How to use the datacompy.NUMERIC_SPARK_TYPES function in datacompy

def comparison_known_diffs1(base_td, compare_source, spark):
    return SparkCompare(
        spark,
        base_td,
        compare_source,
        join_columns=[("acct", "ACCOUNT_IDENTIFIER"), ("acct_seq", "SEQ_NUMBER")],
        column_mapping=[("stat_cd", "STATC"), ("open_dt", "ACCOUNT_OPEN"), ("cd", "CODE")],
        known_differences=[
            {
                "name": "Left-padded, four-digit numeric code",
                "types": datacompy.NUMERIC_SPARK_TYPES,
                "transformation": "lpad(cast({input} AS bigint), 4, '0')",
            },
            {
                "name": "Null to *2",
                "types": ["string"],
                "transformation": "case when {input} is null then '*2' else {input} end",
            },
            {
                "name": "Julian date -> date",
                "types": ["bigint"],
                "transformation": "to_date(cast(unix_timestamp(cast({input} AS string), 'yyyyDDD') AS timestamp))",
            },

def test_decimal_comparisons():
    true_decimals = ["decimal", "decimal()", "decimal(20, 10)"]
    assert all(v in datacompy.NUMERIC_SPARK_TYPES for v in true_decimals)