release
$ jlpm version [--major|--minor|--patch] # updates package.json and creates git commit and tag
$ git push upstream master && git push upstream master --tags # pushes tags to GitHub which triggers Travis CI to build and deploy
FAQs
A JupyterLab extension for Dask.
The npm package dask-labextension receives a total of 62 weekly downloads. As such, dask-labextension popularity was classified as not popular.
We found that dask-labextension demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 2 open source maintainers collaborating on the project.
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