Notebooks¶

class datarobot.models.notebooks.enums.NotebookType¶

Types of notebooks.

class datarobot.models.notebooks.enums.RunType¶

Types of notebook job runs.

class datarobot.models.notebooks.enums.ManualRunType¶

A subset of RunType To be used in API schemas.

class datarobot.models.notebooks.enums.SessionType¶

Types of notebook sessions. Triggered sessions include notebook job runs whether manually triggered or scheduled.

class datarobot.models.notebooks.enums.ScheduleStatus¶

Possible statuses for notebook schedules.

class datarobot.models.notebooks.enums.ScheduledRunStatus¶

Possible statuses for scheduled notebook runs.

class datarobot.models.notebooks.enums.NotebookPermissions¶

Permissions for notebooks.

class datarobot.models.notebooks.enums.NotebookStatus¶

Possible statuses for notebook sessions.

class datarobot.models.notebooks.enums.KernelExecutionStatus¶

Possible statuses for kernel execution.

class datarobot.models.notebooks.enums.CellType¶

Types of cells in a notebook.

class datarobot.models.notebooks.enums.RuntimeLanguage¶

Languages as used in notebook jupyter kernels.

class datarobot.models.notebooks.enums.ImageLanguage¶

Languages as used and supported in notebook images.

class datarobot.models.notebooks.enums.KernelSpec¶

Kernel specifications for Jupyter notebook kernels.

class datarobot.models.notebooks.enums.KernelState¶

Possible states for notebook kernels.

exception datarobot.models.notebooks.exceptions.KernelNotAssignedError¶

Raised when a Codespace notebook does not have a kernel assigned.

class datarobot.models.notebooks.notebook.ManualRunPayload¶

class datarobot.models.notebooks.notebook.Notebook¶

Metadata for a DataRobot Notebook accessible to the user.

• Variables:
  • id (str) – The ID of the Notebook.
  • name (str) – The name of the Notebook.
  • type (NotebookType) – The type of the Notebook. Can be “plain” or “codespace”.
  • permissions (List[NotebookPermissions]) – The permissions the user has for the Notebook.
  • tags (List[str]) – Any tags that have been added to the Notebook. Default is an empty list.
  • created (NotebookActivity) – Information on when the Notebook was created and who created it.
  • updated (NotebookActivity) – Information on when the Notebook was updated and who updated it.
  • last_viewed (NotebookActivity) – Information on when the Notebook was last viewed and who viewed it.
  • settings (NotebookSettings) – Information on global settings applied to the Notebook.
  • org_id (Optional[str]) – The organization ID associated with the Notebook.
  • tenant_id (Optional[str]) – The tenant ID associated with the Notebook.
  • description (Optional[str]) – The description of the Notebook. Optional.
  • session (Optional[NotebookSession]) – Metadata on the current status of the Notebook and its kernel. Optional.
  • use_case_id (Optional[str]) – The ID of the Use Case the Notebook is associated with. Optional.
  • use_case_name (Optional[str]) – The name of the Use Case the Notebook is associated with. Optional.
  • has_schedule (bool) – Whether or not the notebook has a schedule.
  • has_enabled_schedule (bool) – Whether or not the notebook has a currently enabled schedule.

get_uri()¶

• Returns: url – Permanent static hyperlink to this Notebook in its Use Case or standalone.
• Return type: str

classmethod get(notebook_id)¶

Retrieve a single notebook.

• Parameters: notebook_id (str) – The ID of the notebook you want to retrieve.
• Returns: notebook – The requested notebook.
• Return type: Notebook

from datarobot.models.notebooks import Notebook

notebook = Notebook.get(notebook_id='6556b00dcc4ea0bb7ea48121')

create_revision(name=None, notebook_path=None, is_auto=False)¶

Create a new revision for the notebook.

• Parameters:
  • name (Optional[str]) – The name of the revision. Optional.
  • notebook_path (Optional[str]) – The path of the notebook to execute within the codespace. Required if notebook is in a codespace.
  • is_auto (bool) – Indicates whether the revision was auto-saved versus a user interaction. Default is False.
• Returns: notebook_revision – Information about the created notebook revision.
• Return type: NotebookRevision

download_revision(revision_id, file_path=None, filelike=None)¶

Downloads the notebook as a JSON (.ipynb) file for the specified revision.

