Teradata Package for Python Function Reference | 20.00 - list_data_sources - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.

Teradata® Package for Python Function Reference - 20.00

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for Python
Release Number
20.00.00.03
Published
December 2024
ft:locale
en-US
ft:lastEdition
2024-12-19
dita:id
TeradataPython_FxRef_Enterprise_2000
lifecycle
latest
Product Category
Teradata Vantage
teradataml.store.feature_store.feature_store.FeatureStore.list_data_sources = list_data_sources(self, archived=False) -> teradataml.dataframe.dataframe.DataFrame
DESCRIPTION:
    List all the Data Sources.
 
PARAMETERS:
    archived
        Optional Argument
        Specifies whether to list effective data sources or archived data sources.
        When set to False, effective data sources in FeatureStore are listed,
        otherwise, archived data sources are listed.
        Default Value: False
        Types: bool
 
RETURNS:
    teradataml DataFrame
 
RAISES:
    None
 
EXAMPLES:
    >>> from teradataml import DataSource, FeatureStore, load_example_data
    >>> load_example_data("dataframe", "admissions_train")
    # Create teradataml DataFrame.
    >>> admissions=DataFrame("admissions_train")
    # Create FeatureStore for repo 'vfs_v1'.
    >>> fs = FeatureStore("vfs_v1")
    # Create DataSource using teradataml DataFrame.
    >>> ds = DataSource(name='admissions', source=admissions)
    # Apply the DataSource to FeatureStore.
    >>> fs.apply(ds)
    True
 
    # Example 1: List all the effective DataSources in the repo 'vfs_v1'.
    >>> fs.list_data_sources()
               description timestamp_col_name                            source
    name
    admissions        None               None  select * from "admissions_train"
    >>>
 
    # Example 2: List all the archived DataSources in the repo 'vfs_v1'.
    # Let's first archive the DataSource.
    >>> fs.archive_data_source('admissions')
    DataSource 'admissions' is archived.
    True
    # List archived DataSources.
    >>> fs.list_data_sources(archived=True)
               description timestamp_col_name                            source               archived_time
    name
    admissions        None               None  select * from "admissions_train"  2024-09-30 12:05:39.220000
    >>>