Python sql.column方法代碼示例

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def downgrade():
    ''' Remove column access_id from user_projects and projects_groups '''

    # this removes the current constraints as well.
    op.drop_column('user_projects', 'access')
    op.drop_column('projects_groups', 'access')

    # recreate the previous constraints
    op.create_unique_constraint(
            None,
            'user_projects',
            ['project_id', 'user_id'],
    )
    op.create_primary_key(
            None,
            'projects_groups',
            ['project_id', 'group_id'],
    )
    op.drop_table('access_levels') 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def columns(self):
        """The set of columns exported by this :class:`.FunctionElement`.

        Function objects currently have no result column names built in;
        this method returns a single-element column collection with
        an anonymously named column.

        An interim approach to providing named columns for a function
        as a FROM clause is to build a :func:`.select` with the
        desired columns::

            from sqlalchemy.sql import column

            stmt = select([column('x'), column('y')]).\
                select_from(func.myfunction())


        """
        return ColumnCollection(self.label(None)) 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def _clone(self):
        """Create a shallow copy of this ClauseElement.

        This method may be used by a generative API.  Its also used as
        part of the "deep" copy afforded by a traversal that combines
        the _copy_internals() method.

        """
        c = self.__class__.__new__(self.__class__)
        c.__dict__ = self.__dict__.copy()
        ClauseElement._cloned_set._reset(c)
        ColumnElement.comparator._reset(c)

        # this is a marker that helps to "equate" clauses to each other
        # when a Select returns its list of FROM clauses.  the cloning
        # process leaves around a lot of remnants of the previous clause
        # typically in the form of column expressions still attached to the
        # old table.
        c._is_clone_of = self

        return c 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def _find_columns(clause):
    """locate Column objects within the given expression."""

    cols = util.column_set()
    traverse(clause, {}, {'column': cols.add})
    return cols


# there is some inconsistency here between the usage of
# inspect() vs. checking for Visitable and __clause_element__.
# Ideally all functions here would derive from inspect(),
# however the inspect() versions add significant callcount
# overhead for critical functions like _interpret_as_column_or_from().
# Generally, the column-based functions are more performance critical
# and are fine just checking for __clause_element__().  It is only
# _interpret_as_from() where we'd like to be able to receive ORM entities
# that have no defined namespace, hence inspect() is needed there. 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def dimensions(self):
        _dimensions = []
        for dim in self.model_desc.get('simplified_dimensions'):
            table_alias = dim.get('column').split('.')[0]
            table = dict(self._model_lookups).get(table_alias)
            table = table.get('table') if table else self.fact_table.fullname
            table_clz = _Table(table, table_alias)

            column = dim['column'].split('.')[1]
            column_alias = dim['name']
            tbl_map = self.tables_and_columns
            description = dict(tbl_map[table_clz.fullname].get('columns')).get(column)
            if description:
                ke4_dim_id = dim.get('id')
                ke4_dim_status = dim.get('status')
                column_clz = _Column(column, column_alias, description)
                _dimensions.append(_CubeDimension(table_clz, column_clz, ke4_dim_id, ke4_dim_status))
        return _dimensions 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def dimensions(self):
        _dimensions = []
        for dim in self.cube_desc.get('dimensions'):
            table_alias = dim.get('table')
            table = dict(self._model_lookups).get(table_alias)
            table = table.get('table') if table else self.fact_table.fullname
            table_clz = _Table(table, table_alias)

            column = dim['column'] if dim['derived'] is None else dim['derived'][0]
            column_alias = dim['name']
            tbl_map = self.tables_and_columns
            description = dict(tbl_map[table_clz.fullname].get('columns')).get(column)
            column_clz = _Column(column, column_alias, description)

            _dimensions.append(_CubeDimension(table_clz, column_clz))
        return _dimensions 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def upgrade():
    # Add collumn redirect_prefix
    op.add_column(
        u'l7policy',
        sa.Column(u'redirect_prefix', sa.String(255), nullable=True)
    )
    insert_table = sql.table(
        u'l7policy_action',
        sql.column(u'name', sa.String),
        sql.column(u'description', sa.String)
    )

    op.bulk_insert(
        insert_table,
        [
            {'name': 'REDIRECT_PREFIX'}
        ]
    ) 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def batch_add_column(
        cls, operations, column, insert_before=None, insert_after=None
    ):
        """Issue an "add column" instruction using the current
        batch migration context.

