Importing a project (Watson Studio)

Importing a project (Watson Studio)

You can create a project that is preloaded with assets by importing the project.

Use one of these methods:

  • Import from a local file

    If you created a project from file, you can create it from an project ZIP file on your local system. The compressed file that you select must be an exported ZIP file of a Cloud Pak for Data project and must be from the same Cloud Pak for Data version you are currently using or from earlier versions. You cannot import a compressed file that was exported from a project in Cloud Pak for Data as a Service.

    If the exported file that you select to import was encrypted, you must enter the password that was used for encryption to enable decrypting sensitive connection properties. If you enter an incorrect password, the project file imports successfully, but sensitive connection properties are falsely decrypted.

    Note that if the imported project contains notebooks, you can only work with those notebooks in the notebook editor, even if the notebooks were created in JupyterLab. You cannot use the JupyterLab IDE in the project.

    You can download sample projects from Industry accelerators that contain a set of data science assets to accomplish a specific goal.

  • Import from a Git repository

    If you created a project with deprecated Git integration, you can create a project that is preloaded with files from a Git repository. The assets in the repository must be assets that were exported (synched) to the Git repository from a project in IBM Cloud Pak for Data.

    You can:

    • Continue using the Git repository after project creation for project synchronization
    • Use the repository only to import assets.

      See Deprecated Git integration.

      Note that if the imported project contains notebooks, you can only work with those notebooks in the notebook editor, even if the notebooks were created in JupyterLab. You cannot use the JupyterLab IDE in the project.

      You might have to change the environment template associated with notebooks originally created in JupyterLab before you can open them in the notebook editor. See Kernel not found when opening a notebook imported from a Git repository.

      If you notice that notebooks or Python scripts are missing in the project import, they might not have been included in the original project export. Verify that the person who synchronized assets between the repository and your project explicitly selected those assets, and added them to the project export.

Watch the following video see how to create a project from a zipped file and from a GitHub repository.

This video provides a visual method as an alternative to following the written steps in this documentation.

Important: After the project import is completed, you should always view the project import summary to check that all the assets were successfully imported.

The status of a project import is also tracked on the project's Overview page. Check for a readme file on the Assets page of the project for information about the analytics use case of the added assets and the applied data analysis methods. Imported notebook jobs will always run on the latest available version of the notebook.

Before you begin working with the imported assets in your new project, you should check for missing credentials, for example in notebooks and data connections, to enable successful relinking between project assets.

Parent topic: Creating a project