Skip to content

On-premise users: click in-app to access the full platform documentation for your version of DataRobot.

DataRobot API resources > API reference documentation > API changelogs > Python client changelogs

Python client changelogs

Changelogs contain curated, ordered lists of notable changes for each versioned release for DataRobot's Python API client. Reference the changelog below to view changes for DataRobot's newest version, and view previous versions in the table of contents.

Python API client v3.6 changelog

New features

  • Added a new class, OCRJobResource, for running OCR jobs.
  • Added new Jina V2 embedding model in VectorDatabaseEmbeddingModel.
  • Added new small multi-lingual embedding model in VectorDatabaseEmbeddingModel.
  • Added the method Deployment.get_segment_attributes to retrieve segment attributes.
  • Added the method Deployment.get_segment_values to retrieve segment values.
  • Added the method AutomatedDocument.list_all_available_document_types to return a list of document types.
  • Added the method Model.request_per_class_fairness_insights to return per-class bias and fairness insights.
  • Added the class MLOpsEvent <datarobot.mlops.events.MLOpsEvent> to report MLOps events. This class only supports moderation MLOps events.
  • Added the method Deployment.get_moderation_events to retrieve moderation events for that deployment.
  • Extended the advanced options available when setting a target to include new parameters: number_of_incremental_learning_iterations_before_best_model_selection (part of the AdvancedOptions object). This parameter allows you to specify how long the top five models will run prior to the selection of the best model.
  • Added support for connector_type in the method Connector.create.
  • Added the class DataQualityExport and the method Deployment.list_data_quality_exports, used to to retrieve a list of data quality records.
  • Added secure config support for Azure Service Principal credentials.
  • Added support for categorical custom metrics in CustomMetric.
  • Added the class NemoConfiguration <datarobot.models.genai.nemo_configuration.NemoConfiguration> to manage Nemo configurations.
  • Added the method NemoConfiguration.create <datarobot.models.genai.nemo_configuration.NemoConfiguration.upsert> to create or update a Nemo configuration.
  • Added the method NemoConfiguration.get <datarobot.models.genai.nemo_configuration.NemoConfiguration.get> to retrieve a Nemo configuration.
  • Added a new class ShapDistributions <datarobot.insights.ShapDistributions> to interact with SHAP distribution insights.
  • Added the MODEL_COMPLIANCE_GEN_AI value to the attribute document_type from the class DocumentOption <datarobot.models.automated_documentation.DocumentOption> to generate compliance documentation for LLMs in the Registry.
  • Added new attribute prompts_count to the class Chat.
  • Added the class Recipe modules for Data Wrangling.
  • Added the class RecipeOperation and a set of subclasses to represent a single Recipe.operations operation.
  • Added a new attribute similarity_score to the class Citation.
  • Added a new attributes retriever and add_neighbor_chunks to the class VectorDatabaseSettings.
  • Added a new attribute metadata to the class Citation.
  • Added a new attribute metadata_filter to the class ChatPrompt.
  • Added a new attribute metadata_filter to the class ComparisonPrompt.
  • Added a new attribute custom_chunking to the class ChunkingParameters.
  • Added a new attribute custom_chunking to the class VectorDatabase.
  • Added a new class LLMTestConfiguration for LLM test configurations.
  • Use the method LLMTestConfiguration.get <datarobot.models.genai.llm_test_configuration.LLMTestConfiguration.get> to retrieve a hosted LLM test configuration.
  • Use the method LLMTestConfiguration.list <datarobot.models.genai.llm_test_configuration.LLMTestConfiguration.list> to list hosted LLM test configurations.
  • Use the method LLMTestConfiguration.create <datarobot.models.genai.llm_test_configuration.LLMTestConfiguration.create> to create an LLM test configuration.
  • Use the method LLMTestConfiguration.update <datarobot.models.genai.llm_test_configuration.LLMTestConfiguration.update> to update an LLM test configuration.
