# SQLAlchemy 0.9 Documentation

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Release: 0.9.3 | Release Date: February 19, 2014

# Source code for examples.vertical.dictlike

    """Mapping a vertical table as a dictionary.

    This example illustrates accessing and modifying a "vertical" (or
    "properties", or pivoted) table via a dict-like interface.  These are tables
    that store free-form object properties as rows instead of columns.  For
    example, instead of::

      # A regular ("horizontal") table has columns for 'species' and 'size'
      Table('animal', metadata,
            Column('id', Integer, primary_key=True),
            Column('species', Unicode),
            Column('size', Unicode))

    A vertical table models this as two tables: one table for the base or parent
    entity, and another related table holding key/value pairs::

      Table('animal', metadata,
            Column('id', Integer, primary_key=True))

      # The properties table will have one row for a 'species' value, and
      # another row for the 'size' value.
      Table('properties', metadata
            Column('animal_id', Integer, ForeignKey('animal.id'),
                   primary_key=True),
            Column('key', UnicodeText),
            Column('value', UnicodeText))

    Because the key/value pairs in a vertical scheme are not fixed in advance,
    accessing them like a Python dict can be very convenient.  The example below
    can be used with many common vertical schemas as-is or with minor adaptations.

    """
    from __future__ import unicode_literals

    class ProxiedDictMixin(object):
        """Adds obj[key] access to a mapped class.

        This class basically proxies dictionary access to an attribute
        called ``_proxied``.  The class which inherits this class
        should have an attribute called ``_proxied`` which points to a dictionary.

        """

        def __len__(self):
            return len(self._proxied)

        def __iter__(self):
            return iter(self._proxied)

        def __getitem__(self, key):
            return self._proxied[key]

        def __contains__(self, key):
            return key in self._proxied

        def __setitem__(self, key, value):
            self._proxied[key] = value

        def __delitem__(self, key):
            del self._proxied[key]

    if __name__ == '__main__':
        from sqlalchemy import (Column, Integer, Unicode,
            ForeignKey, UnicodeText, and_, create_engine)
        from sqlalchemy.orm import relationship, Session
        from sqlalchemy.orm.collections import attribute_mapped_collection
        from sqlalchemy.ext.declarative import declarative_base
        from sqlalchemy.ext.associationproxy import association_proxy

        Base = declarative_base()

        class AnimalFact(Base):
            """A fact about an animal."""

            __tablename__ = 'animal_fact'

            animal_id = Column(ForeignKey('animal.id'), primary_key=True)
            key = Column(Unicode(64), primary_key=True)
            value = Column(UnicodeText)

        class Animal(ProxiedDictMixin, Base):
            """an Animal"""

            __tablename__ = 'animal'

            id = Column(Integer, primary_key=True)
            name = Column(Unicode(100))

            facts = relationship("AnimalFact",
                        collection_class=attribute_mapped_collection('key'))

            _proxied = association_proxy("facts", "value",
                                creator=
                                lambda key, value: AnimalFact(key=key, value=value))

            def __init__(self, name):
                self.name = name

            def __repr__(self):
                return "Animal(%r)" % self.name

            @classmethod
            def with_characteristic(self, key, value):
                return self.facts.any(key=key, value=value)

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

        session = Session(bind=engine)

        stoat = Animal('stoat')
        stoat['color'] = 'reddish'
        stoat['cuteness'] = 'somewhat'

        # dict-like assignment transparently creates entries in the
        # stoat.facts collection:
        print(stoat.facts['color'])

        session.add(stoat)
        session.commit()

        critter = session.query(Animal).filter(Animal.name == 'stoat').one()
        print(critter['color'])
        print(critter['cuteness'])

        critter['cuteness'] = 'very'

        print('changing cuteness:')

        marten = Animal('marten')
        marten['color'] = 'brown'
        marten['cuteness'] = 'somewhat'
        session.add(marten)

        shrew = Animal('shrew')
        shrew['cuteness'] = 'somewhat'
        shrew['poisonous-part'] = 'saliva'
        session.add(shrew)

        loris = Animal('slow loris')
        loris['cuteness'] = 'fairly'
        loris['poisonous-part'] = 'elbows'
        session.add(loris)

        q = (session.query(Animal).
             filter(Animal.facts.any(
               and_(AnimalFact.key == 'color',
                    AnimalFact.value == 'reddish'))))
        print('reddish animals', q.all())

        q = session.query(Animal).\
                filter(Animal.with_characteristic("color", 'brown'))
        print('brown animals', q.all())

        q = session.query(Animal).\
               filter(~Animal.with_characteristic("poisonous-part", 'elbows'))
        print('animals without poisonous-part == elbows', q.all())

        q = (session.query(Animal).
             filter(Animal.facts.any(value='somewhat')))
        print('any animal with any .value of "somewhat"', q.all())