Connection without specifying catalog name in connection string causes an error

src/databricks/sqlalchemy/base.py の278行目付近から始め、接続文字列でカタログが省略されている場合に get_table_names がカタログをどのように処理するかを追跡してください。スキーマと明示的なカタログを指定して SHOW VIEWS の失敗を再現し、その後、メタデータ検査で None カタログを生成せずにそのカタログを対象にできることを確認してください。

Hello,
I'm trying to create an engine connection which could manage multiple catalogs at once

connection_uri = "databricks://token:XXXXXX@DB_HOST?http_path=/sql/1.0/warehouses/DWH_ID"
engine = create_engine(connection_uri, future=True)
meta_inspector = inspect(self.engine)

Later when calling for example
tables = meta_inspector.get_table_names('test_schema')
I get the following error

backend-1  | sqlalchemy.exc.DatabaseError: (databricks.sql.exc.ServerOperationError) Fail to execute the command as the target schema `None.test_schema` is not in the current catalog. Please set the current catalog with 'USE CATALOG None' first.
backend-1  | [SQL: SHOW VIEWS FROM `None`.`test_schema`]

After further inspection I found the current method being called:
https://github.com/databricks/databricks-sql-python/blob/62eb1d407ab03fc2c57a6626bec2173dbdd8bbb3/src/databricks/sqlalchemy/base.py#L278

It could be fixed with adding on Line 278 the following:
_target_catalog = kwags.get("catalog") or self.catalog
and referencing the catalog name in the method get_table_names
tables = meta_inspector.get_table_names(schema='test_schema',catalog='test_catalog')

NOTE : I'm avoiding creating a different engine for every catalog due to slow response from Databricks
I'm hesitant in opening a PR for this as it's not well tested and I'm not sure if there is an alternative to what i'm trying to achieve , so any feedback would be great !