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FeatureSetOperations Class

  • Reference

FeatureSetOperations.

You should not instantiate this class directly. Instead, you should create an MLClient instance that instantiates it for you and attaches it as an attribute.

Inheritance
azure.ai.ml._scope_dependent_operations._ScopeDependentOperations
FeatureSetOperations

Constructor

FeatureSetOperations(operation_scope: OperationScope, operation_config: OperationConfig, service_client: AzureMachineLearningServices, service_client_for_jobs: AzureMachineLearningWorkspaces, datastore_operations: DatastoreOperations, **kwargs: Dict)

Parameters

Name Description
operation_scope
Required
operation_config
Required
service_client
Required
service_client_for_jobs
Required
datastore_operations
Required

Methods

archive

Archive a FeatureSet asset.
begin_backfill

Backfill.
begin_create_or_update

Create or update FeatureSet
get

Get the specified FeatureSet asset.
get_feature

Get Feature
list

List the FeatureSet assets of the workspace.
list_features

List features
list_materialization_operations

List Materialization operation.
restore

Restore an archived FeatureSet asset.

archive

Archive a FeatureSet asset.

archive(name: str, version: str, **kwargs: Dict) -> None

Parameters

Name Description
name
Required
str

Name of FeatureSet asset.
version
Required
str

Version of FeatureSet asset.

Returns

Type Description

None

begin_backfill

Backfill.

begin_backfill(*, name: str, version: str, feature_window_start_time: datetime | None = None, feature_window_end_time: datetime | None = None, display_name: str | None = None, description: str | None = None, tags: Dict[str, str] | None = None, compute_resource: MaterializationComputeResource | None = None, spark_configuration: Dict[str, str] | None = None, data_status: List[str | DataAvailabilityStatus] | None = None, job_id: str | None = None, **kwargs: Dict) -> LROPoller[FeatureSetBackfillMetadata]

Keyword-Only Parameters

Name Description
name
str

Feature set name. This is case-sensitive.
version
str

Version identifier. This is case-sensitive.
feature_window_start_time
datetime

Start time of the feature window to be materialized.
feature_window_end_time
datetime

End time of the feature window to be materialized.
display_name
str

Specifies description.
description
str

Specifies description.
tags
dict[str, str]

A set of tags. Specifies the tags.
compute_resource
MaterializationComputeResource

Specifies the compute resource settings.
spark_configuration
dict[str, str]

Specifies the spark compute settings.
data_status
list[str or DataAvailabilityStatus]

Specifies the data status that you want to backfill.
job_id
str

The job id.

Returns

Type Description
LROPoller[FeatureSetBackfillMetadata]

An instance of LROPoller that returns ~azure.ai.ml.entities.FeatureSetBackfillMetadata

begin_create_or_update

Create or update FeatureSet

begin_create_or_update(featureset: FeatureSet, **kwargs: Dict) -> LROPoller[FeatureSet]

Parameters

Name Description
featureset
Required
FeatureSet

FeatureSet definition.

Returns

Type Description
LROPoller[FeatureSet]

An instance of LROPoller that returns a FeatureSet.

get

Get the specified FeatureSet asset.

get(name: str, version: str, **kwargs: Dict) -> FeatureSet

Parameters

Name Description
name
Required
str

Name of FeatureSet asset.
version
Required
str

Version of FeatureSet asset.

Returns

Type Description
FeatureSet

FeatureSet asset object.

Exceptions

Type Description
ValidationException

Raised if FeatureSet cannot be successfully identified and retrieved. Details will be provided in the error message.
HttpResponseError

Raised if the corresponding name and version cannot be retrieved from the service.

get_feature

Get Feature

get_feature(feature_set_name: str, version: str, *, feature_name: str, **kwargs: Dict) -> Feature | None

Parameters

Name Description
feature_set_name
Required
str

Feature set name.
version
Required
str

Feature set version.

Keyword-Only Parameters

Name Description
feature_name
str

The feature name. This argument is case-sensitive.
tags
str

String representation of a comma-separated list of tag names, and optionally, values. For example, "tag1,tag2=value2". If provided, only features matching the specified tags are returned.

Returns

Type Description
Feature

Feature object

list

List the FeatureSet assets of the workspace.

list(name: str | None = None, *, list_view_type: ListViewType = ListViewType.ACTIVE_ONLY, **kwargs: Dict) -> ItemPaged[FeatureSet]

Parameters

Name Description
name
Required
Optional[str]

Name of a specific FeatureSet asset, optional.

Keyword-Only Parameters

Name Description
list_view_type

View type for including/excluding (for example) archived FeatureSet assets. Defaults to ACTIVE_ONLY.

Returns

Type Description
ItemPaged[FeatureSet]

An iterator like instance of FeatureSet objects

list_features

List features

list_features(feature_set_name: str, version: str, *, feature_name: str | None = None, description: str | None = None, tags: str | None = None, **kwargs: Dict) -> ItemPaged[Feature]

Parameters

Name Description
feature_set_name
Required
str

Feature set name.
version
Required
str

Feature set version.

Keyword-Only Parameters

Name Description
feature_name
str

feature name.
description
str

Description of the featureset.
tags
str

Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2.

Returns

Type Description
ItemPaged[Feature]

An iterator like instance of Feature objects

list_materialization_operations

List Materialization operation.

list_materialization_operations(name: str, version: str, *, feature_window_start_time: str | datetime | None = None, feature_window_end_time: str | datetime | None = None, filters: str | None = None, **kwargs: Dict) -> ItemPaged[FeatureSetMaterializationMetadata]

Parameters

Name Description
name
Required
str

Feature set name.
version
Required
str

Feature set version.

Keyword-Only Parameters

Name Description
feature_window_start_time
Union[str, datetime]

Start time of the feature window to filter materialization jobs.
feature_window_end_time
Union[str, datetime]

End time of the feature window to filter materialization jobs.
filters
str

Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2.

Returns

Type Description
ItemPaged[FeatureSetMaterializationMetadata]

An iterator like instance of ~azure.ai.ml.entities.FeatureSetMaterializationMetadata objects

restore

Restore an archived FeatureSet asset.

restore(name: str, version: str, **kwargs: Dict) -> None

Parameters

Name Description
name
Required
str

Name of FeatureSet asset.
version
Required
str

Version of FeatureSet asset.

Returns

Type Description

None