def METHOD_NAME(
    _exact_match,
    col_names: list[str],
    salting_partitions: int = 1,
) -> BlockingRule:
    """Creates a series of blocking rules on designated columns or sql
        statements, that are then joined by "AND" clauses.
    It is recommended that you try to ensure your rules are equi-joins
    and only include `AND` clauses to join rules.
    More information can be found
    [here](https://moj-analytical-services.github.io/splink/topic_guides/blocking/performance.html)
    This function acts as a shorthand alias for the `brl.and_` syntax:
    > import splink.duckdb.blocking_rule_library as brl
    > `brl.and_(brl.exact_match_rule, brl.exact_match_rule, ...)`
        Args:
            col_names (list[str]): A list of input columns or sql conditions
                you wish to create blocks on.
            salting_partitions (optional, int): Whether to add salting
                to the blocking rule. More information on salting can
                be found within the docs. Salting is only valid for Spark.
        Examples:
            === ":simple-duckdb: DuckDB"
                ``` python
                import splink.duckdb.blocking_rule_library as brl
                sql = "substr(surname,1,2)"
                block_on([sql, "surname"])
                ```
            === ":simple-apachespark: Spark"
                ``` python
                import splink.spark.blocking_rule_library as brl
                sql = "substr(surname,1,2)"
                block_on([sql, "surname"], salting_partitions=1)
                ```
            === ":simple-amazonaws: Athena"
                ``` python
                import splink.athena.blocking_rule_library as brl
                sql = "substr(surname,1,2)"
                block_on([sql, "surname"])
                ```
            === ":simple-sqlite: SQLite"
                ``` python
                import splink.sqlite.blocking_rule_library as brl
                sql = "substr(surname,1,2)"
                block_on([sql, "surname"])
                ```
            === "PostgreSQL"
                ``` python
                import splink.postgres.blocking_rule_library as brl
                sql = "substr(surname,1,2)"
                block_on([sql, "surname"])
                ```
    """
    col_names = ensure_is_list(col_names)
    em_rules = [_exact_match(col) for col in col_names]
    return and_(*em_rules, salting_partitions=salting_partitions)