Metadata-Version: 2.1
Name: dask_labextension
Version: 5.0.0
Summary: A JupyterLab extension for Dask.
Home-page: https://github.com/dask/dask-labextension
Author: Ian Rose, Matt Rocklin, Jacob Tomlinson
License: BSD-3-Clause
Description: # Dask JupyterLab Extension
        
        [![Build Status](https://travis-ci.org/dask/dask-labextension.svg?branch=master)](https://travis-ci.org/dask/dask-labextension) [![Version](https://img.shields.io/npm/v/dask-labextension.svg)](https://www.npmjs.com/package/dask-labextension) [![Downloads](https://img.shields.io/npm/dm/dask-labextension.svg)](https://www.npmjs.com/package/dask-labextension) [![Dependencies](https://img.shields.io/librariesio/release/npm/dask-labextension.svg)](https://libraries.io/npm/dask-labextension)
        
        This package provides a JupyterLab extension to manage Dask clusters,
        as well as embed Dask's dashboard plots directly into JupyterLab panes.
        
        ![Dask Extension](./dask.png)
        
        ## Explanatory Video (5 minutes)
        
        <a href="http://www.youtube.com/watch?feature=player_embedded&v=EX_voquHdk0 "
           target="_blank">
        <img src="http://img.youtube.com/vi/EX_voquHdk0/0.jpg"
               alt="Dask + JupyterLab Screencast" width="560" height="315" border="10" />
        </a>
        
        ## Requirements
        
        JupyterLab >= 1.0
        distributed >= 1.24.1
        
        ## Installation
        
        To install the Dask JupyterLab extension you will need to have JupyterLab installed.
        For JupyterLab < 3.0, you will also need [Node.js](https://nodejs.org/) version >= 12.
        These are available through a variety of sources.
        One source common to Python users is the conda package manager.
        
        ```bash
        conda install jupyterlab
        conda install -c conda-forge nodejs
        ```
        
        ### JupyterLab 3.0 or greater
        
        You should be able to install this extension with pip or conda,
        and start using it immediately, e.g.
        
        ```bash
        pip install dask-labextension
        ```
        
        ### JupyterLab 2.x
        
        This extension includes both client-side and server-side components.
        Prior to JupyterLab 3.0 these needed to be installed separately,
        with node available on the machine.
        
        The server-side component can be installed via pip or conda-forge:
        
        ```bash
        pip install dask_labextension
        ```
        
        ```bash
        conda install -c conda-forge dask-labextension
        ```
        
        You then build the client-side extension into JupyterLab with:
        
        ```bash
        jupyter labextension install dask-labextension
        ```
        
        If you are running Notebook 5.2 or earlier, enable the server extension by running
        
        ```bash
        jupyter serverextension enable --py --sys-prefix dask_labextension
        ```
        
        ## 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](http://docs.dask.org/en/latest/configuration.html#configuration),
        typically a `.yml` file on disk.
        
        By default the extension launches a `LocalCluster`, for which the configuration is:
        
        ```yaml
        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:
        
        - A SLURM cluster, using
        
        ```yaml
        labextension:
            factory:
              module: 'dask_jobqueue'
               class: 'SLURMCluster'
               args: []
               kwargs: {}
        ```
        
        - A PBS cluster, using
        
        ```yaml
        labextension:
          factory:
            module: 'dask_jobqueue'
            class: 'PBSCluster'
            args: []
            kwargs: {}
        ```
        
        - A [Kubernetes cluster](https://github.com/pangeo-data/pangeo-cloud-federation/blob/8f7f4bf9963ef1ed180dd20c952ff1aa8df54ca2/deployments/ocean/image/binder/dask_config.yaml#L37-L42), using
        
        ```yaml
        labextension:
          factory:
            module: dask_kubernetes
            class: KubeCluster
            args: []
            kwargs: {}
        ```
        
        ## Development install
        
        As described in the [JupyterLab documentation](https://jupyterlab.readthedocs.io/en/stable/extension/extension_dev.html#developing-a-prebuilt-extension)
        for a development install of the labextension you can run the following in this directory:
        
        ```bash
        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:
        
        ```bash
        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
        
        ```bash
        pip install -e .
        jupyter serverextension enable --sys-prefix dask_labextension
        ```
        
        ## Publishing
        
        This application is distributed as two subpackages.
        
        The JupyterLab frontend part is published to [npm](https://www.npmjs.com/package/dask-labextension),
        and the server-side part to [PyPI](https://pypi.org/project/dask-labextension/).
        
        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._
        
        ```console
        $ jlpm config set version-tag-prefix ""
        ```
        
        Making a release
        
        ```console
        $ 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
        ```
        
Keywords: dask,Jupyter,JupyterLab,JupyterLab3
Platform: Linux
Platform: Mac OS X
Platform: Windows
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Framework :: Jupyter
Requires-Python: >=3.6
Description-Content-Type: text/markdown