• Parameters:
  • file_path (string, optional) – The destination to write the file to.
  • filelike (file, optional) – A file-like object to write to. The object must be able to write bytes. The user is responsible for closing the object.
• Return type: None

from datarobot.models.notebooks import Notebook

notebook = Notebook.get(notebook_id='6556b00dcc4ea0bb7ea48121')
manual_run = notebook.run_as_job()
revision_id = manual_run.wait_for_completion()
notebook.download_revision(revision_id=revision_id, file_path="./results.ipynb")

delete()¶

Delete a single notebook :rtype: None

from datarobot.models.notebooks import Notebook

notebook = Notebook.get(notebook_id='6556b00dcc4ea0bb7ea48121')
notebook.delete()

classmethod list(created_before=None, created_after=None, order_by=None, tags=None, owners=None, query=None, use_cases=None)¶

List all Notebooks available to the user.

• Parameters:
  • created_before (Optional[str]) – List Notebooks created before a certain date. Optional.
  • created_after (Optional[str]) – List Notebooks created after a certain date. Optional.
  • order_by (Optional[str]) – Property to sort returned Notebooks. Optional. Supported properties are “name”, “created”, “updated”, “tags”, and “lastViewed”. Prefix the attribute name with a dash to sort in descending order, e.g. order_by=’-created’. By default, the order_by parameter is None.
  • tags (Optional[List[str]]) – A list of tags that returned Notebooks should be associated with. Optional.
  • owners (Optional[List[str]]) – A list of user IDs used to filter returned Notebooks. The respective users share ownership of the Notebooks. Optional.
  • query (Optional[str]) – A specific regex query to use when filtering Notebooks. Optional.
  • use_cases (Optional[UseCase or List[UseCase] or str or List[str]]) – Filters returned Notebooks by a specific Use Case or Cases. Accepts either the entity or the ID. Optional. If set to [None], the method filters the notebook’s datasets by those not linked to a UseCase.
• Returns: notebooks – A list of Notebooks available to the user.
• Return type: List[Notebook]

from datarobot.models.notebooks import Notebook

notebooks = Notebook.list()

is_running()¶

Check if the notebook session is currently running.

• Return type: bool

get_session_status()¶

Get the status of the notebook session.

• Return type: NotebookStatus

start_session(is_triggered_run=False, parameters=None, open_file_paths=None, clone_repository=None)¶

Start a new session for the notebook.

• Parameters:
  • is_triggered_run (bool) – Whether the session being started is considered an “interactive” or “triggered” session. Default is False.
  • parameters (Optional[List[StartSessionParameters]]) – A list of dictionaries in the format {“name”: “FOO”, “value”: “my_value”} representing environment variables propagated to the notebook session.
  • open_file_paths (Optional[List[str]]) – A list of file paths to open upon instantiation of the notebook session.
  • clone_repository (Optional[CloneRepositorySchema]) – Information used to clone a remote repository as part of the environment setup flow.
• Returns: notebook_session – The created notebook session.
• Return type: NotebookSession

from datarobot.models.notebooks import Notebook

notebook = Notebook.get(notebook_id='6556b00dcc4ea0bb7ea48121')
session = notebook.start_session()

stop_session()¶

Stop the current session for the notebook.

• Returns: notebook_session – The stopped notebook session.
• Return type: NotebookSession

from datarobot.models.notebooks import Notebook

notebook = Notebook.get(notebook_id='6556b00dcc4ea0bb7ea48121')
session = notebook.stop_session()

execute(notebook_path=None, cell_ids=None)¶

Execute the notebook. Assumes session is already started.

• Parameters:
  • notebook_path (Optional[str]) – The path of the notebook to execute within the Codespace. Required if the notebook is in a Codespace.
  • cell_ids (Optional[List[str]]) – The list of cell IDs to execute for a notebook. Not supported if the notebook is in a Codespace. Optional. If not provided, the whole notebook will be executed.
• Return type: None

get_execution_status()¶

Get the execution status information of the notebook.

• Returns: execution_status – The notebook execution status information.
• Return type: NotebookExecutionStatus

is_finished_executing(notebook_path=None)¶

Check if the notebook is finished executing.

