def METHOD_NAME(
    self, mock_handler, lightfm_interaction_data
):
    self.set_handler(
        mock_handler, name="pg", tables={"df": lightfm_interaction_data}
    )
    # create project
    self.run_sql("create database proj")
    # create predictor
    self.run_sql(
        """
        create model proj.itemitemtest
        from pg (select * from df)
        predict movieId
        using
            engine='lightfm',
            item_id='movieId',
            user_id='userId',
            threshold=4,
            recommendation_type='{recommender_type}',
            n_recommendations=10
            """
    )
    self.wait_predictor("proj", "itemitemtest")
    result_df = self.run_sql(
        """
        SELECT p.*
        FROM pg.df as t
        JOIN proj.itemitemtest as p
        on t.movieId = p.movieId
        where p.recommender_type='item_item'
        """
    )
    # check that the result is the expected shape e.g. 10 recommendations per user  * 89 users
    assert result_df.shape == (890, 3)