examples.vertical.dictlike-polymorphic 的源代码

"""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 and_
from sqlalchemy import Boolean
from sqlalchemy import case
from sqlalchemy import cast
from sqlalchemy import Column
from sqlalchemy import create_engine
from sqlalchemy import event
from sqlalchemy import ForeignKey
from sqlalchemy import Integer
from sqlalchemy import literal_column
from sqlalchemy import null
from sqlalchemy import or_
from sqlalchemy import String
from sqlalchemy import Unicode
from sqlalchemy import UnicodeText
from sqlalchemy.ext.associationproxy import association_proxy
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.ext.hybrid import hybrid_property
from sqlalchemy.orm import relationship
from sqlalchemy.orm import Session
from sqlalchemy.orm.collections import attribute_keyed_dict
from sqlalchemy.orm.interfaces import PropComparator
from .dictlike import ProxiedDictMixin


class PolymorphicVerticalProperty:
    """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__":
    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_keyed_dict("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())