/SQLAlchemy-0.7.8/lib/sqlalchemy/ext/declarative.py

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# ext/declarative.py
# Copyright (C) 2005-2012 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)

Like other :func:`.relationship` arguments, a string is accepted as well, 
passing the string name of the table as defined in the ``Base.metadata.tables``
collection::

    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
========================

See :ref:`mapper_sql_expressions` for examples on declaratively
mapping attributes to SQL expressions.

.. _declarative_table_args:

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 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. 

Note that when the ``__table__`` approach is used, the object is immediately
usable as a plain :class:`.Table` within the class declaration body itself,
as a Python class is only another syntactical block.  Below this is illustrated
by using the ``id`` column in the ``primaryjoin`` condition of a :func:`.relationship`::

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

        widgets = relationship(Widget, 
                    primaryjoin=Widget.myclass_id==__table__.c.id)

Similarly, mapped attributes which refer to ``__table__`` can be placed inline, 
as below where we assign the ``name`` column to the attribute ``_name``, generating
a synonym for ``name``::

    from sqlalchemy.ext.declarative import synonym_for
    
    class MyClass(Base):
        __table__ = Table('my_table', Base.metadata,
            Column('id', Integer, primary_key=True),
            Column('name', String(50))
        )

        _name = __table__.c.name

        @synonym_for("_name")
        def name(self):
            return "Name: %s" % _name

Using Reflection with Declarative
=================================

It's easy to set up a :class:`.Table` that uses ``autoload=True``
in conjunction with a mapped class::

    class MyClass(Base):
        __table__ = Table('mytable', Base.metadata, 
                        autoload=True, autoload_with=some_engine)

However, one improvement that can be made here is to not 
require the :class:`.Engine` to be available when classes are 
being first declared.   To achieve this, use the example
described at :ref:`examples_declarative_reflection` to build a 
declarative base that sets up mappings only after a special 
``prepare(engine)`` step is called::

    Base = declarative_base(cls=DeclarativeReflectedBase)

    class Foo(Base):
        __tablename__ = 'foo'
        bars = relationship("Bar")

    class Bar(Base):
        __tablename__ = 'bar'

        # illustrate overriding of "bar.foo_id" to have 
        # a foreign key constraint otherwise not
        # reflected, such as when using MySQL
        foo_id = Column(Integer, ForeignKey('foo.id'))

    Base.prepare(e)

        
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`,
which needs to be created with the :class:`.Table` objects
before the class is built::

    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}

.. _declarative_concrete_helpers:

Using the Concrete Helpers
^^^^^^^^^^^^^^^^^^^^^^^^^^^

Helper classes provides a simpler pattern for concrete inheritance.
With these objects, the ``__declare_last__`` helper is used to configure the "polymorphic"
loader for the mapper after all subclasses have been declared.

.. versionadded:: 0.7.3

An abstract base can be declared using the :class:`.AbstractConcreteBase` class::

    from sqlalchemy.ext.declarative import AbstractConcreteBase
    
    class Employee(AbstractConcreteBase, Base):
        pass

To have a concrete ``employee`` table, use :class:`.ConcreteBase` instead::

    from sqlalchemy.ext.declarative import ConcreteBase
    
    class Employee(ConcreteBase, Base):
        __tablename__ = 'employee'
        employee_id = Column(Integer, primary_key=True)
        name = Column(String(50))
        __mapper_args__ = {
                        'polymorphic_identity':'employee', 
                        'concrete':True}
    

Either ``Employee`` base can be used in the normal fashion::

    class Manager(Employee):
        __tablename__ = 'manager'
        employee_id = Column(Integer, primary_key=True)
        name = Column(String(50))
        manager_data = Column(String(40))
        __mapper_args__ = {
                        'polymorphic_identity':'manager', 
                        'concrete':True}

    class Engineer(Employee):
        __tablename__ = 'engineer'
        employee_id = Column(Integer, primary_key=True)
        name = Column(String(50))
        engineer_info = Column(String(40))
        __mapper_args__ = {'polymorphic_identity':'engineer', 
                        'concrete':True}


.. _declarative_mixins:

Mixin and Custom Base Classes
==============================

A common need when using :mod:`~sqlalchemy.ext.declarative` is to
share some functionality, such as a set of common columns, some common
table options, or other mapped properties, across many
classes.  The standard Python idioms for this is to have the classes
inherit from a base which includes these common features.

When using :mod:`~sqlalchemy.ext.declarative`, this idiom is allowed
via the usage of a custom declarative base class, as well as a "mixin" class
which is inherited from in addition to the primary base.  Declarative
includes several helper features to make this work in terms of how
mappings are declared.   An example of some commonly mixed-in
idioms is below::

    from sqlalchemy.ext.declarative import declared_attr
    
    class MyMixin(object):

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

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

        id =  Column(Integer, primary_key=True)

    class MyModel(MyMixin, Base):
        name = Column(String(1000))

Where above, the class ``MyModel`` will contain an "id" column
as the primary key, a ``__tablename__`` attribute that derives
from the name of the class itself, as well as ``__table_args__`` 
and ``__mapper_args__`` defined by the ``MyMixin`` mixin class.