• Parameters: notebook_path (Optional[str]) – The path of the notebook the Codespace. Required only if the notebook is in a Codespace. Will raise an error if working with a standalone notebook.
• Returns: is_finished_executing – Whether or not the notebook has finished executing.
• Return type: bool
• Raises:
  • InvalidUsageError – If attempting to check if a standalone notebook has finished executing and incorrectly passing a notebook path. If attempting to check if a codespace notebook has finished executing without passing a notebook path.
  • KernelNotAssignedError – If attempting to check if a codespace notebook has finished executing but the notebook does not have a kernel assigned.

run_as_job(title=None, notebook_path=None, parameters=None, manual_run_type=ManualRunType.MANUAL)¶

Create a manual scheduled job that runs the notebook.

• Parameters:
  • title (Optional[str]) – The title of the background job. Optional.
  • notebook_path (Optional[str]) – The path of the notebook to execute within the Codespace. Required if notebook is in a Codespace.
  • parameters (Optional[List[StartSessionParameters]]) – A list of dictionaries in the format {“name”: “FOO”, “value”: “my_value”} representing environment variables predefined in the notebook session. Optional.
  • manual_run_type (Optional[ManualRunType]) – The type of manual run being triggered. Defaults to “manual” as opposed to “pipeline”.
• Returns: notebook_scheduled_job – The created notebook schedule job.
• Return type: NotebookScheduledJob
• Raises: InvalidUsageError – If attempting to create a manual scheduled run for a Codespace without a notebook path.

from datarobot.models.notebooks import Notebook

notebook = Notebook.get(notebook_id='6556b00dcc4ea0bb7ea48121')
manual_run = notebook.run_as_job()

# Alternatively, with title and parameters:
# manual_run = notebook.run_as_job(title="My Run", parameters=[{"name": "FOO", "value": "bar"}])

revision_id = manual_run.wait_for_completion()

list_schedules(enabled_only=False)¶

List all NotebookScheduledJobs associated with the notebook.

• Parameters: enabled_only (bool) – Whether or not to return only enabled schedules.
• Returns: notebook_schedules – A list of schedules for the notebook.
• Return type: List[NotebookScheduledJob]
• Raises: InvalidUsageError – If attempting to list schedules for a notebook not associated with a Use Case.

from datarobot.models.notebooks import Notebook

notebook = Notebook.get(notebook_id='6556b00dcc4ea0bb7ea48121')
enabled_schedules = notebook.list_schedules(enabled_only=True)

class datarobot.models.notebooks.execution_environment.ExecutionEnvironmentAssignPayload¶

Payload for assigning an execution environment to a notebook.

class datarobot.models.notebooks.execution_environment.Image¶

Execution environment image information.

• Variables:
  • id (str) – The ID of the image.
  • name (str) – The name of the image.
  • default (bool) – Whether the image is the default image.
  • description (str) – The description of the image.
  • environment_id (str) – The ID of the environment.
  • gpu_optimized (bool) – Whether the image is GPU optimized.
  • language (ImageLanguage) – The runtime language of the image. For example “Python” or “R”
  • language_version (str) – The version of the language. For example “3.11” or “4.3”
  • libraries (list[str]) – A list of pre-installed libraries on the image.

class datarobot.models.notebooks.execution_environment.Machine¶

Execution environment machine information.

• Variables:
  • id (str) – The ID of the machine.
  • name (str) – The name of the machine. Values include “XS”, “S”, “M”, “L” etc.
  • default (bool) – Whether the machine is the default machine.
  • cpu (str) – The CPU of the machine. For example a value like “2000m”.
  • cpu_cores (int) – The number of CPU cores.
  • ephemeral_storage (str) – The ephemeral storage of the machine. For example a value like “15Gi”.
  • has_gpu (bool) – Whether the machine has a GPU.
  • memory (str) – The memory of the machine. For example a value like “8Gi”.
  • ram_gb (int) – The amount of RAM of the machine.

class datarobot.models.notebooks.execution_environment.ExecutionEnvironment¶

An execution environment associated with a notebook.

• Variables:
  • image (Image) – The image associated with the execution environment.
  • machine (Machine) – The machine associated with the execution environment.
  • time_to_live (int) – The inactivity timeout for notebook session.

classmethod get(notebook_id)¶

Get a notebook execution environment by its notebook ID.

• Parameters: notebook_id (str) – The ID of the notebook.
• Returns: The notebook execution environment.
• Return type: ExecutionEnvironment

classmethod assign_environment(notebook_id, payload)¶

Assign execution environment values to a notebook.

