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Code-first (V9.2)

November 22, 2023

The DataRobot v9.2 release includes many new features and capabilities for code-first users, described below. See additional details of Release 9.2 in the data and modeling and MLOps release announcements.

Code-first features
Name GA Preview
Notebooks
Schedule notebook jobs
Use custom environments in DataRobot Notebooks
API enhancements
DataRobot REST API v2.32
Python client v3.2

Notebooks

Preview

Schedule notebook jobs

Now available for preview, you can automate your code-based workflows by scheduling notebooks to run on a schedule in non-interactive mode. Notebook scheduling is managed by notebook jobs. Additionally, you can parameterize a notebook to enhance the automation experience enabled by notebook scheduling. By defining certain values in a notebook as parameters, you can provide inputs for those parameters when a notebook job runs instead of having to continuously modify the notebook itself to change the values for each run.

Required feature flag: Enable Notebooks Scheduling

Preview documentation.

Use custom environments in DataRobot Notebooks

Now available for preview, DataRobot Notebooks is integrated with DataRobot custom environments, allowing you to define reusable custom Docker images for running notebook sessions. You can create a custom environment to use for your notebook sessions if you want full control over the environment, and to leverage reproducible dependencies beyond those available in the built-in images.

Required feature flag: Enable Notebooks Custom Environments

Preview documentation.

API

GA

DataRobot REST API v2.32

DataRobot's v2.32 for the REST API is now generally available. For a complete list of changes introduced in v2.31, view the REST API changelog.

New features

  • New routes to retrieve document thumbnail insights:
    • GET /api/v2/projects/(projectId)/documentThumbnails/
    • GET /api/v2/projects/(projectId)/documentPages/(documentPageId)/file/
    • GET /api/v2/projects/(projectId)/documentThumbnailSamples/
    • GET /api/v2/projects/(projectId)/documentThumbnailBins/
  • New routes to compute and retrieve document text extraction sample insights:
    • POST /api/v2/models/(modelId)/documentTextExtractionSamples/
    • GET /api/v2/projects/(projectId)/documentTextExtractionSamples/
    • GET /api/v2/models/(modelId)/documentTextExtractionSampleDocuments/
    • GET /api/v2/models/(modelId)/documentTextExtractionSamplePages/
  • New routes to retrieve document data quality information:
    • GET /api/v2/projects/(projectId)/documentsDataQualityLog/
    • GET /api/v2/datasets/(datasetId)/documentsDataQualityLog/
    • GET /api/v2/datasets/(datasetId)/versions/(datasetVersionId)/documentsDataQualityLog/
  • New routes to retrieve document data quality information as log files:
    • GET /api/v2/projects/(projectId)/documentsDataQualityLog/file/
    • GET /api/v2/datasets/(datasetId)/documentsDataQualityLog/file/,
    • GET /api/v2/datasets/(datasetId)/versions/(datasetVersionId)/documentsDataQualityLog/file/
  • New route to retrieve deployment predictions vs actuals over time:
    • GET /api/v2/deployments/(deploymentId)/predictionsVsActualsOverTime/
  • New routes to managed registered models and registered model versions(previously known as Model Packages):
    • GET /api/v2/registeredModels/
    • GET /api/v2/registeredModels/(registeredModelId)/
    • PATCH /api/v2/registeredModels/(registeredModelId)/
    • DELETE /api/v2/registeredModels/(registeredModelId)/
    • GET /api/v2/registeredModels/(registeredModelId)/versions/
    • GET /api/v2/registeredModels/(registeredModelId)/versions/(versionId)/
    • PATCH /api/v2/registeredModels/(registeredModelId)/sharedRoles/
    • GET /api/v2/registeredModels/(registeredModelId)/sharedRoles/
    • GET /api/v2/registeredModels/(registeredModelId)/deployments/
    • GET /api/v2/registeredModels/(registeredModelId)/versions/(versionId)/deployments/
  • Added new routes for Use Cases, listed below:
    • GET /api/v2/useCases/
    • POST /api/v2/useCases/
    • GET /api/v2/useCases/(useCaseId)/
    • PATCH /api/v2/useCases/(useCaseId)/
    • DELETE /api/v2/useCases/(useCaseId)/
    • GET /api/v2/useCases/(useCaseId)/projects/
    • GET /api/v2/useCases/(useCaseId)/applications/
    • GET /api/v2/useCases/(useCaseId)/datasets/
    • GET /api/v2/useCases/(useCaseId)/notebooks/
    • GET /api/v2/useCases/(useCaseId)/playgrounds/
    • GET /api/v2/useCases/(useCaseId)/vectorDatabases/
    • GET /api/v2/useCases/(useCaseId)/modelsForComparison/
    • GET /api/v2/useCases/(useCaseId)/filterMetadata/
    • GET /api/v2/useCases/(useCaseId)/resources/
    • GET /api/v2/useCases/(useCaseId)/sharedRoles/
    • PATCH /api/v2/useCases/(useCaseId)/sharedRoles/
    • POST /api/v2/useCases/(useCaseId)/(referenceCollectionType)/(entityId)/
    • DELETE /api/v2/useCases/(useCaseId)/(referenceCollectionType)/(entityId)/

