Python sqlalchemy.func 模块，bernoulli() 实例源码

我们从Python开源项目中，提取了以下9个代码示例，用于说明如何使用sqlalchemy.func.bernoulli()。

项目：ShelbySearch 作者：Agentscreech | 项目源码 | 文件源码

def tablesample(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 _interpret_as_from(selectable).tablesample(
        sampling, name=name, seed=seed)

项目：Price-Comparator 作者：Thejas-1 | 项目源码 | 文件源码

def tablesample(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 _interpret_as_from(selectable).tablesample(
        sampling, name=name, seed=seed)

项目：webapp 作者：superchilli | 项目源码 | 文件源码

def tablesample(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 _interpret_as_from(selectable).tablesample(
        sampling, name=name, seed=seed)

项目：QualquerMerdaAPI 作者：tiagovizoto | 项目源码 | 文件源码

def tablesample(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 _interpret_as_from(selectable).tablesample(
        sampling, name=name, seed=seed)

项目：gardenbot 作者：GoestaO | 项目源码 | 文件源码

def tablesample(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 _interpret_as_from(selectable).tablesample(
        sampling, name=name, seed=seed)

项目：flask-zhenai-mongo-echarts 作者：Fretice | 项目源码 | 文件源码

def tablesample(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 _interpret_as_from(selectable).tablesample(
        sampling, name=name, seed=seed)

项目：watcher 作者：nosmokingbandit | 项目源码 | 文件源码

def tablesample(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 _interpret_as_from(selectable).tablesample(
        sampling, name=name, seed=seed)

项目：flask 作者：bobohope | 项目源码 | 文件源码

def tablesample(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 _interpret_as_from(selectable).tablesample(
        sampling, name=name, seed=seed)

项目：Chorus 作者：DonaldBough | 项目源码 | 文件源码

def tablesample(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 _interpret_as_from(selectable).tablesample(
        sampling, name=name, seed=seed)