Running Older Versions of DXJupyterLab

Learn how to run an older version of DXJupyterLab via the user interface or command-line interface.

Why Run an Older Version of DXJupyterLab?

The primary reason to run an older version of DXJupyterLab is to access snapshots containing tools that cannot be run in the current version's execution environment.

Launching an Older Version via the User Interface (UI)

  1. From the main Platform menu, select Tools, then Tools Library.

  2. Locate and select, from the list of tools, either DXJupyterLab with Python, R, Stata, ML, Image Processing or DXJupyterLab with Spark Cluster.

  3. From the tool detail page, click on the Versions tab.

  4. Select the version you'd like to run. Click the Run button.

Launching an Older Version via the Command-Line Interface (CLI)

  1. Select the project in which you want to run DXJupyterLab.

  2. Launch the version of DXJupyterLab you want to run, substituting the version number for x.y.z in the following commands:

    • For DXJupyterLab without Spark cluster capability, run the command dx run app-dxjupyterlab/x.y.z --priority high.

    • For DXJupyterLab with Spark cluster capability, run the command dx run app-dxjupyterlab_spark_cluster/x.y.z --priority high

Note that running DXJupyterLab at "high" priority is not required. But doing so will ensure that your interactive session is not interrupted by spot instance termination.

Accessing DXJupyterLab

After launching DXJupyterLab, access the DXJupyterLab environment using your browser. To do this:

  1. Get the job ID for the job created when you launched DXJupyterLab. See the Monitoring Executions page for details on how to get the job ID, via either the UI or the CLI.

  2. Open the URL, substituting the job's ID for job-xxxx.

  3. You will see an error message "502 Bad Gateway" if DXJupyterLab is not yet accessible. If this happens, wait a few minutes, then try again.

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