examples.vertical.dictlike-polymorphic
优质
小牛编辑
135浏览
2023-12-01
"""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())