  • Use the method LLMTestConfiguration.delete <datarobot.models.genai.llm_test_configuration.LLMTestConfiguration.delete> to delete an LLM test configuration.
  • Added a new classLLMTestConfigurationSupportedInsights for LLM test configuration supported insights.
  • Use the method LLMTestConfigurationSupportedInsights.list to list hosted LLM test configuration supported insights.
  • Added a new class LLMTestResult for LLM test results.
  • Use the method LLMTestResult.get to retrieve a hosted LLM test result.
  • Use the method LLMTestResult.list to list hosted LLM test results.
  • Use the method LLMTestResult.create to create an LLM test result.
  • Use the method LLMTestResult.delete to delete an LLM test result.
  • Added a new attribute dataset_name to the class OOTBDatasetDict.
  • Added a new attribute rows_count to the class OOTBDatasetDict.
  • Added a new attribute max_num_prompts to the class DatasetEvaluationDict.
  • Added a new attribute prompt_sampling_strategy to the class DatasetEvaluationDict.
  • Added a new class DatasetEvaluationRequestDict for dataset evaluations in create and edit requests.
  • Added a new attribute evaluation_dataset_name to the class InsightEvaluationResult <datarobot.models.genai.llm_test_result.InsightEvaluationResult>.
  • Added a new attribute chat_name to the class InsightEvaluationResult.
  • Added a new attribute llm_test_configuration_name to the class LLMTestResult.
  • Added a new attribute creation_user_name to the class LLMTestResult.
  • Added a new attribute pass_percentage to the class LLMTestResult.
  • Added a new attribute evaluation_dataset_name to the class DatasetEvaluation.
  • Added a new attribute datasets_compatibility to the class LLMTestConfigurationSupportedInsights.
  • Added a new class NonOOTBDataset for non out-of-the-box (OOTB) dataset entities.
  • Use the method NonOOTBDataset.list to retrieve non OOTB datasets for compliance testing.
  • Added a new class {class}OOTBDataset for out-of-the-box dataset entities.
  • Use the method OOTBDataset.list to retrieve out-of-the-box datasets for compliance testing.
  • Added a new class TraceMetadata to retrieve trace metadata.
  • Add new attributes to the class VectorDatabase: parent_id, family_id, metadata_columns, added_dataset_ids, added_dataset_names, and version.
  • Use the method VectorDatabase.get_supported_retrieval_settings to retrieve supported retrieval settings.
  • Use the method VectorDatabase.submit_export_dataset_job to submit the vector database as a dataset to the AI catalog.
  • Updated the method VectorDatabase.create to create a new vector database version.
  • Added a new class SupportedRetrievalSettings for supported vector database retrieval settings.
  • Added a new class SupportedRetrievalSetting for supported vector database retrieval setting.
  • Added a new class VectorDatabaseDatasetExportJob for vector database dataset export jobs.
  • Added new attribute playground_id to the class CostMetricConfiguration.
  • Added new attribute name to the class CostMetricConfiguration.
  • Added a new class SupportedInsights to support lists.
  • Use the method SupportedInsights.list to list supported insights.
  • Added a new class MetricInsights for the new metric insights routes.
  • Use the method MetricInsights.list to list metric insights.
  • Use the method MetricInsights.copy_to_playground to copy metrics to another playground.
  • Added a new class PlaygroundOOTBMetricConfiguration for OOTB metric configurations.
  • Updated the schema for the class EvaluationDatasetMetricAggregation to include the new attributes ootb_dataset_name, dataset_id, and dataset_name.
  • Updated the method EvaluationDatasetMetricAggregation.list with additional optional filter parameters.
  • Added new attribute warning to the class OOTBDataset.
  • Added new attribute warning to the class OOTBDatasetDict.
  • Added new attribute warnings to the class LLMTestConfiguration.
  • Added a new parameter playground_id to the method SidecarModelMetricValidation.create to support sidecar model metrics transition to playground.
  • Updated the schema for the class NemoConfiguration to include the new attributes prompt_pipeline_template_id and response_pipeline_template_id.
  • Added new attributes to the class EvaluationDatasetConfiguration: rows_count and playground_id.

