python sql_metadata to extract table names from SQL query

I have an existing python dataframe which contains the following columns. [login to view URL] [login to view URL] [login to view URL] I've already extracted data from the SQL Server processsnapshot table into a python dataframe. This works & is not part of the task. I would like to extract the table names from the existing dataframe (data) using Column [login to view URL] There are multiple rows of data. Using code from [login to view URL] I've been able to manually copy & paste the data, it works, but I'm after some automation. I would like to automate this process (there are hundreds of rows) The above code puts the results into a string I would like the recorded into a new dataframe & recorded with user & QueryStartTme. 1 result = 1 row. . ie. USER1 1/1/23 9:00:00:00 [login to view URL] USER1 1/1/23 9:00:00:00 [login to view URL] User 1 ran a query starting 1/1/23 9:00:00:00, their single query references 2 tables, so there are 2 seperate entries This task should factor in all table naming conventions. As programs like Tableau, Python, Alteryx, SQL users are running queries on server. In summary, I would like to extract all the table names from a query & have the results neatly presented in a new table.