"""A simple declarative layer for SQLAlchemy ORM. SQLAlchemy object-relational configuration involves the usage of Table, mapper(), and class objects to define the three areas of configuration. declarative moves these three types of configuration underneath the individual mapped class. Regular SQLAlchemy schema and ORM constructs are used in most cases:: from sqlalchemy.ext.declarative import declarative_base engine = create_engine('sqlite://') Base = declarative_base(engine) class SomeClass(Base): __tablename__ = 'some_table' id = Column('id', Integer, primary_key=True) name = Column('name', String(50)) Above, the ``declarative_base`` callable produces a new base class from which all mapped classes inherit from. When the class definition is completed, a new ``Table`` and ``mapper()`` have been generated, accessible via the ``__table__`` and ``__mapper__`` attributes on the ``SomeClass`` class. You may omit the names from the Column definitions. Declarative will fill them in for you. class SomeClass(Base): __tablename__ = 'some_table' id = Column(Integer, primary_key=True) name = Column(String(50)) Attributes may be added to the class after its construction, and they will be added to the underlying ``Table`` and ``mapper()`` definitions as appropriate:: SomeClass.data = Column('data', Unicode) SomeClass.related = relation(RelatedInfo) Classes which are mapped explicitly using ``mapper()`` can interact freely with declarative classes. The ``declarative_base`` base class contains a ``MetaData`` object as well as a dictionary of all classes created against the base. So to access the above metadata and create tables we can say:: Base.metadata.create_all() The ``declarative_base`` can also receive a pre-created ``MetaData`` object:: mymetadata = MetaData() Base = declarative_base(metadata=mymetadata) Relations to other classes are done in the usual way, with the added feature that the class specified to ``relation()`` 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 = relation("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 = relation(User, primaryjoin=user_id==User.id) Synonyms are one area where ``declarative`` needs to slightly change the usual SQLAlchemy configurational syntax. To define a getter/setter which proxies to an underlying attribute, use ``synonym`` with the ``descriptor`` argument:: class MyClass(Base): __tablename__ = 'sometable' _attr = Column('attr', String) def _get_attr(self): return self._some_attr def _set_attr(self, attr) self._some_attr = attr attr = synonym('_attr', descriptor=property(_get_attr, _set_attr)) The above synonym is then usable as an instance attribute as well as a class-level expression construct:: x = MyClass() x.attr = "some value" session.query(MyClass).filter(MyClass.attr == 'some other value').all() As an alternative to ``__tablename__``, a direct ``Table`` construct may be used:: class MyClass(Base): __table__ = Table('my_table', Base.metadata, Column(Integer, primary_key=True), Column(String(50)) ) This is the preferred approach when using reflected tables, as below:: class MyClass(Base): __table__ = Table('my_table', Base.metadata, autoload=True) Mapper arguments are specified using the ``__mapper_args__`` class variable. Note that the column objects declared on the class are immediately usable, as in this joined-table inheritance example:: class Person(Base): __tablename__ = 'people' id = Column(Integer, primary_key=True) discriminator = Column(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)) For single-table inheritance, the ``__tablename__`` and ``__table__`` class variables are optional on a class when the class inherits from another mapped class. As a convenience feature, the ``declarative_base()`` sets a default constructor on classes which takes keyword arguments, and assigns them to the named attributes:: e = Engineer(primary_language='python') Note that ``declarative`` has no integration built in with sessions, and is only intended as an optional syntax for the regular usage of mappers and Table objects. A typical application setup using ``scoped_session`` might look like:: engine = create_engine('postgres://scott:tiger@localhost/test') Session = scoped_session(sessionmaker(transactional=True, autoflush=False, bind=engine)) Base = declarative_base() Mapped instances then make usage of ``Session`` in the usual way. """ from sqlalchemy.schema import Table, SchemaItem, Column, MetaData from sqlalchemy.orm import synonym as _orm_synonym, mapper, comparable_property from sqlalchemy.orm.interfaces import MapperProperty from sqlalchemy.orm.properties import PropertyLoader, ColumnProperty from sqlalchemy import util, exceptions import types __all__ = ['declarative_base', 'synonym_for', 'comparable_using', 'declared_synonym'] class DeclarativeMeta(type): def __init__(cls, classname, bases, dict_): if '_decl_class_registry' in cls.__dict__: return type.__init__(cls, classname, bases, dict_) cls._decl_class_registry[classname] = cls our_stuff = util.OrderedDict() for k in dict_: value = dict_[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 prop = _deferred_relation(cls, value) our_stuff[k] = prop table = None if '__table__' not in cls.__dict__: if '__tablename__' in cls.__dict__: tablename = cls.__tablename__ autoload = cls.__dict__.get('__autoload__') if autoload: table_kw = {'autoload': True} else: table_kw = {} cols = [] for key, c in our_stuff.iteritems(): if isinstance(c, ColumnProperty): for col in c.columns: if isinstance(col, Column) and col.table is None: _undefer_column_name(key, col) cols.append(col) elif isinstance(c, Column): _undefer_column_name(key, c) cols.append(c) cls.__table__ = table = Table(tablename, cls.metadata, *cols, **table_kw) else: table = cls.__table__ mapper_args = getattr(cls, '__mapper_args__', {}) if 'inherits' not in mapper_args: inherits = cls.__mro__[1] inherits = cls._decl_class_registry.get(inherits.__name__, None) mapper_args['inherits'] = inherits if hasattr(cls, '__mapper_cls__'): mapper_cls = util.unbound_method_to_callable(cls.__mapper_cls__) else: mapper_cls = mapper cls.__mapper__ = mapper_cls(cls, table, properties=our_stuff, **mapper_args) 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, MapperProperty): cls.__mapper__.add_property(key, _deferred_relation(cls, value)) else: type.__setattr__(cls, key, value) else: type.__setattr__(cls, key, value) def _deferred_relation(cls, prop): if isinstance(prop, PropertyLoader) and isinstance(prop.argument, basestring): arg = prop.argument def return_cls(): try: return cls._decl_class_registry[arg] except KeyError: raise exceptions.InvalidRequestError("When compiling mapper %s, could not locate a declarative class named %r. Consider adding this property to the %r class after both dependent classes have been defined." % (prop.parent, arg, prop.parent.class_)) prop.argument = return_cls return prop def declared_synonym(prop, name): """Deprecated. Use synonym(name, descriptor=prop).""" return _orm_synonym(name, descriptor=prop) declared_synonym = util.deprecated(None, False)(declared_synonym) def synonym_for(name, map_column=False): """Decorator, make a Python @property a query synonym for a column. A decorator version of [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. A decorator front end to [sqlalchemy.orm#comparable_property()], passes throgh 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 def declarative_base(engine=None, metadata=None, mapper=None): lcl_metadata = metadata or MetaData() if engine: lcl_metadata.bind = engine class Base(object): __metaclass__ = DeclarativeMeta metadata = lcl_metadata if mapper: __mapper_cls__ = mapper _decl_class_registry = {} def __init__(self, **kwargs): for k in kwargs: if not hasattr(type(self), k): raise TypeError('%r is an invalid keyword argument for %s' % (k, type(self).__name__)) setattr(self, k, kwargs[k]) return Base def _undefer_column_name(key, column): if column.key is None: column.key = key if column.name is None: column.name = key