• Parameters:
  • notebook_id (str) – The ID of the notebook.
  • payload (ExecutionEnvironmentAssignPayload) – The payload for the assignment/update.
• Returns: The assigned execution environment.
• Return type: ExecutionEnvironment

from datarobot.models.notebooks import ExecutionEnvironment, ExecutionEnvironmentAssignPayload

payload = ExecutionEnvironmentAssignPayload(machine_slug='medium', time_to_live=10)
exec_env = ExecutionEnvironment.assign_environment('67914bfab0279fd832dc3fd1', payload)

class datarobot.models.notebooks.kernel.NotebookKernel¶

A kernel associated with a codespace notebook.

• Variables:
  • id (str) – The kernel ID.
  • name (str) – The kernel name.
  • language (RuntimeLanguage) – The kernel language. Supports Python and R.
  • running (bool) – Whether the kernel is running.
  • execution_state (KernelState) – The kernel execution state.

class datarobot.models.notebooks.revision.CreateRevisionPayload¶

Payload for creating a notebook revision.

class datarobot.models.notebooks.revision.NotebookRevision¶

Represents a notebook revision.

• Variables:
  • revision_id (str) – The ID of the notebook revision.
  • notebook_id (str) – The ID of the notebook.
  • is_auto (bool) – Whether the revision was auto-saved.

classmethod create(notebook_id, payload=None)¶

Create a new notebook revision.

• Parameters:
  • notebook_id (str) – The ID of the notebook.
  • payload (CreateRevisionPayload) – The payload to create the revision.
• Returns: Information about the created notebook revision.
• Return type: NotebookRevision

class datarobot.models.notebooks.scheduled_job.NotebookScheduledJob¶

DataRobot Notebook Schedule. A scheduled job that runs a notebook.

• Variables:
  • id (str) – The ID of the scheduled notebook job.
  • enabled (bool) – Whether job is enabled or not.
  • run_type (RunType) – The type of the run - either manual (triggered via UI or API) or scheduled.
  • notebook_type (NotebookType) – The type of the notebook - either plain or codespace.
  • job_payload (ScheduledJobPayload) – The payload used for the background job.
  • next_run_time (Optional[str]) – The next time the job is scheduled to run (assuming it is enabled).
  • title (Optional[str]) – The title of the job. Optional.
  • schedule (Optional[str]) – Cron-like string to define how frequently job should be run. Optional.
  • schedule_localized (Optional[str]) – A human-readable localized version of the schedule. Example in English is ‘At 42 minutes past the hour’. Optional.
  • last_successful_run (Optional[str]) – The last time the job was run successfully. Optional.
  • last_failed_run (Optional[str]) – The last time the job failed. Optional.
  • last_run_time (Optional[str]) – The last time the job was run (failed or successful). Optional.

classmethod get(use_case_id, scheduled_job_id)¶

Retrieve a single notebook schedule.

• Parameters: scheduled_job_id (str) – The ID of the notebook schedule you want to retrieve.
• Returns: notebook_schedule – The requested notebook schedule.
• Return type: NotebookScheduledJob

from datarobot.models.notebooks import NotebookScheduledJob

notebook_schedule = NotebookScheduledJob.get(
    use_case_id="654ad653c6c1e889e8eab12e",
    scheduled_job_id="65734fe637157200e28bf688",
)

classmethod list(notebook_ids=None, statuses=None)¶

List all NotebookScheduledJobs available to the user.

• Parameters:
  • notebook_ids (Optional[List[str]]) – Notebook IDs to filter listed schedules by. Optional.
  • statuses (Optional[List[ScheduleStatus]]) – Statuses to filter listed schedules by. Includes values “disabled” and “enabled”. Optional.
• Returns: notebook_schedules – A list of NotebookScheduledJobs available to the user.
• Return type: List[NotebookScheduledJob]

cancel()¶

Cancel a running notebook schedule.

• Return type: None

get_most_recent_run()¶

Retrieve the most recent run for the notebook schedule.

• Returns: notebook_scheduled_run – The most recent run for the notebook schedule, or None if no runs have been made.
• Return type: Optional[NotebookScheduledRun]

from datarobot.models.notebooks import NotebookScheduledJob

notebook_schedule = NotebookScheduledJob.get(
    use_case_id="654ad653c6c1e889e8eab12e",
    scheduled_job_id="65734fe637157200e28bf688",
)
most_recent_run = notebook_schedule.get_most_recent_run()

get_job_history()¶

Retrieve list of historical runs for the notebook schedule. Gets the most recent runs first.

