def get(self, key, columns=None, column_start="", column_finish="",
            column_reversed=False, column_count=100, include_timestamp=False,
            super_column=None, read_consistency_level=None, include_ttl=False):

        packed_key = self._pack_key(key)
        single_column = columns is not None and len(columns) == 1
        if (not self.super and single_column) or \
           (self.super and super_column is not None and single_column):
            column = None
            if self.super and super_column is None:
                super_column = columns[0]
            else:
                column = columns[0]
            cp = self._column_path(super_column, column)
            col_or_super = self.pool.execute('get', packed_key, cp,
                    read_consistency_level or self.read_consistency_level)
            return self._cosc_to_dict([col_or_super], include_timestamp, include_ttl)
        else:
            cp = self._column_parent(super_column)
            sp = self._slice_predicate(columns, column_start, column_finish,
                                       column_reversed, column_count, super_column)

            list_col_or_super = self.pool.execute('get_slice', packed_key, cp, sp,
                read_consistency_level or self.read_consistency_level)

            if len(list_col_or_super) == 0:
                raise NotFoundException()
            return self._cosc_to_dict(list_col_or_super, include_timestamp, include_ttl)
Execute double precision real-to-complex forward transform plan.
dataset/ETHPy150Open pycassa/pycassa/pycassa/columnfamily.py/ColumnFamily.get--crossover with--dataset/ETHPy150Open lebedov/scikit-cuda/skcuda/cufft.py/cufftExecD2Z