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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def create_continuous_query(self, name, select, database=None, resample_opts=None):
 r"""Create a continuous query for a database. :param name: the name of continuous query to create :type name: str :param select: select statement for the continuous query :type select: str :param database: the database for which the continuous query is created. Defaults to current client's database :type database: str :param resample_opts: resample options :type resample_opts: str :Example: :: >> select_clause = 'SELECT mean("value") INTO "cpu_mean" ' \ >> client.create_continuous_query( >> client.get_list_continuous_queries() [ { 'db_name': [ { 'name': 'cpu_mean', 'query': 'CREATE CONTINUOUS QUERY "cpu_mean" ' 'ON "db_name" ' 'RESAMPLE EVERY 10s FOR 2m ' 'BEGIN SELECT mean("value") ' 'INTO "cpu_mean" FROM "cpu" ' 'GROUP BY time(1m) END' } ] } ] """

        query_string = (
            "CREATE CONTINUOUS QUERY {0} ON {1}{2} BEGIN {3} END"
        ).format(quote_ident(name), quote_ident(database or self._database),
                 ' RESAMPLE ' + resample_opts if resample_opts else '', select)
        self.query(query_string)