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Workspace

Workspace

A workspace is a dedicated environment where you can develop, test, and deploy your data workflows and applications. Workspaces provide isolated resources, allowing you to manage dependencies and configurations specific to your projects.

A default workspace is created for you when you sign up for Datatailr. You can also create additional workspaces as needed.

A workspace is based on an environment definition that specifies the software dependencies and compute resources required for your development process. You can create, manage and open workspaces on the workspaces page of the Datatailr dashboard. Open it from the left sidebar by clicking the Workspaces icon.

Workspaces in sidebar Workspaces in sidebar

The list of available workspaces will be displayed. To launch a workspace, hover over the "Connect" button and select one of the available options: "JupyterLab" or "VS Code":

Workspaces list Workspaces list

It is best to start with VS Code, as it provides a full-featured IDE experience and allows you to quickly initialize new Datatailr projects using the integrated terminal.

The first thing you'll see when you open a workspace is a README file with instructions on how to initialize a new demo project and deploy it to the Datatailr platform. See the Quick Start guide to get up and running.

Creating a New Workspace

Using the 'Add New' button on the workspaces page, you can create additional workspaces as needed. The workspace creation dialog allows you to specify the following parameters:

  • Name: A unique name for your workspace.
  • Memory: The amount of memory allocated to the workspace. The default is 1 GB.
  • CPU Cores: The number of CPU cores allocated to the workspace. The default is 1 core.
  • Python Version: The version of Python to be used in the workspace. The default is Python 3.12.
  • Python Requirements: A list of Python packages to be installed in the workspace. You can specify package names and versions in the standard pip format (e.g., pandas==1.5.3).
  • Pre-install shell commands: A list of shell commands to be executed during the workspace setup. This is useful for installing system-level dependencies or performing custom configurations.
  • Post-install shell commands: A list of shell commands to be executed after the Python packages have been installed. This can be used for additional setup tasks or configurations.
  • Permissions: Specify the access level for the workspace. You can read more about the permissions model in the Permissions section.

Create Workspace Create Workspace