Deprecated Git integration

In an analytics project with deprecated Git integration (Git integration with locking), you can work both with code assets, like notebooks or Python and R scripts, tool-specific assets such as Data Refinery flows, and Decision Optimization models, and data assets like CSV files.

These assets are stored in a Git repository, but in different subdirectories of the repository. Jupyterlab code assets are stored in assets/jupyterlab, RStudio code assets in assets/rstudio and data assets in assets/data_asset. All other directories in the repository are used to store the tool-specific assets along with other metadata for the project.

Assets in the Git repository can be added as project assets. All these assets are listed on the project's Assets page, including the code assets, but the code assets themselves are read-only and can be edited only in the appropriate IDE.

You need to enable Git integration at the time you create a project:

• To work with notebooks or Python scripts in the JupyterLab IDE
• To work with R scripts and Shiny apps in RStudio

• To enable on-demand synchronization between project assets and a Git repository. This enables:

  • Pulling notebook and Python script changes pushed from JupyterLab
  • Pulling R Shiny apps and R scripts pushed from RStudio
  • Exporting assets from the project to enable creating a new project from Git
• To create a project from assets that were exported to a Git repository

Important:

• Each project must have its own Git repository. No two projects can use the same Git repository. This is especially relevant when working in projects with JupyterLab and RStudio. You can't create a project to work with JupyterLab and associate your new project with the Git repository that you used in another project with JupyterLab.
• Git integration in a project is only available to enterprise users with a valid certificate to the platform on which they create the Git repository to associate with the project.

Parent topic: Projects