• Returns: notebook_scheduled_runs – The list of historical runs for the notebook schedule.
• Return type: List[NotebookScheduledRun]

from datarobot.models.notebooks import NotebookScheduledJob

notebook_schedule = NotebookScheduledJob.get(
    use_case_id="654ad653c6c1e889e8eab12e",
    scheduled_job_id="65734fe637157200e28bf688",
)
notebook_scheduled_runs = notebook_schedule.get_job_history()

wait_for_completion(max_wait=600)¶

Wait for the completion of a scheduled notebook and return the revision ID corresponding to the run’s output.

• Parameters: max_wait (int) – The number of seconds to wait before giving up.
• Returns: revision_id – Returns either revision ID or message describing current state.
• Return type: str

from datarobot.models.notebooks.notebook import Notebook

notebook = Notebook.get(notebook_id='6556b00dcc4ea0bb7ea48121')
manual_run = notebook.run_as_job()
revision_id = manual_run.wait_for_completion()

class datarobot.models.notebooks.scheduled_run.ScheduledJobParam¶

DataRobot Schedule Job Parameter.

• Variables:
  • name (str) – The name of the parameter.
  • value (str) – The value of the parameter.

class datarobot.models.notebooks.scheduled_run.ScheduledJobPayload¶

DataRobot Schedule Job Payload.

• Variables:
  • uid (str) – The ID of the user who created the notebook schedule.
  • org_id (str) – The ID of the user’s organization who created the notebook schedule.
  • use_case_id (str) – The ID of the Use Case that the notebook belongs to.
  • notebook_id (str) – The ID of the notebook being run on a schedule.
  • notebook_name (str) – The name of the notebook being run on a schedule.
  • run_type (RunType) – The type of the run - either manual (triggered via UI or API) or scheduled.
  • notebook_type (NotebookType) – The type of the notebook - either plain or codespace.
  • parameters (List[ScheduledJobParam]) – The parameters being used in the notebook schedule. Can be an empty list.
  • notebook_path (Optional[str]) – The path of the notebook to execute within the codespace. Optional. Required if notebook is in a codespace.
  • use_case_name (Optional[str]) – The name of the Use Case that the notebook belongs to.

class datarobot.models.notebooks.scheduled_run.ScheduledRunRevisionMetadata¶

DataRobot Notebook Revision Metadata specifically for a scheduled run.

Both id and name can be null if for example the job is still running or has failed.

• Variables:
  • id (Optional[str]) – The ID of the Notebook Revision. Optional.
  • name (Optional[str]) – The name of the Notebook Revision. Optional.

class datarobot.models.notebooks.scheduled_run.NotebookScheduledRun¶

DataRobot Notebook Scheduled Run. A historical run of a notebook schedule.

• Variables:
  • id (str) – The ID of the scheduled notebook job.
  • use_case_id (str) – The Use Case ID of the scheduled notebook job.
  • status (str) – The status of the run.
  • payload (ScheduledJobPayload) – The payload used for the background job.
  • title (Optional[str]) – The title of the job. Optional.
  • start_time (Optional[str]) – The start time of the job. Optional.
  • end_time (Optional[str]) – The end time of the job. Optional.
  • revision (ScheduledRunRevisionMetadata) – Notebook revision data - ID and name.
  • duration (Optional[int]) – The job duration in seconds. May be None for example while the job is running. Optional.
  • run_type (Optional[RunType]) – The type of the run - either manual (triggered via UI or API) or scheduled. Optional.
  • notebook_type (Optional[NotebookType]) – The type of the notebook - either plain or codespace. Optional.

class datarobot.models.notebooks.session.CloneRepositorySchema¶

Schema for cloning a repository when starting a notebook session.

class datarobot.models.notebooks.session.StartSessionParameters¶

Parameters used as environment variables in a notebook session.

class datarobot.models.notebooks.session.StartSessionPayload¶

Payload for starting a notebook session.

class datarobot.models.notebooks.session.NotebookExecutionStatus¶

Notebook execution status information.

