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Feature#

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Feature#

hsfs.feature.Feature(
    name,
    type=None,
    description=None,
    primary=None,
    partition=None,
    hudi_precombine_key=None,
    online_type=None,
    default_value=None,
    feature_group_id=None,
    feature_group=None,
)

Metadata object representing a feature in a feature group in the Feature Store.

See Training Dataset Feature for the feature representation of training dataset schemas.


Properties#

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default_value#

Default value of the feature as string, if the feature was appended to the feature group.


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description#

Description of the feature.


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feature_group_id#


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hudi_precombine_key#

Whether the feature is part of the hudi precombine key of the feature group.


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name#

Name of the feature.


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online_type#

Data type of the feature in the online feature store.


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partition#

Whether the feature is part of the partition key of the feature group.


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primary#

Whether the feature is part of the primary key of the feature group.


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type#

Data type of the feature in the offline feature store.

Not a Python type

This type property is not to be confused with Python types. The type property represents the actual data type of the feature in the feature store.


Methods#

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contains#

Feature.contains(other)

Deprecated

contains method is deprecated. Use isin instead.


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from_response_json#

Feature.from_response_json(json_dict)

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is_complex#

Feature.is_complex()

Returns true if the feature has a complex type.

Example

# connect to the Feature Store
fs = ...

# get the Feature Group instance
fg = fs.get_or_create_feature_group(...)

selected_feature = fg.get_feature("min_temp")
selected_feature.is_complex()

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isin#

Feature.isin(other)

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json#

Feature.json()

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like#

Feature.like(other)

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to_dict#

Feature.to_dict()

Get structured info about specific Feature in python dictionary format.

Example

# connect to the Feature Store
fs = ...

# get the Feature Group instance
fg = fs.get_or_create_feature_group(...)

selected_feature = fg.get_feature("min_temp")
selected_feature.to_dict()