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Basically what I'm trying to do is use the info schema to generate a dataframe of drop commands that I would then want to iterate through and execute.

import snowflake.snowpark as snowpark

def main(session: snowpark.Session): 

    drop_commands = session.sql(""" SELECT 'DROP ' || table_type ||  ' if exists <database>.' || table_schema || '.' || table_name || ';' as drop_command
                                    FROM  <database>.INFORMATION_SCHEMA.TABLES 
                                    WHERE table_catalog = '<database>' 
                                        and table_schema in '<schema>'""").collect()
    for iter,row in df:

    # Return value will appear in the Results tab.
    return drop_commands

I'm expecting that the drop_commands object will return as a data frame and then the loop will iterate through each drop command and drop snowflake object that I tell it to using the query. When I comment out the loop and get rid of the .collect() at the end of the drop_commands definition then I can see the data frame returned in the results... However, this is contradictory to the documentation that Snowflake has available (* .collect() executes the sql *). I've tried different versions of the loop as well because of reading about the differences between a snowpark and pandas data frame to no avail.

Note that I would like to have these snowpark issues addressed regardless of whether there is an easier way to purge certain tables/schemas/databases - however if anyone does know how to do that programmatically that'd be great feedback as well.

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