domino logo
Tech Ecosystem
Get started with Python
Step 0: Orient yourself to DominoStep 1: Create a projectStep 2: Configure your projectStep 3: Start a workspaceStep 4: Get your files and dataStep 5: Develop your modelStep 6: Clean up WorkspacesStep 7: Deploy your model
Get started with R
Step 0: Orient yourself to Domino (R Tutorial)Step 1: Create a projectStep 2: Configure your projectStep 3: Start a workspaceStep 4: Get your files and dataStep 5: Develop your modelStep 6: Clean up WorkspacesStep 7: Deploy your model
Get Started with MATLAB
Step 1: Orient yourself to DominoStep 2: Create a Domino ProjectStep 3: Configure Your Domino ProjectStep 4: Start a MATLAB WorkspaceStep 5: Fetch and Save Your DataStep 6: Develop Your ModelStep 7: Clean Up Your Workspace
Step 8: Deploy Your Model
Scheduled JobsLaunchers
Step 9: Working with Domino Datasets
Domino Reference
Projects
Projects Overview
Revert Projects and Files
Revert a ProjectRevert a File
Projects PortfolioProject Goals in Domino 4+Jira Integration in DominoUpload Files to Domino using your BrowserCopy ProjectsFork and Merge ProjectsSearchSharing and CollaborationCommentsDomino Service FilesystemCompare File RevisionsArchive a Project
Advanced Project Settings
Project DependenciesProject TagsRename a ProjectSet up your Project to Ignore FilesUpload files larger than 550MBExporting Files as a Python or R PackageTransfer Project Ownership
Domino Runs
JobsDiagnostic Statistics with dominostats.jsonNotificationsResultsRun Comparison
Advanced Options for Domino Runs
Run StatesDomino Environment VariablesEnvironment Variables for Secure Credential StorageUse Apache Airflow with Domino
Scheduled Jobs
Domino Workspaces
WorkspacesUse Git in Your WorkspaceUse Visual Studio Code in Domino WorkspacesPersist RStudio PreferencesAccess Multiple Hosted Applications in one Workspace Session
Spark on Domino
On-Demand Spark
On-Demand Spark OverviewValidated Spark VersionConfigure PrerequisitesWork with your ClusterManage DependenciesWork with Data
External Hadoop and Spark
Hadoop and Spark OverviewConnect to a Cloudera CDH5 cluster from DominoConnect to a Hortonworks cluster from DominoConnect to a MapR cluster from DominoConnect to an Amazon EMR cluster from DominoRun Local Spark on a Domino ExecutorUse PySpark in Jupyter WorkspacesKerberos Authentication
On-Demand Ray
On-Demand Ray OverviewValidated Ray VersionConfigure PrerequisitesWork with your ClusterManage DependenciesWork with Data
Customize the Domino Software Environment
Environment ManagementDomino Standard EnvironmentsInstall Packages and DependenciesAdd Workspace IDEs
Partner Environments for Domino
Use MATLAB as a WorkspaceCreate a SAS Data Science Workspace EnvironmentNVIDIA NGC Containers
Advanced Options for Domino Software Environment
Install Custom Packages in Domino with Git IntegrationAdd Custom DNS Servers to Your Domino EnvironmentConfigure a Compute Environment to User Private Cran/Conda/PyPi MirrorsScala notebooksUse TensorBoard in Jupyter Workspaces
Publish your Work
Publish a Model API
Model Publishing OverviewModel Invocation SettingsModel Access and CollaborationModel Deployment ConfigurationPromote Projects to ProductionExport Model Image
Publish a Web Application
App Publishing OverviewGet Started with DashGet Started with ShinyGet Started with FlaskContent Security Policies for Web Apps
Advanced Web Application Settings in Domino
App Scaling and PerformanceHost HTML Pages from DominoHow to Get the Domino Username of an App Viewer
Launchers
Launchers OverviewAdvanced Launcher Editor
Assets Portfolio Overview
Connect to your Data
Data in Domino
Datasets OverviewDatasets Best Practices
Data Sources Overview
Connect to Data Sources
External Data Volumes
Git and Domino
Git Repositories in DominoWork From a Commit ID in Git
Work with Data Best Practices
Work with Big Data in DominoWork with Lots of FilesMove Data Over a Network
Advanced User Configuration Settings
User API KeysDomino TokenOrganizations Overview
Use the Domino Command Line Interface (CLI)
Install the Domino Command Line (CLI)Domino CLI ReferenceDownload Files with the CLIForce-Restore a Local ProjectMove a Project Between Domino DeploymentsUse the Domino CLI Behind a Proxy
Browser Support
Get Help with Domino
Additional ResourcesGet Domino VersionContact Domino Technical SupportSupport Bundles
domino logo
About Domino
Domino Data LabKnowledge BaseData Science BlogTraining
User Guide
>
Domino Reference
>
Domino Workspaces
>
Persist RStudio Preferences

Persist RStudio Preferences

In the context of your runs, the RStudio user preferences (such as theme) are stored in a file located at /home/ubuntu/.rstudio/monitored/user-settings/user-settings. You can launch RStudio with custom preferences by modifying this file through the pre-setup script of a custom compute environment.

Method 1: Write lines to settings file

If you know the line you must add to the settings file, you can write it directly in the pre-setup script. For example:

mkdir -p /home/ubuntu/.rstudio/monitored/user-settings/
echo 'uiPrefs={"theme" : "Mono Industrial"}' >> /home/ubuntu/.rstudio/monitored/user-settings/user-settings
chown -R ubuntu:ubuntu /home/ubuntu/.rstudio
if [ -f .domino/launch-rstudio-server ]; then
    sed -i.bak 's# > ~/.rstudio/monitored/user-settings/user-settings# >> ~/.rstudio/monitored/user-settings/user-settings#' .domino/launch-rstudio-server
    chown ubuntu:ubuntu .domino/launch-rstudio-server
fi

The following describes what each line is doing:

  • The mkdir statement creates the encompassing directory.

  • The echo statement writes the theme to the file. This can be replaced with a copy operation if you’d prefer to store a file in your project (see next section).

  • The chown statements are needed to avoid a permissions error.

  • The sed statement modifies a Domino script that would otherwise overwrite this settings file.

Method 2: Copy a saved settings file

If you aren’t sure which lines to write, or if you want to persist this settings file in your project, you can save a copy in your project and use the following pre-setup script code to apply it to your session.

First, run a session and modify the RStudio preferences to your liking. Before you stop the session, copy the user-settings file to the root of your project directory. You can do so with this line of R code:

file.copy("/home/ubuntu/.rstudio/monitored/user-settings/user-settings", ".")

Then, add the following lines to the pre-setup script of your environment definition, in order to load the preferences file (if it exists) on subsequent runs:

if [ -f user-settings ]; then
    mkdir -p /home/ubuntu/.rstudio/monitored/user-settings/
    cp user-settings /home/ubuntu/.rstudio/monitored/user-settings
    sed -i.bak '/initialWorkingDirectory=/d' /home/ubuntu/.rstudio/monitored/user-settings/user-settings
    chown -R ubuntu:ubuntu /home/ubuntu/.rstudio
    if [ -f .domino/launch-rstudio-server ]; then
        sed -i.bak 's# > ~/.rstudio/monitored/user-settings/user-settings# >> ~/.rstudio/monitored/user-settings/user-settings#' .domino/launch-rstudio-server
        chown ubuntu:ubuntu .domino/launch-rstudio-server
    fi
fi
Note
Domino Data LabKnowledge BaseData Science BlogTraining
Copyright © 2022 Domino Data Lab. All rights reserved.