awswrangler.catalog.tables(limit: int = 100, catalog_id: str | None = None, database: str | None = None, search_text: str | None = None, name_contains: str | None = None, name_prefix: str | None = None, name_suffix: str | None = None, boto3_session: Session | None = None) DataFrame

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


This function has arguments which can be configured globally through wr.config or environment variables:

  • catalog_id

  • database

Check out the Global Configurations Tutorial for details.

  • 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 table information.

Return type:



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