        .. seealso::

            :meth:`.Operations.add_column`

        """

        kw = {}
        if insert_before:
            kw["insert_before"] = insert_before
        if insert_after:
            kw["insert_after"] = insert_after

        op = cls(
            operations.impl.table_name,
            column,
            schema=operations.impl.schema,
            **kw
        )
        return operations.invoke(op) 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def batch_drop_column(cls, operations, column_name, **kw):
        """Issue a "drop column" instruction using the current
        batch migration context.

        .. seealso::

            :meth:`.Operations.drop_column`

        """
        op = cls(
            operations.impl.table_name,
            column_name,
            schema=operations.impl.schema,
            **kw
        )
        return operations.invoke(op) 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def alias(self, name=None, flat=False):
        """Produce a :class:`.Alias` construct against this
        :class:`.FunctionElement`.

        This construct wraps the function in a named alias which
        is suitable for the FROM clause, in the style accepted for example
        by Postgresql.

        e.g.::

            from sqlalchemy.sql import column

            stmt = select([column('data_view')]).\\
                select_from(SomeTable).\\
                select_from(func.unnest(SomeTable.data).alias('data_view')
            )

        Would produce:

        .. sourcecode:: sql

            SELECT data_view
            FROM sometable, unnest(sometable.data) AS data_view

        .. versionadded:: 0.9.8 The :meth:`.FunctionElement.alias` method
           is now supported.  Previously, this method's behavior was
           undefined and did not behave consistently across versions.

        """

        return Alias(self, name) 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def expression(self):
        """Return a column expression.

        Part of the inspection interface; returns self.

        """
        return self 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def _compare_name_for_result(self, other):
        """Return True if the given column element compares to this one
        when targeting within a result row."""

        return hasattr(other, 'name') and hasattr(self, 'name') and \
            other.name == self.name 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def compare(self, other, use_proxies=False, equivalents=None, **kw):
        """Compare this ColumnElement to another.

        Special arguments understood:

        :param use_proxies: when True, consider two columns that
          share a common base column as equivalent (i.e. shares_lineage())

        :param equivalents: a dictionary of columns as keys mapped to sets
          of columns. If the given "other" column is present in this
          dictionary, if any of the columns in the corresponding set() pass
          the comparison test, the result is True. This is used to expand the
          comparison to other columns that may be known to be equivalent to
          this one via foreign key or other criterion.

        """
        to_compare = (other, )
        if equivalents and other in equivalents:
            to_compare = equivalents[other].union(to_compare)

        for oth in to_compare:
            if use_proxies and self.shares_lineage(oth):
                return True
            elif hash(oth) == hash(self):
                return True
        else:
            return False 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def label(self, name):
        """Produce a column label, i.e. ``<columnname> AS <name>``.

        This is a shortcut to the :func:`~.expression.label` function.

        if 'name' is None, an anonymous label name will be generated.

        """
        return Label(name, self, self.type) 

# 需要導入模塊: from sqlalchemy import sql [as 別名]
# 或者: from sqlalchemy.sql import column [as 別名]
def literal_column(text, type_=None):
    """Produce a :class:`.ColumnClause` object that has the
    :paramref:`.column.is_literal` flag set to True.

    :func:`.literal_column` is similar to :func:`.column`, except that
    it is more often used as a "standalone" column expression that renders
    exactly as stated; while :func:`.column` stores a string name that
    will be assumed to be part of a table and may be quoted as such,
    :func:`.literal_column` can be that, or any other arbitrary column-oriented
    expression.

    :param text: the text of the expression; can be any SQL expression.
      Quoting rules will not be applied. To specify a column-name expression
      which should be subject to quoting rules, use the :func:`column`
      function.

    :param type\_: an optional :class:`~sqlalchemy.types.TypeEngine`
      object which will
      provide result-set translation and additional expression semantics for
      this column. If left as None the type will be NullType.

    .. seealso::

        :func:`.column`

        :func:`.text`

        :ref:`sqlexpression_literal_column`

    """
    return ColumnClause(text, type_=type_, is_literal=True)