![]() Start a local Jupyter server: run a Jupyter server in a local directory that will be attached to your workspace.Ĭonnect to a running local Jupyter server: establish a connection to any locally run Jupyter server. In the New Jupyter Connection dialog, select the connection type: Connect to a Jupyter serverĬlick the icon on the toolbar of the Workspace tool window to establish a connection to a Jupyter server. You can switch to another environment or create a new one. You can open files that reside in it, or create new files (see how to add new Jupyter notebooks and Python files).ĭataSpell will use the default virtual environment to execute notebooks and scripts in the newly added directory or project. Once you add a directory or a project, it appears in the Workspace tool window. Note that you can also enable Git integration for a selected directory: just right-click it and choose Enable VCS Integration from the context menu. Alternatively, you can select GitHub on the left, login using your credentials, and select any repository you want to work with. Do not select the default DataSpell installation directory as the target local directory. Specify the path to the repository and select the directory to which it will be cloned. Right-click the workspace tree or a directory and select Get from Version Control from the context menu Right-click anywhere in the Workspace tool window and select New | New Top-Level Directory from the context menuįor information about creating a new project, see Create a project. To add a project, select the project directory.įrom the main menu, select File | New Top-Level Directory ![]() Select File | Add Directory or Project from the main menu.Ĭlick in the toolbar of the Workspace tool window.įind the desired directory in your file system. Adding directories and projects to the workspace Add an existing directory or projectĬlick the Attach new of existing directory link in the Workspace tool window. ![]() You can add directories and projects to the workspace, as well as connect to Jupyter servers. On the Welcome screen, you can choose whether you want to work with projects, or open DataSpell workspace. ![]()
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