awswrangler.catalog.tables(limit: int = 100, catalog_id: Optional[str] = None, database: Optional[str] = None, search_text: Optional[str] = None, name_contains: Optional[str] = None, name_prefix: Optional[str] = None, name_suffix: Optional[str] = None, boto3_session: Optional[boto3.session.Session] = None) → pandas.core.frame.DataFrame

Get a DataFrame with tables filtered by a search term, prefix, suffix.

  • limit (int, optional) – Max number of tables to be returned.

  • catalog_id (str, optional) – The ID of the Data Catalog from which to retrieve Databases. If none is provided, the AWS account ID is used by default.

  • database (str, optional) – Database name.

  • search_text (str, optional) – Select only tables with the given string in table’s properties.

  • name_contains (str, optional) – Select by a specific string on table name

  • name_prefix (str, optional) – Select by a specific prefix on table name

  • name_suffix (str, optional) – Select by a specific suffix on table name

  • boto3_session (boto3.Session(), optional) – Boto3 Session. The default boto3 session will be used if boto3_session receive None.


Pandas Dataframe filled by formatted infos.

Return type

Iterator[Dict[str, Any]]


>>> import awswrangler as wr
>>> df_tables = wr.catalog.tables()