"""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, self.cls.type, 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())