domino logo
Tech Ecosystem
Get Started
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
Search in Deployments
Security and Credentials
Secure Credential Storage
Store Project CredentialsStore User CredentialsStore Model Credentials
Get API KeyCreate a Mirror of Compute Environments
Collaborate
Share and Collaborate on Projects
Set Project VisibilityInvite CollaboratorsCollaborator Permissions
Add Comments
Reuse Work
Set Up ExportsSet Up Imports
Organizations
Organization PermissionsTransfer Projects to an Organization
Projects
Domino File System Projects
Domino File SystemOrganize Domino File System Project AssetsImport Git RepositoriesWork from a Commit ID in GitFork ProjectsMerge Projects
Manage Project Files
Upload Files to DominoCompare File RevisionsExclude Project Files From SyncExport Files as Python or R Package
Archive a Project
Revert Projects and Files
Revert a FileRevert a Project
Project FilesSet Project SettingsStore Project Credentials
Project Goals
Add GoalsEdit GoalsLink Work to Goals
Organize Projects with TagsSet Project Stages
Project Status
Set Project as BlockedSet Project as CompleteSet Project as Unblocked
View Execution DetailsView Project ActivityTrack Project StatusRename a Project
Share and Collaborate
Set Project VisibilityInvite CollaboratorsCollaborator Permissions
Export and Import Project Content
Set Up ExportsSet Up Imports
See the Assets for Your ProjectPromote Projects to ProductionTransfer Project OwnershipIntegrate Jira
Domino Datasets
Datasets Best PracticesAbout domino.yamlDatasets Advanced Mode TutorialDatasets Scratch SpacesConvert Legacy Datasets to Domino Datasets
External Data
Considerations for Connecting to Data SourcesTips: Transfer Data Over a Network
Workspaces
Reopen a WorkspaceView and Manage Workspace Sessions
Create a Workspace
Open a VS Code WorkspaceSet Custom Preferences for RStudio Workspaces
Workspace Settings
Change Your Workspace's Volume SizeConfigure Long-Running Workspaces
Save Work in a WorkspaceSync ChangesView WorkspacesStop a WorkspaceResume a WorkspaceDelete a WorkspaceView Workspace LogsView Workspace UsageView Workspace HistoryUse Domino Workspaces in SafariRun Multiple Applications in a Workspace
Clusters
Spark on Domino
Hadoop and Spark Overview
Connect 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 Spark Overview
Validated Spark VersionConfigure PrerequisitesWork with your ClusterManage DependenciesWork with Data
Environments
Set a Default EnvironmentCreate an EnvironmentEdit Environment DefinitionView Your EnvironmentsView Environment RevisionsDuplicate an EnvironmentArchive an Environment
Environments
Example: Create a New Environment
Customize Environments
Install Custom Packages with Git Integration
Add Packages to Environments
Use Dockerfile InstructionsUse requirements.txt (Python only)Use the Execution to Add a Package
Add Workspace IDEsScala notebooksAccess Additional Domains and HostnamesUse TensorBoard in Jupyter Workspaces
Use Partner Environments
Use MATLAB as a WorkspaceCreate a SAS Data Science Workspace Environment
Executions
Execution StatesDomino Environment Variables
Jobs
Start a JobScheduled Jobs
Launchers
Launchers OverviewCreate a LauncherRun a LauncherCopy Launcher Definitions
View Job DetailsCompare JobsTag JobsStop JobsView Execution Performance
Execution Notifications
Set Notification PreferencesSet Custom Execution Notifications
Execution Results
Download Execution ResultsCustomize the Results DashboardAutomate Complex Pipelines with Apache Airflow
Model APIs
Configure a Model for Deployment
Scale Models
Scale Model Versions
Configure Compute ResourcesRoute Your ModelProject Files in ModelsEnvironments for ModelsShare and Collaborate on Models
Publish
Model APIs
Publish a ModelSend Test Calls to the ModelPublish a New Version of a ModelSelect How to Authorize a Model
Domino Apps
Publish a Domino AppHost HTML Pages from DominoGrant Access to Domino AppsView a Domino AppView All Domino AppsPublish a Python App with DashPublish an R App with ShinyPublish a Project as a Website with FlaskOptimize App Scalability and PerformanceGet the Domino Username of an App Viewer
Launchers
Create a LauncherRun a LauncherCopy Launcher Definitions
Domino Command Line Interface (CLI)
Install the Domino Command Line Interface (CLI)Domino CLI ReferenceDownload Files with the CLIForce-Restore a Local ProjectMove a Project Between DeploymentsUse the Domino CLI Behind a Proxy
Troubleshooting
Troubleshoot Domino ModelsWork with Many FilesTroubleshoot Imports
Get Help
Additional ResourcesGet Domino VersionContact Technical SupportSupport BundlesBrowser SupportUser Guide Updates
domino logo
About Domino
Domino Data LabKnowledge BaseData Science BlogTraining
User Guide
>
Domino Command Line Interface (CLI)
>
Domino CLI Reference

Domino CLI Reference

Install and get started with the CLI

How to install and get started with the Domino CLI

Run your code

run [--direct][--wait][--no-sync][--tier][--local] <file> [args…​]

"run" will copy all files in your project folder to the cloud, where it will execute the specified file with any arguments you have specified, unless you have specified the --local flag.

