path: root/lib/python2.7/site-packages/SQLAlchemy-0.7.0-py2.7-linux-x86_64.egg/sqlalchemy/ext/declarative.py

# ext/declarative.py
# Copyright (C) 2005-2011 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php

"""
Synopsis
========

SQLAlchemy object-relational configuration involves the
combination of :class:`.Table`, :func:`.mapper`, and class
objects to define a mapped class.
:mod:`~sqlalchemy.ext.declarative` allows all three to be
expressed at once within the class declaration. As much as
possible, regular SQLAlchemy schema and ORM constructs are
used directly, so that configuration between "classical" ORM
usage and declarative remain highly similar.

As a simple example::

    from sqlalchemy.ext.declarative import declarative_base

    Base = declarative_base()

    class SomeClass(Base):
        __tablename__ = 'some_table'
        id = Column(Integer, primary_key=True)
        name =  Column(String(50))

Above, the :func:`declarative_base` callable returns a new base class from
which all mapped classes should inherit. When the class definition is
completed, a new :class:`.Table` and
:func:`.mapper` will have been generated.

The resulting table and mapper are accessible via
``__table__`` and ``__mapper__`` attributes on the
``SomeClass`` class::

    # access the mapped Table
    SomeClass.__table__

    # access the Mapper
    SomeClass.__mapper__

Defining Attributes
===================

In the previous example, the :class:`.Column` objects are
automatically named with the name of the attribute to which they are
assigned.

To name columns explicitly with a name distinct from their mapped attribute,
just give the column a name.  Below, column "some_table_id" is mapped to the 
"id" attribute of `SomeClass`, but in SQL will be represented as "some_table_id"::

    class SomeClass(Base):
        __tablename__ = 'some_table'
        id = Column("some_table_id", Integer, primary_key=True)

Attributes may be added to the class after its construction, and they will be
added to the underlying :class:`.Table` and
:func:`.mapper()` definitions as appropriate::

    SomeClass.data = Column('data', Unicode)
    SomeClass.related = relationship(RelatedInfo)

Classes which are constructed using declarative can interact freely
with classes that are mapped explicitly with :func:`mapper`.

It is recommended, though not required, that all tables 
share the same underlying :class:`~sqlalchemy.schema.MetaData` object,
so that string-configured :class:`~sqlalchemy.schema.ForeignKey`
references can be resolved without issue.

Accessing the MetaData
=======================

The :func:`declarative_base` base class contains a
:class:`.MetaData` object where newly defined
:class:`.Table` objects are collected. This object is
intended to be accessed directly for
:class:`.MetaData`-specific operations. Such as, to issue
CREATE statements for all tables::

    engine = create_engine('sqlite://')
    Base.metadata.create_all(engine)

The usual techniques of associating :class:`.MetaData:` with :class:`.Engine`
apply, such as assigning to the ``bind`` attribute::

    Base.metadata.bind = create_engine('sqlite://')

To associate the engine with the :func:`declarative_base` at time
of construction, the ``bind`` argument is accepted::

    Base = declarative_base(bind=create_engine('sqlite://'))

:func:`declarative_base` can also receive a pre-existing
:class:`.MetaData` object, which allows a
declarative setup to be associated with an already 
existing traditional collection of :class:`~sqlalchemy.schema.Table`
objects:: 

    mymetadata = MetaData()
    Base = declarative_base(metadata=mymetadata)

Configuring Relationships
=========================

Relationships to other classes are done in the usual way, with the added
feature that the class specified to :func:`~sqlalchemy.orm.relationship`
may be a string name.  The "class registry" associated with ``Base``
is used at mapper compilation time to resolve the name into the actual
class object, which is expected to have been defined once the mapper
configuration is used:: 

    class User(Base):
        __tablename__ = 'users'

        id = Column(Integer, primary_key=True)
        name = Column(String(50))
        addresses = relationship("Address", backref="user")

    class Address(Base):
        __tablename__ = 'addresses'

        id = Column(Integer, primary_key=True)
        email = Column(String(50))
        user_id = Column(Integer, ForeignKey('users.id'))

Column constructs, since they are just that, are immediately usable,
as below where we define a primary join condition on the ``Address``
class using them:: 

    class Address(Base):
        __tablename__ = 'addresses'

        id = Column(Integer, primary_key=True)
        email = Column(String(50))
        user_id = Column(Integer, ForeignKey('users.id'))
        user = relationship(User, primaryjoin=user_id == User.id)

In addition to the main argument for :func:`~sqlalchemy.orm.relationship`,
other arguments which depend upon the columns present on an as-yet
undefined class may also be specified as strings.  These strings are
evaluated as Python expressions.  The full namespace available within
this evaluation includes all classes mapped for this declarative base,
as well as the contents of the ``sqlalchemy`` package, including
expression functions like :func:`~sqlalchemy.sql.expression.desc` and
:attr:`~sqlalchemy.sql.expression.func`:: 

    class User(Base):
        # ....
        addresses = relationship("Address",
                             order_by="desc(Address.email)", 
                             primaryjoin="Address.user_id==User.id")

As an alternative to string-based attributes, attributes may also be 
defined after all classes have been created.  Just add them to the target
class after the fact::

    User.addresses = relationship(Address,
                              primaryjoin=Address.user_id==User.id)

Configuring Many-to-Many Relationships
======================================

Many-to-many relationships are also declared in the same way
with declarative as with traditional mappings. The
``secondary`` argument to
:func:`.relationship` is as usual passed a 
:class:`.Table` object, which is typically declared in the 
traditional way.  The :class:`.Table` usually shares
the :class:`.MetaData` object used by the declarative base::

    keywords = Table(
        'keywords', Base.metadata,
        Column('author_id', Integer, ForeignKey('authors.id')),
        Column('keyword_id', Integer, ForeignKey('keywords.id'))
        )

    class Author(Base):
        __tablename__ = 'authors'
        id = Column(Integer, primary_key=True)
        keywords = relationship("Keyword", secondary=keywords)

As with traditional mapping, its generally not a good idea to use 
a :class:`.Table` as the "secondary" argument which is also mapped to
a class, unless the :class:`.relationship` is declared with ``viewonly=True``.
Otherwise, the unit-of-work system may attempt duplicate INSERT and
DELETE statements against the underlying table.

