Use the list_feature_catalogs() method to list all the feature catalogs.
There are no parameters for this function.
Example setup
>>> from teradataml import FeatureStore
Example 1: List all the feature catalogs in the repo 'vfs_v1'
Create FeatureStore for the repo 'vfs_v1' or use existing one.
>>> fs = FeatureStore("vfs_v1")
FeatureStore is ready to use.
Load the sales data.
>>> load_example_data("dataframe", "sales")
>>> df = DataFrame("sales")
Create a feature process.
>>> from teradataml import FeatureProcess >>> fp = FeatureProcess(repo="vfs_v1", ... data_domain='sales', ... object=df, ... entity="accounts", ... features=["Jan", "Feb", "Mar", "Apr"]) >>> fp.run()
Process '5747082b-4acb-11f0-a2d7-f020ffe7fe09' started. Process '5747082b-4acb-11f0-a2d7-f020ffe7fe09' completed.
List all the feature catalogs in the repo 'vfs_v1'.
>>> fs.list_feature_catalogs()
data_domain feature_id table_name valid_start valid_end entity_name accounts sales 2 FS_T_918e1cb4_c6bc_6d38_634d_7b9fe53e2a63 2025-06-16 16:02:49.481245+00: 9999-12-31 23:59:59.999999+00: accounts sales 100001 FS_T_e84ff803_3d5c_4793_cd72_251c780fffe4 2025-06-16 16:02:49.481245+00: 9999-12-31 23:59:59.999999+00: accounts sales 1 FS_T_918e1cb4_c6bc_6d38_634d_7b9fe53e2a63 2025-06-16 16:02:49.481245+00: 9999-12-31 23:59:59.999999+00: accounts sales 200001 FS_T_918e1cb4_c6bc_6d38_634d_7b9fe53e2a63 2025-06-16 16:02:49.481245+00: 9999-12-31 23:59:59.999999+00: