(cls, selectable, sampling, name=None, seed=None)
return coercions.expect(roles.FromClauseRole, selectable).tablesample(
            sampling, name=name, seed=seed
        )
Return a :class:`.TableSample` object.

        :class:`.TableSample` is an :class:`.Alias` subclass that represents
        a table with the TABLESAMPLE clause applied to it.
        :func:`~.expression.tablesample`
        is also available from the :class:`.FromClause` class via the
        :meth:`.FromClause.tablesample` method.

        The TABLESAMPLE clause allows selecting a randomly selected approximate
        percentage of rows from a table. It supports multiple sampling methods,
        most commonly BERNOULLI and SYSTEM.

        e.g.::

            from sqlalchemy import func

            selectable = people.tablesample(
                        func.bernoulli(1),
                        name='alias',
                        seed=func.random())
            stmt = select([selectable.c.people_id])

        Assuming ``people`` with a column ``people_id``, the above
        statement would render as::

            SELECT alias.people_id FROM
            people AS alias TABLESAMPLE bernoulli(:bernoulli_1)
            REPEATABLE (random())

        .. versionadded:: 1.1

        :param sampling: a ``float`` percentage between 0 and 100 or
            :class:`.functions.Function`.

        :param name: optional alias name

        :param seed: any real-valued SQL expression.  When specified, the
         REPEATABLE sub-clause is also rendered.
Return a :class:`.TableSample` object.
Return a : class : . TableSample object .
def _factory(cls, selectable, sampling, name=None, seed=None):
        """Return a :class:`.TableSample` object.

        :class:`.TableSample` is an :class:`.Alias` subclass that represents
        a table with the TABLESAMPLE clause applied to it.
        :func:`~.expression.tablesample`
        is also available from the :class:`.FromClause` class via the
        :meth:`.FromClause.tablesample` method.

        The TABLESAMPLE clause allows selecting a randomly selected approximate
        percentage of rows from a table. It supports multiple sampling methods,
        most commonly BERNOULLI and SYSTEM.

        e.g.::

            from sqlalchemy import func

            selectable = people.tablesample(
                        func.bernoulli(1),
                        name='alias',
                        seed=func.random())
            stmt = select([selectable.c.people_id])

        Assuming ``people`` with a column ``people_id``, the above
        statement would render as::

            SELECT alias.people_id FROM
            people AS alias TABLESAMPLE bernoulli(:bernoulli_1)
            REPEATABLE (random())

        .. versionadded:: 1.1

        :param sampling: a ``float`` percentage between 0 and 100 or
            :class:`.functions.Function`.

        :param name: optional alias name

        :param seed: any real-valued SQL expression.  When specified, the
         REPEATABLE sub-clause is also rendered.

        """
        return coercions.expect(roles.FromClauseRole, selectable).tablesample(
            sampling, name=name, seed=seed
        )
def _factory ( cls , selectable , sampling , name = None , seed = None ) : return coercions . expect ( roles . FromClauseRole , selectable ) . tablesample ( sampling , name = name , seed = seed )