.. _declarative_sql_expressions:

Defining SQL Expressions
========================

The usage of :func:`.column_property` with Declarative to define
load-time, mapped SQL expressions is
pretty much the same as that described in
:ref:`mapper_sql_expressions`. Local columns within the same
class declaration can be referenced directly::

    class User(Base):
        __tablename__ = 'user'
        id = Column(Integer, primary_key=True)
        firstname = Column(String)
        lastname = Column(String)
        fullname = column_property(
            firstname + " " + lastname
        )

Correlated subqueries reference the :class:`.Column` objects they
need either from the local class definition or from remote 
classes::

    from sqlalchemy.sql import func

    class Address(Base):
        __tablename__ = 'address'

        id = Column('id', Integer, primary_key=True)
        user_id = Column(Integer, ForeignKey('user.id'))

    class User(Base):
        __tablename__ = 'user'

        id = Column(Integer, primary_key=True)
        name = Column(String)

        address_count = column_property(
            select([func.count(Address.id)]).\\
                where(Address.user_id==id)
        )

In the case that the ``address_count`` attribute above doesn't have access to
``Address`` when ``User`` is defined, the ``address_count`` attribute should
be added to ``User`` when both ``User`` and ``Address`` are available (i.e.
there is no string based "late compilation" feature like there is with
:func:`.relationship` at this time). Note we reference the ``id`` column
attribute of ``User`` with its class when we are no longer in the declaration
of the ``User`` class::

    User.address_count = column_property(
        select([func.count(Address.id)]).\\
            where(Address.user_id==User.id)
    ) 

Table Configuration
===================

Table arguments other than the name, metadata, and mapped Column
arguments are specified using the ``__table_args__`` class attribute.
This attribute accommodates both positional as well as keyword
arguments that are normally sent to the
:class:`~sqlalchemy.schema.Table` constructor.
The attribute can be specified in one of two forms. One is as a
dictionary:: 

    class MyClass(Base):
        __tablename__ = 'sometable'
        __table_args__ = {'mysql_engine':'InnoDB'}

The other, a tuple, where each argument is positional
(usually constraints)::

    class MyClass(Base):
        __tablename__ = 'sometable'
        __table_args__ = (
                ForeignKeyConstraint(['id'], ['remote_table.id']),
                UniqueConstraint('foo'),
                )

Keyword arguments can be specified with the above form by 
specifying the last argument as a dictionary::

    class MyClass(Base):
        __tablename__ = 'sometable'
        __table_args__ = (
                ForeignKeyConstraint(['id'], ['remote_table.id']),
                UniqueConstraint('foo'),
                {'autoload':True}
                )

Using a Hybrid Approach with __table__
=======================================

As an alternative to ``__tablename__``, a direct
:class:`~sqlalchemy.schema.Table` construct may be used.  The
:class:`~sqlalchemy.schema.Column` objects, which in this case require
their names, will be added to the mapping just like a regular mapping
to a table:: 

    class MyClass(Base):
        __table__ = Table('my_table', Base.metadata,
            Column('id', Integer, primary_key=True),
            Column('name', String(50))
        )

``__table__`` provides a more focused point of control for establishing
table metadata, while still getting most of the benefits of using declarative.
An application that uses reflection might want to load table metadata elsewhere
and simply pass it to declarative classes::

    from sqlalchemy.ext.declarative import declarative_base

    Base = declarative_base()
    Base.metadata.reflect(some_engine)

    class User(Base):
        __table__ = metadata.tables['user']

    class Address(Base):
        __table__ = metadata.tables['address']

Some configuration schemes may find it more appropriate to use ``__table__``, 
such as those which already take advantage of the data-driven nature of 
:class:`.Table` to customize and/or automate schema definition.   See
the wiki example `NamingConventions <http://www.sqlalchemy.org/trac/wiki/UsageRecipes/NamingConventions>`_
for one such example.

Mapper Configuration
====================

Declarative makes use of the :func:`~.orm.mapper` function internally
when it creates the mapping to the declared table.   The options
for :func:`~.orm.mapper` are passed directly through via the ``__mapper_args__``
class attribute.  As always, arguments which reference locally
mapped columns can reference them directly from within the 
class declaration::

    from datetime import datetime

    class Widget(Base):
        __tablename__ = 'widgets'

        id = Column(Integer, primary_key=True)
        timestamp = Column(DateTime, nullable=False)

        __mapper_args__ = {
                        'version_id_col': timestamp,
                        'version_id_generator': lambda v:datetime.now()
                    }

.. _declarative_inheritance:

Inheritance Configuration
=========================

Declarative supports all three forms of inheritance as intuitively
as possible.  The ``inherits`` mapper keyword argument is not needed
as declarative will determine this from the class itself.   The various
"polymorphic" keyword arguments are specified using ``__mapper_args__``.

Joined Table Inheritance
~~~~~~~~~~~~~~~~~~~~~~~~

Joined table inheritance is defined as a subclass that defines its own 
table::

    class Person(Base):
        __tablename__ = 'people'
        id = Column(Integer, primary_key=True)
        discriminator = Column('type', String(50))
        __mapper_args__ = {'polymorphic_on': discriminator}

    class Engineer(Person):
        __tablename__ = 'engineers'
        __mapper_args__ = {'polymorphic_identity': 'engineer'}
        id = Column(Integer, ForeignKey('people.id'), primary_key=True)
        primary_language = Column(String(50))

Note that above, the ``Engineer.id`` attribute, since it shares the
same attribute name as the ``Person.id`` attribute, will in fact
represent the ``people.id`` and ``engineers.id`` columns together, and
will render inside a query as ``"people.id"``. 
To provide the ``Engineer`` class with an attribute that represents
only the ``engineers.id`` column, give it a different attribute name::

    class Engineer(Person):
        __tablename__ = 'engineers'
        __mapper_args__ = {'polymorphic_identity': 'engineer'}
        engineer_id = Column('id', Integer, ForeignKey('people.id'),
                                                    primary_key=True)
        primary_language = Column(String(50))

Single Table Inheritance
~~~~~~~~~~~~~~~~~~~~~~~~

Single table inheritance is defined as a subclass that does not have
its own table; you just leave out the ``__table__`` and ``__tablename__``
attributes:: 

    class Person(Base):
        __tablename__ = 'people'
        id = Column(Integer, primary_key=True)
        discriminator = Column('type', String(50))
        __mapper_args__ = {'polymorphic_on': discriminator}

    class Engineer(Person):
        __mapper_args__ = {'polymorphic_identity': 'engineer'}
        primary_language = Column(String(50))

When the above mappers are configured, the ``Person`` class is mapped
to the ``people`` table *before* the ``primary_language`` column is
defined, and this column will not be included in its own mapping.
When ``Engineer`` then defines the ``primary_language`` column, the
column is added to the ``people`` table so that it is included in the
mapping for ``Engineer`` and is also part of the table's full set of
columns.  Columns which are not mapped to ``Person`` are also excluded
from any other single or joined inheriting classes using the
``exclude_properties`` mapper argument.  Below, ``Manager`` will have
all the attributes of ``Person`` and ``Manager`` but *not* the
``primary_language`` attribute of ``Engineer``::

    class Manager(Person):
        __mapper_args__ = {'polymorphic_identity': 'manager'}
        golf_swing = Column(String(50))

The attribute exclusion logic is provided by the
``exclude_properties`` mapper argument, and declarative's default
behavior can be disabled by passing an explicit ``exclude_properties``
collection (empty or otherwise) to the ``__mapper_args__``.

Concrete Table Inheritance
~~~~~~~~~~~~~~~~~~~~~~~~~~

Concrete is defined as a subclass which has its own table and sets the
``concrete`` keyword argument to ``True``::

    class Person(Base):
        __tablename__ = 'people'
        id = Column(Integer, primary_key=True)
        name = Column(String(50))

    class Engineer(Person):
        __tablename__ = 'engineers'
        __mapper_args__ = {'concrete':True}
        id = Column(Integer, primary_key=True)
        primary_language = Column(String(50))
        name = Column(String(50))

Usage of an abstract base class is a little less straightforward as it
requires usage of :func:`~sqlalchemy.orm.util.polymorphic_union`::

    engineers = Table('engineers', Base.metadata,
                    Column('id', Integer, primary_key=True),
                    Column('name', String(50)),
                    Column('primary_language', String(50))
                )
    managers = Table('managers', Base.metadata,
                    Column('id', Integer, primary_key=True),
                    Column('name', String(50)),
                    Column('golf_swing', String(50))
                )

    punion = polymorphic_union({
        'engineer':engineers,
        'manager':managers
    }, 'type', 'punion')

    class Person(Base):
        __table__ = punion
        __mapper_args__ = {'polymorphic_on':punion.c.type}

    class Engineer(Person):
        __table__ = engineers
        __mapper_args__ = {'polymorphic_identity':'engineer', 'concrete':True}

    class Manager(Person):
        __table__ = managers
        __mapper_args__ = {'polymorphic_identity':'manager', 'concrete':True}


Mixin Classes
==============

A common need when using :mod:`~sqlalchemy.ext.declarative` is to
share some functionality, often a set of columns, across many
classes. The normal Python idiom would be to put this common code into
a base class and have all the other classes subclass this class.

When using :mod:`~sqlalchemy.ext.declarative`, this need is met by
using a "mixin class". A mixin class is one that isn't mapped to a
table and doesn't subclass the declarative :class:`.Base`. For example::

    class MyMixin(object):

        __table_args__ = {'mysql_engine': 'InnoDB'}
        __mapper_args__= {'always_refresh': True}

        id =  Column(Integer, primary_key=True)


    class MyModel(Base,MyMixin):
        __tablename__ = 'test'

        name = Column(String(1000))

Where above, the class ``MyModel`` will contain an "id" column
as well as ``__table_args__`` and ``__mapper_args__`` defined
by the ``MyMixin`` mixin class.

Mixing in Columns
~~~~~~~~~~~~~~~~~

The most basic way to specify a column on a mixin is by simple 
declaration::

    class TimestampMixin(object):
        created_at = Column(DateTime, default=func.now())

    class MyModel(Base, TimestampMixin):
        __tablename__ = 'test'

        id =  Column(Integer, primary_key=True)
        name = Column(String(1000))

Where above, all declarative classes that include ``TimestampMixin``
will also have a column ``created_at`` that applies a timestamp to 
all row insertions.

Those familiar with the SQLAlchemy expression language know that 
the object identity of clause elements defines their role in a schema.
Two ``Table`` objects ``a`` and ``b`` may both have a column called 
``id``, but the way these are differentiated is that ``a.c.id`` 
and ``b.c.id`` are two distinct Python objects, referencing their
parent tables ``a`` and ``b`` respectively.

In the case of the mixin column, it seems that only one
:class:`.Column` object is explicitly created, yet the ultimate 
``created_at`` column above must exist as a distinct Python object
for each separate destination class.  To accomplish this, the declarative
extension creates a **copy** of each :class:`.Column` object encountered on 
a class that is detected as a mixin.

This copy mechanism is limited to simple columns that have no foreign
keys, as a :class:`.ForeignKey` itself contains references to columns
which can't be properly recreated at this level.  For columns that 
have foreign keys, as well as for the variety of mapper-level constructs
that require destination-explicit context, the
:func:`~.declared_attr` decorator (renamed from ``sqlalchemy.util.classproperty`` in 0.6.5) 
is provided so that
patterns common to many classes can be defined as callables::

    from sqlalchemy.ext.declarative import declared_attr

    class ReferenceAddressMixin(object):
        @declared_attr
        def address_id(cls):
            return Column(Integer, ForeignKey('address.id'))

    class User(Base, ReferenceAddressMixin):
        __tablename__ = 'user'
        id = Column(Integer, primary_key=True)

Where above, the ``address_id`` class-level callable is executed at the 
point at which the ``User`` class is constructed, and the declarative
extension can use the resulting :class:`.Column` object as returned by
the method without the need to copy it.

Columns generated by :func:`~.declared_attr` can also be
referenced by ``__mapper_args__`` to a limited degree, currently 
by ``polymorphic_on`` and ``version_id_col``, by specifying the 
classdecorator itself into the dictionary - the declarative extension
will resolve them at class construction time::

    class MyMixin:
        @declared_attr
        def type_(cls):
            return Column(String(50))

        __mapper_args__= {'polymorphic_on':type_}

    class MyModel(Base,MyMixin):
        __tablename__='test'
        id =  Column(Integer, primary_key=True)

Mixing in Relationships
~~~~~~~~~~~~~~~~~~~~~~~

Relationships created by :func:`~sqlalchemy.orm.relationship` are provided
with declarative mixin classes exclusively using the
:func:`.declared_attr` approach, eliminating any ambiguity
which could arise when copying a relationship and its possibly column-bound
contents. Below is an example which combines a foreign key column and a
relationship so that two classes ``Foo`` and ``Bar`` can both be configured to
reference a common target class via many-to-one::

    class RefTargetMixin(object):
        @declared_attr
        def target_id(cls):
            return Column('target_id', ForeignKey('target.id'))

        @declared_attr
        def target(cls):
            return relationship("Target")

    class Foo(Base, RefTargetMixin):
        __tablename__ = 'foo'
        id = Column(Integer, primary_key=True)

    class Bar(Base, RefTargetMixin):
        __tablename__ = 'bar'
        id = Column(Integer, primary_key=True)

    class Target(Base):
        __tablename__ = 'target'
        id = Column(Integer, primary_key=True)

:func:`~sqlalchemy.orm.relationship` definitions which require explicit
primaryjoin, order_by etc. expressions should use the string forms 
for these arguments, so that they are evaluated as late as possible.
To reference the mixin class in these expressions, use the given ``cls``
to get it's name::

    class RefTargetMixin(object):
        @declared_attr
        def target_id(cls):
            return Column('target_id', ForeignKey('target.id'))

        @declared_attr
        def target(cls):
            return relationship("Target",
                primaryjoin="Target.id==%s.target_id" % cls.__name__
            )

Mixing in deferred(), column_property(), etc.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Like :func:`~sqlalchemy.orm.relationship`, all
:class:`~sqlalchemy.orm.interfaces.MapperProperty` subclasses such as
:func:`~sqlalchemy.orm.deferred`, :func:`~sqlalchemy.orm.column_property`,
etc. ultimately involve references to columns, and therefore, when 
used with declarative mixins, have the :func:`.declared_attr` 
requirement so that no reliance on copying is needed::

    class SomethingMixin(object):

        @declared_attr
        def dprop(cls):
            return deferred(Column(Integer))

    class Something(Base, SomethingMixin):
        __tablename__ = "something"


Controlling table inheritance with mixins
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The ``__tablename__`` attribute in conjunction with the hierarchy of
classes involved in a declarative mixin scenario controls what type of 
table inheritance, if any,
is configured by the declarative extension.

If the ``__tablename__`` is computed by a mixin, you may need to
control which classes get the computed attribute in order to get the
type of table inheritance you require.

For example, if you had a mixin that computes ``__tablename__`` but
where you wanted to use that mixin in a single table inheritance
hierarchy, you can explicitly specify ``__tablename__`` as ``None`` to
indicate that the class should not have a table mapped::

    from sqlalchemy.ext.declarative import declared_attr

    class Tablename:
        @declared_attr
        def __tablename__(cls):
            return cls.__name__.lower()

    class Person(Base,Tablename):
        id = Column(Integer, primary_key=True)
        discriminator = Column('type', String(50))
        __mapper_args__ = {'polymorphic_on': discriminator}

    class Engineer(Person):
        __tablename__ = None
        __mapper_args__ = {'polymorphic_identity': 'engineer'}
        primary_language = Column(String(50))

Alternatively, you can make the mixin intelligent enough to only
return a ``__tablename__`` in the event that no table is already
mapped in the inheritance hierarchy. To help with this, a
:func:`~sqlalchemy.ext.declarative.has_inherited_table` helper
function is provided that returns ``True`` if a parent class already
has a mapped table. 

As an example, here's a mixin that will only allow single table
inheritance::

    from sqlalchemy.ext.declarative import declared_attr
    from sqlalchemy.ext.declarative import has_inherited_table

    class Tablename:
        @declared_attr
        def __tablename__(cls):
            if has_inherited_table(cls):
                return None
            return cls.__name__.lower()

    class Person(Base,Tablename):
        id = Column(Integer, primary_key=True)
        discriminator = Column('type', String(50))
        __mapper_args__ = {'polymorphic_on': discriminator}

    class Engineer(Person):
        primary_language = Column(String(50))
        __mapper_args__ = {'polymorphic_identity': 'engineer'}

If you want to use a similar pattern with a mix of single and joined
table inheritance, you would need a slightly different mixin and use
it on any joined table child classes in addition to their parent
classes::

    from sqlalchemy.ext.declarative import declared_attr
    from sqlalchemy.ext.declarative import has_inherited_table

    class Tablename:
        @declared_attr
        def __tablename__(cls):
            if (has_inherited_table(cls) and
                Tablename not in cls.__bases__):
                return None
            return cls.__name__.lower()

    class Person(Base,Tablename):
        id = Column(Integer, primary_key=True)
        discriminator = Column('type', String(50))
        __mapper_args__ = {'polymorphic_on': discriminator}

    # This is single table inheritance
    class Engineer(Person):
        primary_language = Column(String(50))
        __mapper_args__ = {'polymorphic_identity': 'engineer'}

    # This is joined table inheritance
    class Manager(Person,Tablename):
        id = Column(Integer, ForeignKey('person.id'), primary_key=True)
        preferred_recreation = Column(String(50))
        __mapper_args__ = {'polymorphic_identity': 'engineer'}

Combining Table/Mapper Arguments from Multiple Mixins
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the case of ``__table_args__`` or ``__mapper_args__``
specified with declarative mixins, you may want to combine
some parameters from several mixins with those you wish to
define on the class iteself. The
:func:`.declared_attr` decorator can be used
here to create user-defined collation routines that pull
from multiple collections::

    from sqlalchemy.ext.declarative import declared_attr

    class MySQLSettings:
        __table_args__ = {'mysql_engine':'InnoDB'}

    class MyOtherMixin:
        __table_args__ = {'info':'foo'}

    class MyModel(Base,MySQLSettings,MyOtherMixin):
        __tablename__='my_model'

        @declared_attr
        def __table_args__(cls):
            args = dict()
            args.update(MySQLSettings.__table_args__)
            args.update(MyOtherMixin.__table_args__)
            return args

        id =  Column(Integer, primary_key=True)

Creating Indexes with Mixins
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To define a named, potentially multicolumn :class:`.Index` that applies to all 
tables derived from a mixin, use the "inline" form of :class:`.Index` and establish
it as part of ``__table_args__``::

    class MyMixin(object):
        a =  Column(Integer)
        b =  Column(Integer)

        @declared_attr
        def __table_args__(cls):
            return (Index('test_idx_%s' % cls.__tablename__, 'a', 'b'),)

    class MyModel(Base,MyMixin):
        __tablename__ = 'atable'
        c =  Column(Integer,primary_key=True)


Class Constructor
=================

As a convenience feature, the :func:`declarative_base` sets a default
constructor on classes which takes keyword arguments, and assigns them
to the named attributes::

    e = Engineer(primary_language='python')

Sessions
========

Note that ``declarative`` does nothing special with sessions, and is
only intended as an easier way to configure mappers and
:class:`~sqlalchemy.schema.Table` objects.  A typical application
setup using :func:`~sqlalchemy.orm.scoped_session` might look like::

    engine = create_engine('postgresql://scott:tiger@localhost/test')
    Session = scoped_session(sessionmaker(autocommit=False,
                                          autoflush=False,
                                          bind=engine))
    Base = declarative_base()

Mapped instances then make usage of
:class:`~sqlalchemy.orm.session.Session` in the usual way. 

"""

from sqlalchemy.schema import Table, Column, MetaData, _get_table_key
from sqlalchemy.orm import synonym as _orm_synonym, mapper,\
                                comparable_property, class_mapper
from sqlalchemy.orm.interfaces import MapperProperty
from sqlalchemy.orm.properties import RelationshipProperty, ColumnProperty, CompositeProperty
from sqlalchemy.orm.util import _is_mapped_class
from sqlalchemy import util, exc
from sqlalchemy.sql import util as sql_util, expression


__all__ = 'declarative_base', 'synonym_for', \
            'comparable_using', 'instrument_declarative'

def instrument_declarative(cls, registry, metadata):
    """Given a class, configure the class declaratively,
    using the given registry, which can be any dictionary, and
    MetaData object. 

    """
    if '_decl_class_registry' in cls.__dict__:
        raise exc.InvalidRequestError(
                            "Class %r already has been "
                            "instrumented declaratively" % cls)
    cls._decl_class_registry = registry
    cls.metadata = metadata
    _as_declarative(cls, cls.__name__, cls.__dict__)

def has_inherited_table(cls):
    """Given a class, return True if any of the classes it inherits from has a
    mapped table, otherwise return False.
    """
    for class_ in cls.__mro__:
        if getattr(class_,'__table__',None) is not None:
            return True
    return False

def _as_declarative(cls, classname, dict_):

    # dict_ will be a dictproxy, which we can't write to, and we need to!
    dict_ = dict(dict_)

    column_copies = {}
    potential_columns = {}

    mapper_args = {}
    table_args = inherited_table_args = None
    tablename = None
    parent_columns = ()

    declarative_props = (declared_attr, util.classproperty)

    for base in cls.__mro__:
        class_mapped = _is_mapped_class(base)
        if class_mapped:
            parent_columns = base.__table__.c.keys()

        for name,obj in vars(base).items():
            if name == '__mapper_args__':
                if not mapper_args and (
                                        not class_mapped or 
                                        isinstance(obj, declarative_props)
                                    ):
                    mapper_args = cls.__mapper_args__
            elif name == '__tablename__':
                if not tablename and (
                                        not class_mapped or 
                                        isinstance(obj, declarative_props)
                                    ):
                    tablename = cls.__tablename__
            elif name == '__table_args__':
                if not table_args and (
                                        not class_mapped or 
                                        isinstance(obj, declarative_props)
                                    ):
                    table_args = cls.__table_args__
                    if not isinstance(table_args, (tuple, dict, type(None))):
                        raise exc.ArgumentError(
                                "__table_args__ value must be a tuple, "
                                "dict, or None")
                    if base is not cls:
                        inherited_table_args = True
            elif class_mapped:
                continue
            elif base is not cls:
                # we're a mixin.

                if isinstance(obj, Column):
                    if obj.foreign_keys:
                        raise exc.InvalidRequestError(
                        "Columns with foreign keys to other columns "
                        "must be declared as @declared_attr callables "
                        "on declarative mixin classes. ")
                    if name not in dict_ and not (
                            '__table__' in dict_ and 
                            (obj.name or name) in dict_['__table__'].c
                            ) and name not in potential_columns:
                        potential_columns[name] = \
                                column_copies[obj] = \
                                obj.copy()
                        column_copies[obj]._creation_order = \
                                obj._creation_order
                elif isinstance(obj, MapperProperty):
                    raise exc.InvalidRequestError(
                        "Mapper properties (i.e. deferred,"
                        "column_property(), relationship(), etc.) must "
                        "be declared as @declared_attr callables "
                        "on declarative mixin classes.")
                elif isinstance(obj, declarative_props):
                    dict_[name] = ret = \
                            column_copies[obj] = getattr(cls, name)
                    if isinstance(ret, (Column, MapperProperty)) and \
                        ret.doc is None:
                        ret.doc = obj.__doc__

    # apply inherited columns as we should
    for k, v in potential_columns.items():
        if tablename or (v.name or k) not in parent_columns:
            dict_[k] = v

    if inherited_table_args and not tablename:
        table_args = None

    # make sure that column copies are used rather 
    # than the original columns from any mixins
    for k in ('version_id_col', 'polymorphic_on',):
        if k in mapper_args:
            v = mapper_args[k]
            mapper_args[k] = column_copies.get(v,v)

    if classname in cls._decl_class_registry:
        util.warn("The classname %r is already in the registry of this"
                  " declarative base, mapped to %r" % (
                classname,
                cls._decl_class_registry[classname]
                ))
    cls._decl_class_registry[classname] = cls
    our_stuff = util.OrderedDict()

    for k in dict_:
        value = dict_[k]
        if isinstance(value, declarative_props):
            value = getattr(cls, k)

        if (isinstance(value, tuple) and len(value) == 1 and
            isinstance(value[0], (Column, MapperProperty))):
            util.warn("Ignoring declarative-like tuple value of attribute "
                      "%s: possibly a copy-and-paste error with a comma "
                      "left at the end of the line?" % k)
            continue
        if not isinstance(value, (Column, MapperProperty)):
            continue
        if k == 'metadata':
            raise exc.InvalidRequestError(
                "Attribute name 'metadata' is reserved "
                "for the MetaData instance when using a "
                "declarative base class."
            )
        prop = _deferred_relationship(cls, value)
        our_stuff[k] = prop

    # set up attributes in the order they were created
    our_stuff.sort(key=lambda key: our_stuff[key]._creation_order)

    # extract columns from the class dict
    cols = set()
    for key, c in our_stuff.iteritems():
        if isinstance(c, (ColumnProperty, CompositeProperty)):
            for col in c.columns:
                if isinstance(col, Column) and \
                    col.table is None:
                    _undefer_column_name(key, col)
                    cols.add(col)
        elif isinstance(c, Column):
            _undefer_column_name(key, c)
            cols.add(c)
            # if the column is the same name as the key, 
            # remove it from the explicit properties dict.
            # the normal rules for assigning column-based properties
            # will take over, including precedence of columns
            # in multi-column ColumnProperties.
            if key == c.key:
                del our_stuff[key]
    cols = sorted(cols, key=lambda c:c._creation_order)

    table = None
    if '__table__' not in dict_:
        if tablename is not None:

            if isinstance(table_args, dict):
                args, table_kw = (), table_args
            elif isinstance(table_args, tuple):
                if isinstance(table_args[-1], dict):
                    args, table_kw = table_args[0:-1], table_args[-1]
                else:
                    args, table_kw = table_args, {}
            else:
                args, table_kw = (), {}

            autoload = dict_.get('__autoload__')
            if autoload:
                table_kw['autoload'] = True

            cls.__table__ = table = Table(tablename, cls.metadata,
                                          *(tuple(cols) + tuple(args)),
                                           **table_kw)
    else:
        table = cls.__table__
        if cols:
            for c in cols:
                if not table.c.contains_column(c):
                    raise exc.ArgumentError(
                        "Can't add additional column %r when "
                        "specifying __table__" % c.key
                    )

    if 'inherits' not in mapper_args:
        for c in cls.__bases__:
            if _is_mapped_class(c):
                mapper_args['inherits'] = cls._decl_class_registry.get(
                                                            c.__name__, None)
                break

    if hasattr(cls, '__mapper_cls__'):
        mapper_cls = util.unbound_method_to_callable(cls.__mapper_cls__)
    else:
        mapper_cls = mapper

    if table is None and 'inherits' not in mapper_args:
        raise exc.InvalidRequestError(
            "Class %r does not have a __table__ or __tablename__ "
            "specified and does not inherit from an existing "
            "table-mapped class." % cls
            )

    elif 'inherits' in mapper_args and not mapper_args.get('concrete', False):
        inherited_mapper = class_mapper(mapper_args['inherits'],
                                            compile=False)
        inherited_table = inherited_mapper.local_table

        if table is None:
            # single table inheritance.
            # ensure no table args
            if table_args:
                raise exc.ArgumentError(
                    "Can't place __table_args__ on an inherited class "
                    "with no table."
                    )

            # add any columns declared here to the inherited table.
            for c in cols:
                if c.primary_key:
                    raise exc.ArgumentError(
                        "Can't place primary key columns on an inherited "
                        "class with no table."
                        )
                if c.name in inherited_table.c:
                    raise exc.ArgumentError(
                        "Column '%s' on class %s conflicts with "
                        "existing column '%s'" % 
                        (c, cls, inherited_table.c[c.name])
                    )
                inherited_table.append_column(c)

        # single or joined inheritance
        # exclude any cols on the inherited table which are not mapped on the
        # parent class, to avoid
        # mapping columns specific to sibling/nephew classes
        inherited_mapper = class_mapper(mapper_args['inherits'],
                                            compile=False)
        inherited_table = inherited_mapper.local_table

        if 'exclude_properties' not in mapper_args:
            mapper_args['exclude_properties'] = exclude_properties = \
                set([c.key for c in inherited_table.c
                     if c not in inherited_mapper._columntoproperty])
            exclude_properties.difference_update([c.key for c in cols])

        # look through columns in the current mapper that 
        # are keyed to a propname different than the colname
        # (if names were the same, we'd have popped it out above,
        # in which case the mapper makes this combination).
        # See if the superclass has a similar column property.
        # If so, join them together.
        for k, col in our_stuff.items():
            if not isinstance(col, expression.ColumnElement):
                continue
            if k in inherited_mapper._props:
                p = inherited_mapper._props[k]
                if isinstance(p, ColumnProperty):
                    # note here we place the superclass column
                    # first.  this corresponds to the 
                    # append() in mapper._configure_property().
                    # change this ordering when we do [ticket:1892]
                    our_stuff[k] = p.columns + [col]


    cls.__mapper__ = mapper_cls(cls, 
                                table, 
                                properties=our_stuff, 
                                **mapper_args)

class DeclarativeMeta(type):
    def __init__(cls, classname, bases, dict_):
        if '_decl_class_registry' in cls.__dict__:
            return type.__init__(cls, classname, bases, dict_)

        _as_declarative(cls, classname, cls.__dict__)
        return type.__init__(cls, classname, bases, dict_)

    def __setattr__(cls, key, value):
        if '__mapper__' in cls.__dict__:
            if isinstance(value, Column):
                _undefer_column_name(key, value)
                cls.__table__.append_column(value)
                cls.__mapper__.add_property(key, value)
            elif isinstance(value, ColumnProperty):
                for col in value.columns:
                    if isinstance(col, Column) and col.table is None:
                        _undefer_column_name(key, col)
                        cls.__table__.append_column(col)
                cls.__mapper__.add_property(key, value)
            elif isinstance(value, MapperProperty):
                cls.__mapper__.add_property(
                                        key, 
                                        _deferred_relationship(cls, value)
                                )
            else:
                type.__setattr__(cls, key, value)
        else:
            type.__setattr__(cls, key, value)


class _GetColumns(object):
    def __init__(self, cls):
        self.cls = cls

    def __getattr__(self, key):
        mapper = class_mapper(self.cls, compile=False)
        if mapper:
            if not mapper.has_property(key):
                raise exc.InvalidRequestError(
                            "Class %r does not have a mapped column named %r"
                            % (self.cls, key))

            prop = mapper.get_property(key)
            if not isinstance(prop, ColumnProperty):
                raise exc.InvalidRequestError(
                            "Property %r is not an instance of"
                            " ColumnProperty (i.e. does not correspond"
                            " directly to a Column)." % key)
        return getattr(self.cls, key)

class _GetTable(object):
    def __init__(self, key, metadata):
        self.key = key
        self.metadata = metadata

    def __getattr__(self, key):
        return self.metadata.tables[
                _get_table_key(key, self.key)
            ]

def _deferred_relationship(cls, prop):
    def resolve_arg(arg):
        import sqlalchemy

        def access_cls(key):
            if key in cls._decl_class_registry:
                return _GetColumns(cls._decl_class_registry[key])
            elif key in cls.metadata.tables:
                return cls.metadata.tables[key]
            elif key in cls.metadata._schemas:
                return _GetTable(key, cls.metadata)
            else:
                return sqlalchemy.__dict__[key]

        d = util.PopulateDict(access_cls)
        def return_cls():
            try:
                x = eval(arg, globals(), d)

                if isinstance(x, _GetColumns):
                    return x.cls
                else:
                    return x
            except NameError, n:
                raise exc.InvalidRequestError(
                    "When initializing mapper %s, expression %r failed to "
                    "locate a name (%r). If this is a class name, consider "
                    "adding this relationship() to the %r class after "
                    "both dependent classes have been defined." % 
                    (prop.parent, arg, n.args[0], cls)
                )
        return return_cls

    if isinstance(prop, RelationshipProperty):
        for attr in ('argument', 'order_by', 'primaryjoin', 'secondaryjoin',
                     'secondary', '_user_defined_foreign_keys', 'remote_side'):
            v = getattr(prop, attr)
            if isinstance(v, basestring):
                setattr(prop, attr, resolve_arg(v))

        if prop.backref and isinstance(prop.backref, tuple):
            key, kwargs = prop.backref
            for attr in ('primaryjoin', 'secondaryjoin', 'secondary',
                         'foreign_keys', 'remote_side', 'order_by'):
               if attr in kwargs and isinstance(kwargs[attr], basestring):
                   kwargs[attr] = resolve_arg(kwargs[attr])


    return prop

def synonym_for(name, map_column=False):
    """Decorator, make a Python @property a query synonym for a column.

    A decorator version of :func:`~sqlalchemy.orm.synonym`. The function being
    decorated is the 'descriptor', otherwise passes its arguments through to
    synonym()::

      @synonym_for('col')
      @property
      def prop(self):
          return 'special sauce'

    The regular ``synonym()`` is also usable directly in a declarative setting
    and may be convenient for read/write properties::

      prop = synonym('col', descriptor=property(_read_prop, _write_prop))

    """
    def decorate(fn):
        return _orm_synonym(name, map_column=map_column, descriptor=fn)
    return decorate

def comparable_using(comparator_factory):
    """Decorator, allow a Python @property to be used in query criteria.

    This is a  decorator front end to
    :func:`~sqlalchemy.orm.comparable_property` that passes
    through the comparator_factory and the function being decorated::

      @comparable_using(MyComparatorType)
      @property
      def prop(self):
          return 'special sauce'

    The regular ``comparable_property()`` is also usable directly in a
    declarative setting and may be convenient for read/write properties::

      prop = comparable_property(MyComparatorType)

    """
    def decorate(fn):
        return comparable_property(comparator_factory, fn)
    return decorate

class declared_attr(property):
    """Mark a class-level method as representing the definition of
    a mapped property or special declarative member name.

    .. note:: @declared_attr is available as 
      ``sqlalchemy.util.classproperty`` for SQLAlchemy versions
      0.6.2, 0.6.3, 0.6.4.

    @declared_attr turns the attribute into a scalar-like
    property that can be invoked from the uninstantiated class.
    Declarative treats attributes specifically marked with 
    @declared_attr as returning a construct that is specific
    to mapping or declarative table configuration.  The name
    of the attribute is that of what the non-dynamic version
    of the attribute would be.

    @declared_attr is more often than not applicable to mixins,
    to define relationships that are to be applied to different
    implementors of the class::

        class ProvidesUser(object):
            "A mixin that adds a 'user' relationship to classes."

            @declared_attr
            def user(self):
                return relationship("User")

    It also can be applied to mapped classes, such as to provide
    a "polymorphic" scheme for inheritance::

        class Employee(Base):
            id = Column(Integer, primary_key=True)
            type = Column(String(50), nullable=False)

            @declared_attr
            def __tablename__(cls):
                return cls.__name__.lower()

            @declared_attr
            def __mapper_args__(cls):
                if cls.__name__ == 'Employee':
                    return {
                            "polymorphic_on":cls.type, 
                            "polymorphic_identity":"Employee"
                    }
                else:
                    return {"polymorphic_identity":cls.__name__}

    """

    def __init__(self, fget, *arg, **kw):
        super(declared_attr, self).__init__(fget, *arg, **kw)
        self.__doc__ = fget.__doc__

    def __get__(desc, self, cls):
        return desc.fget(cls)

def _declarative_constructor(self, **kwargs):
    """A simple constructor that allows initialization from kwargs.

    Sets attributes on the constructed instance using the names and
    values in ``kwargs``.

    Only keys that are present as
    attributes of the instance's class are allowed. These could be,
    for example, any mapped columns or relationships.
    """
    cls_ = type(self)
    for k in kwargs:
        if not hasattr(cls_, k):
            raise TypeError(
                "%r is an invalid keyword argument for %s" %
                (k, cls_.__name__))
        setattr(self, k, kwargs[k])
_declarative_constructor.__name__ = '__init__'

def declarative_base(bind=None, metadata=None, mapper=None, cls=object,
                     name='Base', constructor=_declarative_constructor,
                     metaclass=DeclarativeMeta):
    """Construct a base class for declarative class definitions.

    The new base class will be given a metaclass that produces
    appropriate :class:`~sqlalchemy.schema.Table` objects and makes
    the appropriate :func:`~sqlalchemy.orm.mapper` calls based on the
    information provided declaratively in the class and any subclasses
    of the class.

    :param bind: An optional
      :class:`~sqlalchemy.engine.base.Connectable`, will be assigned
      the ``bind`` attribute on the :class:`~sqlalchemy.MetaData` 
      instance. 

    :param metadata:
      An optional :class:`~sqlalchemy.MetaData` instance.  All
      :class:`~sqlalchemy.schema.Table` objects implicitly declared by
      subclasses of the base will share this MetaData.  A MetaData instance
      will be created if none is provided.  The
      :class:`~sqlalchemy.MetaData` instance will be available via the
      `metadata` attribute of the generated declarative base class.

    :param mapper:
      An optional callable, defaults to :func:`~sqlalchemy.orm.mapper`. Will
      be used to map subclasses to their Tables.

    :param cls:
      Defaults to :class:`object`. A type to use as the base for the generated
      declarative base class. May be a class or tuple of classes.

    :param name:
      Defaults to ``Base``.  The display name for the generated
      class.  Customizing this is not required, but can improve clarity in
      tracebacks and debugging.

    :param constructor:
      Defaults to
      :func:`~sqlalchemy.ext.declarative._declarative_constructor`, an
      __init__ implementation that assigns \**kwargs for declared
      fields and relationships to an instance.  If ``None`` is supplied,
      no __init__ will be provided and construction will fall back to
      cls.__init__ by way of the normal Python semantics.

    :param metaclass:
      Defaults to :class:`.DeclarativeMeta`.  A metaclass or __metaclass__
      compatible callable to use as the meta type of the generated
      declarative base class.

    """
    lcl_metadata = metadata or MetaData()
    if bind:
        lcl_metadata.bind = bind

    bases = not isinstance(cls, tuple) and (cls,) or cls
    class_dict = dict(_decl_class_registry=dict(),
                      metadata=lcl_metadata)

    if constructor:
        class_dict['__init__'] = constructor
    if mapper:
        class_dict['__mapper_cls__'] = mapper

    return metaclass(name, bases, class_dict)

def _undefer_column_name(key, column):
    if column.key is None:
        column.key = key
    if column.name is None:
        column.name = key