---
title: Python client changelog
description: Reference the changes introduced to new versions of DataRobot's Python client.

---

# Python client changelog {: #python-client-changelog }

Reference the changes introduced to new versions of DataRobot's Python client.

## Python client v3.3 {: #python-client-v32}

### 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 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.

### Bugfixes

- Payload property `subset` renamed to `source` in `Model.request_feature_effect`
- Fixed an issue where Context.trace_context was not being set from environment variables or DR config files.
- `Project.refresh` no longer sets `Project.advanced_options` to a dictionary.
- Fixed `Dataset.modify` to clarify behavior of when to preserve or clear categories.
- Fixed an issue with enums in f-strings resulting in the enum class and property being printed instead of the enum property's value in Python 3.11 environments.

### Deprecation Summary

- `Project.refresh` will no longer set `Project.advanced_options` to a dictionary after version 3.5 is released. All interactions with `Project.advanced_options` should be expected to be through the `AdvancedOptions` class.

### Experimental changes

- Added a new class, `VectorDatabase`, for interacting with DataRobot vector databases.
  * `VectorDatabase.get` retrieves a VectorDatabase object by ID.
  * `VectorDatabase.list` lists all VectorDatabases available to the user.
  * `VectorDatabase.create` creates a new VectorDatabase.
  * `VectorDatabase.create` allows you to use a validated deployment of a custom model as your own Vector Database.
  * `VectorDatabase.update` updates the name of a VectorDatabase.
  * `VectorDatabase.delete` deletes a single VectorDatabase.
  * `VectorDatabase.get_supported_embeddings` retrieves all supported embedding models.
  * `VectorDatabase.get_supported_text_chunkings` retrieves all supported text chunking configurations.
  * `VectorDatabase.download_text_and_embeddings_asset` download a parquet file with internal vector database data.

- Added a new class, `CustomModelVectorDatabaseValidation`, for validating custom model deployments for use as a vector database.
  * `CustomModelVectorDatabaseValidation.get` retrieves a CustomModelVectorDatabaseValidation object by ID.
  * `CustomModelVectorDatabaseValidation.get_by_values` retrieves a CustomModelVectorDatabaseValidation object by field values.
  * `CustomModelVectorDatabaseValidation.create` starts validation of the deployment.
  * `CustomModelVectorDatabaseValidation.revalidate` repairs an unlinked external vector database.

- Added a new class, `Playground`, for interacting with DataRobot generative AI playgrounds.
  * `Playground.get` retrieves a playground object by ID.
  * `Playground.list` lists all playgrounds available to the user.
  * `Playground.create` creates a new playground.
  * `Playground.update` updates the name and description of a playground.
  * `Playground.delete` deletes a single playground.

- Added a new class, `LLMDefinition`, for interacting with DataRobot generative AI LLMs.
  * `LLMDefinition.list` lists all LLMs available to the user.

- Added a new class, `LLMBlueprint`, for interacting with DataRobot generative AI LLM blueprints.
  * `LLMBlueprint.get` retrieves an LLM blueprint object by ID.
  * `LLMBlueprint.list` lists all LLM blueprints available to the user.
  * `LLMBlueprint.create` creates a new LLM blueprint.
  * `LLMBlueprint.create_from_llm_blueprint` creates a new LLM blueprint from an existing one.
  * `LLMBlueprint.update` updates an LLM blueprint.
  * `LLMBlueprint.delete` deletes a single LLM blueprint.

- Added a new class, `ChatPrompt`, for interacting with DataRobot generative AI chat prompts.
  * `ChatPrompt.get` retrieves a chat prompt object by ID.
  * `ChatPrompt.list` lists all chat prompts available to the user.
  * `ChatPrompt.create` creates a new chat prompt.
  * `ChatPrompt.delete` deletes a single chat prompt.

- Added a new class, `CustomModelLLMValidation`, for validating custom model deployments for use as a custom model LLM.
  * `CustomModelLLMValidation.get` retrieves a CustomModelLLMValidation object by ID.
  * `CustomModelLLMValidation.get_by_values` retrieves a CustomModelLLMValidation object by field values.
  * `CustomModelLLMValidation.create` starts validation of the deployment.
  * `CustomModelLLMValidation.revalidate` repairs an unlinked external custom model LLM.

- Added a new class, `ComparisonPrompt`, for interacting with DataRobot generative AI comparison prompts.
  * `ComparisonPrompt.get` retrieves a comparison prompt object by ID.
  * `ComparisonPrompt.list` lists all comparison prompts available to the user.
  * `ComparisonPrompt.create` creates a new comparison prompt.
  * `ComparisonPrompt.update` updates a comparison prompt.
  * `ComparisonPrompt.delete` deletes a single comparison prompt.

- Extended `UseCase`, adding two new fields to represent the count of vector databases and playgrounds.

- Added a new method, `ChatPrompt.create_llm_blueprint`, to create an LLM blueprint from a chat prompt.

- Added a new method, `CustomModelLLMValidation.delete`, to delete a custom model LLM validation record.

- Added a new method, `LLMBlueprint.register_custom_model`, for registering a custom model from a generative AI LLM blueprint.
