How to use the pymapd._parsers._extract_column_details function in pymapd

TColumnType(col_name='qty',
                        col_type=TTypeInfo(type=1, encoding=0, nullable=True,
                                           is_array=False, precision=0,
                                           scale=0, comp_param=0),
                        is_reserved_keyword=False, src_name=''),
            TColumnType(col_name='price',
                        col_type=TTypeInfo(type=3, encoding=0, nullable=True,
                                           is_array=False, precision=0,
                                           scale=0, comp_param=0),
                        is_reserved_keyword=False, src_name=''),
            TColumnType(col_name='vol',
                        col_type=TTypeInfo(type=3, encoding=0, nullable=True,
                                           is_array=False, precision=0,
                                           scale=0, comp_param=0),
                        is_reserved_keyword=False, src_name='')]
        result = _extract_column_details(data)

        expected = [
            ColumnDetails(name='date_', type='STR', nullable=True, precision=0,
                          scale=0, comp_param=32, encoding='DICT',
                          is_array=False),
            ColumnDetails(name='trans', type='STR', nullable=True, precision=0,
                          scale=0, comp_param=32, encoding='DICT',
                          is_array=False),
            ColumnDetails(name='symbol', type='STR', nullable=True,
                          precision=0, scale=0, comp_param=32,
                          encoding='DICT',
                          is_array=False),
            ColumnDetails(name='qty', type='INT', nullable=True, precision=0,
                          scale=0, comp_param=0, encoding='NONE',
                          is_array=False),
            ColumnDetails(name='price', type='FLOAT', nullable=True,

def _get_schema_using_query(self, query):
        with self._execute(query, results=True) as result:
            # resets the state of the cursor and closes operation
            result.cursor.fetchall()
            names, ibis_types = self._adapt_types(
                _extract_column_details(result.cursor._result.row_set.row_desc)
            )

        return sch.Schema(names, ibis_types)

Returns
        -------
        details: List[tuples]

        Examples
        --------
        >>> con.get_table_details('stocks')
        [ColumnDetails(name='date_', type='STR', nullable=True, precision=0,
                       scale=0, comp_param=32, encoding='DICT'),
         ColumnDetails(name='trans', type='STR', nullable=True, precision=0,
                       scale=0, comp_param=32, encoding='DICT'),
         ...
        ]
        """
        details = self._client.get_table_details(self._session, table_name)
        return _extract_column_details(details.row_desc)