Execute a SQL query with internal cursor from python

I'm working on a research project and need to generate multiple temporary tables for my analysis. The query to create those tables looks like this:

DECLARE crsr CURSOR FORWARD_ONLY FOR
  SELECT DISTINCT 
    YEAR(s.date) AS Jahr, 
    MONTH(s.date) AS Monat
  FROM ##preliminary_data___id__ AS s;

OPEN crsr;
FETCH NEXT FROM crsr
INTO
  @year, @month;
WHILE @@fetch_Status = 0
BEGIN
  PRINT 'Next Date -------------------------------------'
  DECLARE @date DATE = DATEFROMPARTS(@year, @month, 1);
  PRINT @date;

  INSERT INTO ##final_data___id__(--snip--)
  SELECT 
    --snip--

  FETCH NEXT FROM crsr
  INTO @year, @month;
 
END;

CLOSE crsr;
DEALLOCATE crsr;

The query, executed from MS SSMS works as expected. I have about 15k subjects, so I would like to generate these table automatically, ideally using python. When I use sqlalchemy, this is my code:

engine = sqlalchemy.create_engine(cxn_str)
with engine.raw_connection().cursor() as cursor:
    cursor.execute(query)
    cursor.commit()

This runs successfully, but the resulting ##final_data___id__ only contains the data for one month. It also runs very quickly, which leads me to assume that FETCH NEXT FROM crsr is never actually performed.

How would I correctly execute this query from python, such that the created table contains the data for all available months?

This is a research project that runs against a corporate database, therefore I have no rights to create stored procedures or tables. ##tables are the longest lasting objects that are possible, and in this setup this is acceptable.

Thanks!