.. _configuration: .. py:currentmodule:: dask_casa How to Configure Dask Labextension Cluster =========================================== The Dask JupyterLab extension package provides a JupyterLab extension to manage Dask clusters, as well as to embed Dask's dashboard plots directly into JupyterLab panes. The ``~/.config/dask/jobqueue-coffea-casa.yaml`` or ``/etc/dask/jobqueue-coffea-casa.yaml`` files are usually the default configuration files used for :class:`CoffeaCasaCluster`: Example of a file: .. code-block:: yaml jobqueue: coffea-casa: # Dask worker options, taken from https://github.com/dask/dask-jobqueue/tree/master/dask_jobqueue cores: 4 # Total number of cores per job memory: "6 GiB" # Total amount of memory per job processes: null # Number of Python processes per jobs worker-image: "coffeateam/coffea-casa-analysis:0.xx.xx" # Comunication settings interface: null # Network interface to use like eth0 or ib0 death-timeout: 60 # Number of seconds to wait if a worker can not find a scheduler local-directory: null # Location of fast local storage like /scratch or $TMPDIR extra: [] # HTCondor Resource Manager options disk: "5 GiB" # Amount of disk per worker job env-extra: [] job-extra: {} # Extra submit attributes log-directory: null shebang: "#!/usr/bin/env condor_submit -spool" # Scheduler options scheduler-options: {} name: dask-worker To configure a cluster that is launched using it, you should adjust the Dask configuration file, typically stored at ``~/.config/dask/labextension.yaml`` or ``/etc/dask/labextension.yaml``. .. code-block:: yaml labextension: factory: module: 'coffea_casa' class: 'CoffeaCasaCluster' args: [] kwargs: {} default: workers: 1 adapt: minimum: 5 maximum: 10 Users can edit `kwargs: {}` to change a :class:`CoffeaCasaCluster` constructor directly (see more details in :doc:`cc_setup`). To get an address of scheduler that will be used during client connection, try right-clicking on the cluster in the sidebar: .. image:: _static/dask-labextention-address.png :alt: Dask Labextention powered cluster, with right-click menu :width: 65% :align: center And then pressing *Inject Dask Client Connection Code*, as is shown in example below: .. code-block:: python from dask.distributed import Client client = Client("tls://oksana-2eshadura-40cern-2ech.dask.coffea.casa:8786") client or, more simply: .. code-block:: python from dask.distributed import Client client = Client("tls://localhost:8786") client