API changes

  • Updated the exc_message for ServerError to be constructed with a request ID to help with debugging.
  • Added the method Deployment.get_capabilities to retrieve a list of Capability objects containing capability details.
  • Advanced options parameters: modelGroupId, modelRegimeId, and modelBaselines were renamed into seriesId, forecastDistance, and forecastOffsets.
  • Added the parameter use_sample_from_dataset from the method Project.create_from_dataset. This parameter, when set, uses the EDA sample of the dataset to start the project.
  • Added the parameter quick_compute to functions in the classes ShapMatrix, ShapImpact, and ShapPreview.
  • Added the parameter copy_insights to the method Playground.create to copy the insights from an existing playground to a new one.
  • Added the parameter llm_test_configuration_ids to the method LLMBlueprint.register_custom_model, used to run LLM compliance tests when a blueprint is sent to the custom model workshop.

Enhancements

  • Added standard pagination parameters (e.g. limit, offset) to the method Deployment.list <datarobot.models.Deployment.list>, allowing you to get deployment data in smaller chunks.

Bugfixes

  • Fixed a field in the class CustomTaskVersion for controlling network policies. This is changed from outgoing_network_policy to outbound_network_policy. When performing a GET action, this field was incorrect and always resolved to None. When attempting a POST or PATCH action, the incorrect field would result in a 422 error. A
  • Changed the name of datarobot.enums.CustomTaskOutgoingNetworkPolicy to datarobot.enums.CustomTaskOutboundNetworkPolicy to reflect the proper field name.
  • Fixed a schema for the class DataSliceSizeInfo so that it allows an empty list for the messages field.

Deprecation summary

  • Removed the parameter in_use from the method ImageAugmentationList.create. This parameter was deprecated in v3.1.0.
  • Deprecated the method AutomatedDocument.list_available_document_types. Please use the method AutomatedDocument.list_all_available_document_types instead.
  • Deprecated the method Model.request_fairness_insights. Please use the method Model.request_per_class_fairness_insights instead, to return StatusCheckJob instead of status_id.
  • Deprecated the method Model.get_prime_eligibility. Prime models are no longer supported.
  • The eligibleForPrime field will no longer be returned from the method Model.get_supported_capabilities and will be removed after version 3.8 is released.
  • Deprecated the property ShapImpact.row_count and it will be removed after version 3.7 is released.
  • Advanced options parameters: modelGroupId, modelRegimeId, and modelBaselines were renamed into seriesId, forecastDistance, and forecastOffsets. The former names are deprecated and they will be removed after version 3.6 is released.
  • Renamed datarobot.enums.CustomTaskOutgoingNetworkPolicy to datarobot.enums.CustomTaskOutboundNetworkPolicy to reflect bugfix changes. The original enum was unusable.
  • Removed the parameter user_agent_suffix in datarobot.Client. Please use trace_context instead.
  • Removed the deprecated method DataStore.get_access_list. Please use the method DataStore.get_shared_roles instead.
  • Removed support for SharingAccess instances in the method DataStore.update_access_list. Use SharingRole instances instead.
  • Deprecated file_path for the methods Connector.create and Connector.update.

Configuration changes

  • Removed the upper bound pin on the urllib3 package to allow versions 2.0.2 and above.
  • Upgraded the Pillow library to version 10.3.0. Users installing DataRobot with the "images" extra (pip install datarobot[images]) should note that this is a required library.

Documentation changes

  • The API Reference page has been split into multiple sections for better usability.
  • Fixed documentation for the method Project.refresh to clarify that it does not return a value.
  • Fixed code examples for the class ExternalScores.
  • Added a copy button to code examples in ReadTheDocs documentation, for convenience.
  • Removed the outdated "Examples" section from the documentation. Please refer to DataRobot's API Documentation Home for more examples.
  • Removed the duplicate "Getting started" section from the documentation.
  • Updated to Sphinx RTD Theme v3.

Experimental changes

  • Added the force_update parameter to the update method in the class ChunkDefinition.
  • Removed attribute select_columns from the class ChunkDefinition
  • Added initial experimental support for Chunking Service V2
  • DatasetDefinition
  • DatasetProps
  • DatasetInfo
  • DynamicDatasetProps
  • RowsChunkDefinition
  • FeaturesChunkDefinition
  • ChunkDefinitionStats

  • ChunkDefinition

  • Added a new method, update, to the class ChunkDefinition.

  • Added experimental support for time series wrangling, including a usage template:

  • datarobot._experimental.models.time_series_wrangling_template.user_flow_template: Experimental changes offer automated time series feature engineering for the data in Snowflake or Postgres.

  • Added the ability to use the Spark dialect when creating a recipe, allowing data wrangling support for files.

  • Added new attribute warning to the class Chat.

  • Moved all modules from datarobot._experimental.models.genai to datarobot.models.genai.

  • Added a new method Model.train_first_incremental_from_sample that trains the first incremental learning iteration from an existing sample model. Requires the "Project Creation from a Dataset Sample" feature flag.

Updated January 8, 2025