There's no fixed convention over whether ``MyMixin`` precedes 
``Base`` or not.  Normal Python method resolution rules apply, and 
the above example would work just as well with::

    class MyModel(Base, MyMixin):
        name = Column(String(1000))

This works because ``Base`` here doesn't define any of the 
variables that ``MyMixin`` defines, i.e. ``__tablename__``, 
``__table_args__``, ``id``, etc.   If the ``Base`` did define 
an attribute of the same name, the class placed first in the 
inherits list would determine which attribute is used on the 
newly defined class.

Augmenting the Base
~~~~~~~~~~~~~~~~~~~

In addition to using a pure mixin, most of the techniques in this 
section can also be applied to the base class itself, for patterns that
should apply to all classes derived from a particular base.  This 
is achieved using the ``cls`` argument of the :func:`.declarative_base` function::

    from sqlalchemy.ext.declarative import declared_attr

    class Base(object):
        @declared_attr
        def __tablename__(cls):
            return cls.__name__.lower()
            
        __table_args__ = {'mysql_engine': 'InnoDB'}

        id =  Column(Integer, primary_key=True)

    from sqlalchemy.ext.declarative import declarative_base
    
    Base = declarative_base(cls=Base)

    class MyModel(Base):
        name = Column(String(1000))

Where above, ``MyModel`` and all other classes that derive from ``Base`` will have 
a table name derived from the class name, an ``id`` primary key column, as well as 
the "InnoDB" engine for MySQL.

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(TimestampMixin, Base):
        __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 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(ReferenceAddressMixin, Base):
        __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.

.. versionchanged:: > 0.6.5
    Rename 0.6.5 ``sqlalchemy.util.classproperty`` into :func:`~.declared_attr`.

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(MyMixin, Base):
        __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(RefTargetMixin, Base):
        __tablename__ = 'foo'
        id = Column(Integer, primary_key=True)

    class Bar(RefTargetMixin, Base):
        __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(SomethingMixin, Base):
        __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(Tablename, Base):
        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(object):
        @declared_attr
        def __tablename__(cls):
            if has_inherited_table(cls):
                return None
            return cls.__name__.lower()

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

    class Person(Tablename, Base):
        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(Tablename, Person):
        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(object):
        __table_args__ = {'mysql_engine':'InnoDB'}

    class MyOtherMixin(object):
        __table_args__ = {'info':'foo'}

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

Special Directives
==================

``__declare_last__()``
~~~~~~~~~~~~~~~~~~~~~~

The ``__declare_last__()`` hook allows definition of 
a class level function that is automatically called by the :meth:`.MapperEvents.after_configured`
event, which occurs after mappings are assumed to be completed and the 'configure' step
has finished::

    class MyClass(Base):
        @classmethod
        def __declare_last__(cls):
            ""
            # do something with mappings

.. versionadded:: 0.7.3

.. _declarative_abstract:

``__abstract__``
~~~~~~~~~~~~~~~~~~~

``__abstract__`` causes declarative to skip the production
of a table or mapper for the class entirely.  A class can be added within a hierarchy
in the same way as mixin (see :ref:`declarative_mixins`), allowing subclasses to extend
just from the special class::

    class SomeAbstractBase(Base):
        __abstract__ = True
        
        def some_helpful_method(self):
            ""
            
        @declared_attr
        def __mapper_args__(cls):
            return {"helpful mapper arguments":True}

    class MyMappedClass(SomeAbstractBase):
        ""
        
One possible use of ``__abstract__`` is to use a distinct :class:`.MetaData` for different
bases::

    Base = declarative_base()

    class DefaultBase(Base):
        __abstract__ = True
        metadata = MetaData()

    class OtherBase(Base):
        __abstract__ = True
        metadata = MetaData()

Above, classes which inherit from ``DefaultBase`` will use one :class:`.MetaData` as the 
registry of tables, and those which inherit from ``OtherBase`` will use a different one.  
The tables themselves can then be created perhaps within distinct databases::

    DefaultBase.metadata.create_all(some_engine)
    OtherBase.metadata_create_all(some_other_engine)

.. versionadded:: 0.7.3

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
from sqlalchemy import event
from sqlalchemy.orm.util import polymorphic_union, _mapper_or_none


__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__:
        _is_declarative_inherits = hasattr(base, '_decl_class_registry')

        if '__declare_last__' in base.__dict__:
            @event.listens_for(mapper, "after_configured")
            def go():
                cls.__declare_last__()
        if '__abstract__' in base.__dict__:
            if (base is cls or 
                (base in cls.__bases__ and not _is_declarative_inherits)
            ):
                return

        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:
                if isinstance(obj, declarative_props):
                    util.warn("Regular (i.e. not __special__) "
                            "attribute '%s.%s' uses @declared_attr, "
                            "but owning class %s is mapped - "
                            "not applying to subclass %s." 
                            % (base.__name__, name, base, cls))
                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 hasattr(cls, '__table_cls__'):
        table_cls = util.unbound_method_to_callable(cls.__table_cls__)
    else:
        table_cls = Table

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

            args, table_kw = (), {}
            if table_args:
                if isinstance(table_args, dict):
                    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_args

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

            cls.__table__ = table = table_cls(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'] = c
                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 subclass column
                    # first.  See [ticket:1892] for background.
                    our_stuff[k] = [col] + p.columns


    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_)
        else:
            _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, C…