Python client v3.2

v3.2 for DataRobot's Python client is now generally available. For a complete list of changes introduced in v2.31, view the Python client changelog.

New Features

  • Added support for Python 3.11.
  • Added new a library, "strenum", to add StrEnum support while maintaining backwards compatibility with Python 3.7-3.10. DataRobot does not use the native StrEnum class in Python 3.11.
  • Added a new class PredictionEnvironment for interacting with DataRobot prediction environments.
  • Extended the advanced options available when setting a target to include new parameters: modelGroupId, modelRegimeId, and modelBaselines (part of the AdvancedOptions object). These parameters allow you to specify the user columns required to run time series models without feature derivation in OTV projects.
  • Added a new method PredictionExplanations.create_on_training_data, for computing prediction explanation on training data.

  • Added a new class RegisteredModel for interacting with DataRobot registered models to support the following methods:

  • RegisteredModel.get to retrieve a RegisteredModel object by ID.
  • RegisteredModel.list to list all registered models.
  • RegisteredModel.archive to permanently archive registered model.
  • RegisteredModel.update to update registered model.
  • RegisteredModel.get_shared_roles to retrieve access control information for a registered model.
  • RegisteredModel.share to share a registered model.
  • RegisteredModel.get_version to retrieve a RegisteredModelVersion object by ID.
  • RegisteredModel.list_versions to list registered model versions.
  • RegisteredModel.list_associated_deployments to list deployments associated with a registered model.

  • Added a new class RegisteredModelVersion for interacting with DataRobot registered model versions (also known as model packages) to support the following methods:

  • RegisteredModelVersion.create_for_external to create a new registered model version from an external model.
  • RegisteredModelVersion.list_associated_deployments to list deployments associated with a registered model version.
  • RegisteredModelVersion.create_for_leaderboard_item to create a new registered model version from a Leaderboard model.
  • RegisteredModelVersion.create_for_custom_model_version to create a new registered model version from a custom model version.

  • Added a new method Deployment.create_from_registered_model_version to support creating deployments from a registered model version.

  • Added a new method Deployment.download_model_package_file to support downloading model package files (.mlpkg) of the currently deployed model.

  • Added support for retrieving document thumbnails:

  • DocumentThumbnail <datarobot.models.documentai.document.DocumentThumbnail>
  • DocumentPageFile <datarobot.models.documentai.document.DocumentPageFile>

  • Added support to retrieve document text extraction samples using:

  • DocumentTextExtractionSample
  • DocumentTextExtractionSamplePage
  • DocumentTextExtractionSampleDocument

  • Added new fields to CustomTaskVersion for controlling network policies. The new fields were also added to the response. This can be set with datarobot.enums.CustomTaskOutgoingNetworkPolicy.

  • Added a new method BatchPredictionJob.score_with_leaderboard_model to run batch predictions using a Leaderboard model instead of a deployment.

  • Set IntakeSettings and OutputSettings to use IntakeAdapters and OutputAdapters enum values respectively for the property type.

  • Added the method Deployment.get_predictions_vs_actuals_over_time to retrieve a deployment's predictions vs actuals over time data.

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Updated March 26, 2024