Search for components in FeatureStore | Teradata Package for Python - Search for components in FeatureStore - Teradata Package for Python

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for Python
Release Number
20.00
Published
December 2024
ft:locale
en-US
ft:lastEdition
2025-01-23
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nvi1706202040305.ditamap
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plt1683835213376.ditaval
dita:id
rkb1531260709148
Product Category
Teradata Vantage

Use the following functions to search for the relevant component in FeatureStore.

list_features

Use list_features() to retrieve available Features in the teradataml DataFrame. You can use any filter that is supported by terdataml DataFrame to search Feature details.

You can use the same API to list down archived Features. See Remove components from FeatureStore.

Example:

>>> fs.list_features()
      column_name description               creation_time modified_time  tags data_type feature_type  status group_name
name
Mar          Mar        None  2024-09-30 11:21:43.314118          None  None    BIGINT   CONTINUOUS  ACTIVE      sales
Jan          Jan        None  2024-09-30 11:21:42.655343          None  None    BIGINT   CONTINUOUS  ACTIVE      sales
Apr          Apr        None  2024-09-30 11:21:44.143402          None  None    BIGINT   CONTINUOUS  ACTIVE      sales
Feb          Feb        None  2024-09-30 11:21:41.542627          None  None     FLOAT   CONTINUOUS  ACTIVE      sales
>>>

list_entities

Use list_entities() to retrieve available Entities in the teradataml DataFrame. You can use any filter that is supported by terdataml DataFrame to search Entity details.

You can use the same API to list down archived Entities. See Remove components from FeatureStore.

Example:

>>> fs.list_entities()
                    description
name  entity_column
sales accounts             None
>>>

list_data_sources

Use list_data_sources() to retrieve available Data Sources in the teradataml DataFrame. You can use any filter that is supported by terdataml DataFrame to search Data Source details.

You can use the same API to list down archived Data Sources. See Remove components from FeatureStore.

Example:

>>> fs.list_data_sources()
            description timestamp_col_name                            source
name
admissions        None               None  select * from "admissions_train"
>>>

list_feature_groups

Use list_feature_groups() to retrieve available Feature Groups in the teradataml DataFrame. You can use any filter that is supported by terdataml DataFrame to search Feature Group details.

You can use the same API to list down archived Feature Groups. See Remove components from FeatureStore.
>>> fs.list_feature_groups()
           description data_source_name entity_name
name
admissions        None       admissions  admissions
>>>