Feature#
[source] Feature #
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.
[source] default_value property writable #
default_value: str | None
Default value of the feature as string, if the feature was appended to the feature group.
[source] feature_group_id property #
feature_group_id: int | None
ID of the feature group to which this feature belongs.
[source] foreign property writable #
foreign: bool
Whether the feature is part of the foreign key of the feature group.
[source] hudi_precombine_key property writable #
hudi_precombine_key: bool
Whether the feature is part of the hudi precombine key of the feature group.
[source] on_demand property writable #
on_demand: bool
Whether the feature is a on-demand feature computed using on-demand transformation functions.
[source] online_type property writable #
online_type: str | None
Data type of the feature in the online feature store.
[source] partition property writable #
partition: bool
Whether the feature is part of the partition key of the feature group.
[source] primary property writable #
primary: bool
Whether the feature is part of the primary key of the feature group.
[source] type property writable #
type: str | None
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.
[source] use_fully_qualified_name property writable #
use_fully_qualified_name: bool
Use fully qualified name for the feature when generating dataframes for training/batch data.
[source] contains #
Construct a filter similar to SQL's IN operator.
Deprecated
contains method is deprecated. Use Feature.isin instead.
| PARAMETER | DESCRIPTION |
|---|---|
other | A single feature value or a list of feature values. |
| RETURNS | DESCRIPTION |
|---|---|
filter.Filter | A filter that leaves only the feature values also contained in |
[source] is_complex #
is_complex() -> bool
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()
[source] like #
like(other: Any) -> filter.Filter
Returns LIKE filter for the feature; replicating the behavior of SQL LIKE clause.