Too many connections issue with postgres and multiprocessing

Question

I am trying to read and write to a db in the following way:

with open("argument_file.txt", "r") as f:
    arguments = f.read().split("\n")
engine = create_engine('postgresql://...', pool_size=20, max_overflow=0)
with futures.ProcessPoolExecutor(max_workers=20, initializer=lambda : engine.dispose(close=False)) as e:
    for result in e.map(main, arguments):
        print(result)

def main(argument):
    metadata = s.MetaData()
    events = Table('events', metadata, autoload_with=engine)
    query = select(events).where(...)  
    with engine.connect() as connection:
        ResultProxy = connection.execute(query)
        df = pd.DataFrame(ResultProxy.fetchall())
        df.columns = ResultProxy.keys()
    transformed_df = f(df)
    transformed_df.to_sql("table_name", engine, if_exists="append", index=False)
    return f"Argument {argument} processed"
    

(f is a function that maps a pd.DataFrame to a pd.DataFrame.) I am running into an error sqlalchemy.exc.OperationalError: (psycopg2.OperationalError) FATAL: sorry, too many clients already. When checking SELECT * FROM pg_stat_activity; I am seeing many old idle processes (the most I have seen is 96, which could explain that there is an issue with a pool size of 20 and a maximum of 115 connections in postgresql).

I suspect that there is an issue with closing old connections. But I think my code closes (either via context manager or via pd built-in code). What am I missing? (If this way to read/write is suboptimal in other ways, I'd also be very happy to hear that!)