Expectation#

hsfs.expectation.Expectation(
    name,
    features,
    rules,
    description=None,
    featurestore_id=None,
    href=None,
    expand=None,
    items=None,
    count=None,
    type=None,
)

Metadata object representing an feature validation expectation in the Feature Store.

Properties#

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description#

Description of the expectation.

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features#

Optional list of features this expectation is applied to. If no features are provided, the expectation will be applied to all the feature group features.

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name#

Name of the expectation, unique per feature store (project).

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rules#

List of rules applied to the features of the expectation.

Methods#

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save#

Expectation.save()

Persist the expectation metadata object to the feature store.

Creation#

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create_expectation#

FeatureStore.create_expectation(name, description="", features=[], rules=[])

Create an expectation metadata object.

Lazy

This method is lazy and does not persist the expectation in the feature store on its own. To materialize the expectation and save call the save() method of the expectation metadata object.

Arguments

name str: Name of the expectation to create.
description Optional[str]: A string describing the expectation that can describe its business logic and applications within the feature store.
features Optional[List[str]]: The features this expectation is applied on.
rules Optional[List[hsfs.rule.Rule]]: The validation rules this expectation will apply to the features.

Returns:

Expectation: The expectation metadata object.

Retrieval#

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get_expectations#

FeatureStore.get_expectations()

Get all expectation entities from the feature store.

Getting expectations from the Feature Store means getting their metadata handles so you can subsequently add features and/or rules and save it which will overwrite the previous instance.

Returns

Expectation: The expectation metadata object.

Raises

RestAPIError: If unable to retrieve the expectations from the feature store.

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get_expectation#

FeatureStore.get_expectation(name)

Get an expectation entity from the feature store.

Getting an expectation from the Feature Store means getting its metadata handle so you can subsequently add features and/or rules and save it which will overwrite the previous instance.

Arguments

name str: Name of the training dataset to get.

Returns

Expectation: The expectation metadata object.

Raises

RestAPIError: If unable to retrieve the expectation from the feature store.