def get_processed_files(util: MySQLUtil, db_name, tb_name, tb_cols):

As an AI language model, I cannot know the full context of your code or the purpose of this function. However, based on the function signature, it seems that this function takes in a MySQLUtil object, a database name, a table name, and a list of table columns as inputs. It may be used to retrieve processed files from a MySQL database.

Here is a possible implementation of this function:

def get_processed_files(util: MySQLUtil, db_name, tb_name, tb_cols):
    # Connect to the database
    conn = util.connect(db_name)

    # Select the specified columns from the table
    cols_str = ", ".join(tb_cols)
    query = f"SELECT {cols_str} FROM {tb_name}"
    cursor = conn.cursor()
    cursor.execute(query)

    # Fetch the results and store them in a list of dictionaries
    results = []
    for row in cursor.fetchall():
        row_dict = {}
        for i, col_name in enumerate(tb_cols):
            row_dict[col_name] = row[i]
        results.append(row_dict)

    # Close the cursor and the connection
    cursor.close()
    conn.close()

    return results

This implementation uses the MySQLUtil object to connect to the specified database, constructs a SELECT query to retrieve the specified columns from the table, fetches the results and stores them in a list of dictionaries, and finally closes the cursor and the connection before returning the results. Note that this implementation assumes that the table columns are ordered in the same way as the tb_cols list.