The optional --wait flag will run your script synchronously, that is, the command won’t return until your job finishes.

The optional --direct flag lets you run a shell command directly on the Domino machines.

The optional --no-sync flag will run the latest version of code on the server, without uploading any local changes on your computer.

The optional --tier flag lets you select a specific hardware tier to execute the specified file on.

The optional --local flag lets you run your script on your local machine.

The optional --title flag lets you supply a title for the run.

Local runs are useful if your desired compute environment is not immediately available, but you would like to record your results in Domino. When a local run is invoked, Domino commits a snapshot of project files to the server and then runs the given command (for example, python main.py) on the local machine. When the command has completed, Domino detects results that have been produced and commits those back to the server, tracking them as “results” of the run as though the command ran on the server.

Viewing the “Results” for Run #16 will bring up a page showing the output of the main.py where colleagues can view and discuss the output.

Screen Shot 2017 03 07 at 9.49.38 PM

Examples

domino run calculateStats.R domino run runModel.m model1 .05 domino run --wait runModel.m model1 .05 domino run --direct "pip freeze | grep pandas" domino run --tier "Large" calculateStats.R domino run --local "python main.py"

Projects

Create a new project

create [projectName]

create will create a new project by making a new folder on your computer and telling the Domino server about your new project. Optionally, you can specify the name of the project. If you don’t specify a name, Domino will ask you for one. To create a project on behalf of an organization you belong to, use the --owner flag.

Examples

domino create domino create myProject domino create --owner myOrg myProject

Create a project in a directory that already has files

init [projectName]

init will create a new Domino project inside your current folder. This is useful if you already have a working folder and you’d like to convert it to a Domino project. While the "create" command creates a new folder inside your current directory, init will initialize a project from your current folder. The --owner flag can be used to set an organization you belong to as the project owner.

Note
Examples

domino init domino init myProject domino init --owner myOrg myProject

Get a project from the server onto your computer for the first time

get [username]/projectName

get will find an existing project on the server and copy it down to your computer. This is useful to get a project you created on a different computer, or to get a project that someone else created, and you are collaborating on.

If you are getting someone else’s project, specify their username and the project name. If you are getting one of your own projects, you can omit the username.

domino get otherUser/someProject

domino get myProject

Connect a folder to an existing project

restore

restore will connect your current directory to an existing Domino project on the server. Restore will look for evidence of a project name inside .domino/config.json. If it doesn’t find such a file, it will prompt you for the name of an existing project to use.

This is particularly useful if you are using Domino and git to track the same folder. If you clone a project with git, git will likely have ignored the hidden files that identify it has a Domino project. So you can git clone and then domino restore to re-connect the folder to its Domino project.

Examples

domino restore

Files

Synchronize the files on your computer with the server

sync

sync will synchronize the project folder on your computer with the project stored on the server. This is equivalent to running a download followed by an upload.

Examples

domino sync

Download the latest version of your files

download

download will download the latest copy of your files from the cloud into your current project folder. If you have made changes that conflict with changes in the cloud, you will see both versions of the conflicting file side-by-side.

There are two reasons files in the cloud might change: first, your collaborators on a project might make changes; second, you might have executed a run that produced new output files.

Examples

domino download

Upload your files without starting a run

upload [-m "message"]

upload will upload your current project folder contents to the cloud, but will not begin a new run. The optional message flag lets you record a message, which will be displayed when browsing past commits on the Files tab of your project.

Examples

domino upload -m "this is a great message"

Datasets

Upload folder to a Dataset

You can upload all the files in a folder from your local machine to a Dataset. Existing files will be overwritten unless you use the --fileUploadSetting option.

domino upload-dataset <project-owner>/<project-name>/<dataset-name> <folder path>
Example

domino upload-dataset jsmith/global-predictions/global-data /Users/myUser/data

Use the --fileUploadSetting option to handle path collisions as follows:

  1. overwrite: If a file already exists in the Dataset, the new file overwrites the existing file.

  2. rename: If a file already exists in the Dataset, the new file is uploaded and renamed with _1 appended to the filename. For example, /Users/myUser/data/file.txt becomes /Users/myUser/data/file_1.txt,

  3. ignore: If a file already exists in the Dataset, the new file is ignored.

For example:

domino upload-dataset --<fileUploadSetting> <project-owner>/<project-name>/<dataset-name> <folder path>

Create a snapshot

Use the following command to create a snapshot that is visible and populated after the backend finishes copying the files in the dataset.

Note
domino create-snapshot <project-owner>/<project-name>/<dataset-name>

Create a dataset from a snapshot

Use the following command to create a dataset from a snapshot where <snapshot-integer> maps to a valid snapshot number in the dataset.

Note
  domino create-dataset-from-snapshot <project-owner>/<project-name>/<dataset-name> <snapshot-number> <new-dataset-name>

Get help

help

help will print out a list of commands you can run, with information about each one, similar to this page.

Examples

domino help domino help run

Get the version of your CLI

version

version will output your CLI version

Examples

domino --version

Domino Data LabKnowledge BaseData Science BlogTraining
Copyright © 2022 Domino Data Lab. All rights reserved.