Release: 1.4.44 | Release Date: November 12, 2022

# SQLAlchemy 1.4 Documentation

# Source code for examples.vertical.dictlike-polymorphic

    """Mapping a polymorphic-valued vertical table as a dictionary.

    Builds upon the dictlike.py example to also add differently typed
    columns to the "fact" table, e.g.::

      Table('properties', metadata
            Column('owner_id', Integer, ForeignKey('owner.id'),
                   primary_key=True),
            Column('key', UnicodeText),
            Column('type', Unicode(16)),
            Column('int_value', Integer),
            Column('char_value', UnicodeText),
            Column('bool_value', Boolean),
            Column('decimal_value', Numeric(10,2)))

    For any given properties row, the value of the 'type' column will point to the
    '_value' column active for that row.

    This example approach uses exactly the same dict mapping approach as the
    'dictlike' example.  It only differs in the mapping for vertical rows.  Here,
    we'll use a @hybrid_property to build a smart '.value' attribute that wraps up
    reading and writing those various '_value' columns and keeps the '.type' up to
    date.

    """

    from sqlalchemy import event
    from sqlalchemy import literal_column
    from sqlalchemy.ext.hybrid import hybrid_property
    from sqlalchemy.orm.interfaces import PropComparator
    from .dictlike import ProxiedDictMixin

    class PolymorphicVerticalProperty(object):
        """A key/value pair with polymorphic value storage.

        The class which is mapped should indicate typing information
        within the "info" dictionary of mapped Column objects; see
        the AnimalFact mapping below for an example.

        """

        def __init__(self, key, value=None):
            self.key = key
            self.value = value

        @hybrid_property
        def value(self):
            fieldname, discriminator = self.type_map[self.type]
            if fieldname is None:
                return None
            else:
                return getattr(self, fieldname)

        @value.setter
        def value(self, value):
            py_type = type(value)
            fieldname, discriminator = self.type_map[py_type]

            self.type = discriminator
            if fieldname is not None:
                setattr(self, fieldname, value)

        @value.deleter
        def value(self):
            self._set_value(None)

        @value.comparator
        class value(PropComparator):
            """A comparator for .value, builds a polymorphic comparison
            via CASE."""

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

            def _case(self):
                pairs = set(self.cls.type_map.values())
                whens = [
                    (
                        literal_column("'%s'" % discriminator),
                        cast(getattr(self.cls, attribute), String),
                    )
                    for attribute, discriminator in pairs
                    if attribute is not None
                ]
                return case(whens, value=self.cls.type, else_=null())

            def __eq__(self, other):
                return self._case() == cast(other, String)

            def __ne__(self, other):
                return self._case() != cast(other, String)

        def __repr__(self):
            return "<%s %r=%r>" % (self.__class__.__name__, self.key, self.value)

    @event.listens_for(
        PolymorphicVerticalProperty, "mapper_configured", propagate=True
    )
    def on_new_class(mapper, cls_):
        """Look for Column objects with type info in them, and work up
        a lookup table."""

        info_dict = {}
        info_dict[type(None)] = (None, "none")
        info_dict["none"] = (None, "none")

        for k in mapper.c.keys():
            col = mapper.c[k]
            if "type" in col.info:
                python_type, discriminator = col.info["type"]
                info_dict[python_type] = (k, discriminator)
                info_dict[discriminator] = (k, discriminator)
        cls_.type_map = info_dict

    if __name__ == "__main__":
        from sqlalchemy import (
            Column,
            Integer,
            Unicode,
            ForeignKey,
            UnicodeText,
            and_,
            or_,
            String,
            Boolean,
            cast,
            null,
            case,
            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(PolymorphicVerticalProperty, 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)
            type = Column(Unicode(16))

            # add information about storage for different types
            # in the info dictionary of Columns
            int_value = Column(Integer, info={"type": (int, "integer")})
            char_value = Column(UnicodeText, info={"type": (str, "string")})
            boolean_value = Column(Boolean, info={"type": (bool, "boolean")})

        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://", echo=True)

        Base.metadata.create_all(engine)
        session = Session(engine)

        stoat = Animal("stoat")
        stoat["color"] = "red"
        stoat["cuteness"] = 7
        stoat["weasel-like"] = True

        session.add(stoat)
        session.commit()

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

        print("changing cuteness value and type:")
        critter["cuteness"] = "very cute"

        session.commit()

        marten = Animal("marten")
        marten["cuteness"] = 5
        marten["weasel-like"] = True
        marten["poisonous"] = False
        session.add(marten)

        shrew = Animal("shrew")
        shrew["cuteness"] = 5
        shrew["weasel-like"] = False
        shrew["poisonous"] = True

        session.add(shrew)
        session.commit()

        q = session.query(Animal).filter(
            Animal.facts.any(
                and_(AnimalFact.key == "weasel-like", AnimalFact.value == True)
            )
        )
        print("weasel-like animals", q.all())

        q = session.query(Animal).filter(
            Animal.with_characteristic("weasel-like", True)
        )
        print("weasel-like animals again", q.all())

        q = session.query(Animal).filter(
            Animal.with_characteristic("poisonous", False)
        )
        print("animals with poisonous=False", q.all())

        q = session.query(Animal).filter(
            or_(
                Animal.with_characteristic("poisonous", False),
                ~Animal.facts.any(AnimalFact.key == "poisonous"),
            )
        )
        print("non-poisonous animals", q.all())

        q = session.query(Animal).filter(Animal.facts.any(AnimalFact.value == 5))
        print("any animal with a .value of 5", q.all())