• Variables:
  • status (str) – The status of the notebook execution.
  • cell_id (Optional[bson.ObjectId]) – The ID of the cell being executed. Optional.
  • queued_cell_ids (Optional[List[bson.ObjectId]]) – The list of cell IDs that are queued for execution. Optional.

class datarobot.models.notebooks.session.CodespaceNotebookCell¶

Represents a cell in a codespace notebook.

class datarobot.models.notebooks.session.CodespaceNotebookState¶

Notebook state information for a codespace notebook.

• Variables:
  • name (str) – The name of the notebook.
  • path (str) – The path of the notebook.
  • generation (int) – The generation of the notebook.
  • nbformat (int) – The notebook format version.
  • nbformat_minor (int) – The notebook format minor version.
  • metadata (dict) – The metadata of the notebook.
  • cells (List[CodespaceNotebookCell]) – The list of cells in the notebook.
  • kernel_id (Optional[str]) – The ID of the kernel. Optional.

class datarobot.models.notebooks.session.NotebookSession¶

Notebook session information.

• Variables:
  • status (NotebookStatus) – The current status of the notebook kernel.
  • notebook_id (str) – The ID of the notebook.
  • session_id (str) – The ID of the session. Incorporates the notebook_id as part of this ID.
  • started_at (Optional[str]) – The date and time when the notebook was started. Optional.
  • session_type (Optional[SessionType]) – The type of the run - either manual (triggered via UI or API) or scheduled. Optional.
  • ephemeral_session_key (Optional[str]) – The ID specific to ephemeral session if being used. Optional.

classmethod get(notebook_id)¶

Get a notebook session by its notebook ID.

• Parameters: notebook_id (str) – The ID of the notebook.
• Returns: The notebook session information.
• Return type: NotebookSession

classmethod start(notebook_id, payload)¶

Start a notebook session.

• Parameters:
  • notebook_id (str) – The ID of the notebook.
  • payload (StartSessionPayload) – The payload to start the session.
• Returns: The notebook session information.
• Return type: NotebookSession

classmethod stop(notebook_id)¶

Stop a notebook session.

• Parameters: notebook_id (str) – The ID of the notebook.
• Returns: The notebook session information.
• Return type: NotebookSession

classmethod execute_notebook(notebook_id, cell_ids=None)¶

Execute a notebook.

• Parameters:
  • notebook_id (str) – The ID of the notebook.
  • cell_ids (Optional[List[bson.ObjectId]]) – The list of cell IDs to execute. Optional. If not provided, the whole notebook will be executed.
• Return type: None

classmethod execute_codespace_notebook(notebook_id, notebook_path, generation, cells)¶

Execute a notebook.

• Parameters:
  • notebook_id (str) – The ID of the notebook.
  • notebook_path (str) – The path of the notebook.
  • generation (int) – The generation of the notebook.
  • cells (List[CodespaceNotebookCell]) – The list of cells to execute.
• Return type: None

classmethod get_execution_status(notebook_id)¶

Get the execution status information of a notebook.

• Parameters: notebook_id (str) – The ID of the notebook.
• Returns: The execution status information of the notebook.
• Return type: NotebookExecutionStatus

class datarobot.models.notebooks.settings.NotebookSettings¶

Settings for a DataRobot Notebook.

• Variables:
  • show_line_numbers (bool) – Whether line numbers in cells should be displayed.
  • hide_cell_titles (bool) – Whether cell titles should be displayed.
  • hide_cell_outputs (bool) – Whether the cell outputs should be displayed.
  • show_scrollers (bool) – Whether scroll bars should be shown on cells.
  • hide_cell_footers (bool) – Whether footers should be shown on cells.
  • highlight_whitespace (bool) – Whether whitespace should be highlighted or not.

class datarobot.models.notebooks.user.NotebookUser¶

A user associated with a Notebook.

• Variables:
  • id (str) – The ID of the user.
  • activated (bool) – Whether or not the user is enabled.
  • username (str) – The username of the user, usually their email address.
  • first_name (str) – The first name of the user.
  • last_name (str) – The last name of the user.
  • gravatar_hash (Optional[str]) – The gravatar hash of the user. Optional.
  • tenant_phase (Optional[str]) – The phase that the user’s tenant is in. Optional.

class datarobot.models.notebooks.user.NotebookActivity¶

A record of activity (i.e. last run, updated, etc.) in a Notebook.

• Variables:
  • at (str) – The time of the activity in the notebook.
  • by (NotebookUser) – The user who performed the activity.