comp-dev-cms-ita / dask-labextension

JupyterLab extension for Dask, with multiple factory selection
BSD 3-Clause "New" or "Revised" License
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dask distributed-computing htcondor htcondor-cluster jupyterlab jupyterlab-extension

dask-labextension: af_plugin

This is a fork of Dask JupyterLab Extension to support multiple types of cluster selection as shown in the figures:

Requirements

JupyterLab >= 3.0 distributed >= 1.24.1

Installation

To install the Dask JupyterLab extension you will need to have JupyterLab 3.0 or greater installed.

jlpm
jlpm build
python3 -m pip install . --use-feature=in-tree-build

Configuration of Dask cluster management

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.

You can specify the list of clusters you want to use with the factories field in the labextension.yaml file, as following:

labextension:
  factories:
    # First type of cluster (a custom class from a Python module)
    - name: "HTCondor"
      module: "dask_remote_jobqueue"
      class: "RemoteHtcondor"
      args: []
      kwargs: {}
    # Second type of cluster
    - name: "Local"
      module: "dask.distributed"
      class: "LocalCluster"
      args: []
      kwargs: {}
  # Backup options
  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

Note: if the field factories is not present, the extension will search the factory attribute and there will not be a menu selection but only the factory indicated will be used.

Development install

As described in the JupyterLab documentation for a development install of the labextension you can run the following in this directory:

jlpm  # Install npm package dependencies
jlpm build  # Compile the TypeScript sources to Javascript
jupyter labextension develop . --overwrite  # Install the current directory as an extension

To rebuild the extension:

jlpm build

You should then be able to refresh the JupyterLab page and it will pick up the changes to the extension.

To run an editable install of the server extension, run

pip install -e .
jupyter serverextension enable --sys-prefix dask_labextension