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1e278de4cc
Applied on top of a pure run of black -l 79 in I7eda77fed3d8e73df84b3651fd6cfcfe858d4dc9, this set of changes resolves all remaining flake8 conditions for those codes we have enabled in setup.cfg. Included are resolutions for all remaining flake8 issues including shadowed builtins, long lines, import order, unused imports, duplicate imports, and docstring issues. Change-Id: I4f72d3ba1380dd601610ff80b8fb06a2aff8b0fe
248 lines
7.0 KiB
Python
248 lines
7.0 KiB
Python
"""Mapping a polymorphic-valued vertical table as a dictionary.
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Builds upon the dictlike.py example to also add differently typed
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columns to the "fact" table, e.g.::
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Table('properties', metadata
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Column('owner_id', Integer, ForeignKey('owner.id'),
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primary_key=True),
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Column('key', UnicodeText),
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Column('type', Unicode(16)),
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Column('int_value', Integer),
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Column('char_value', UnicodeText),
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Column('bool_value', Boolean),
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Column('decimal_value', Numeric(10,2)))
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For any given properties row, the value of the 'type' column will point to the
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'_value' column active for that row.
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This example approach uses exactly the same dict mapping approach as the
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'dictlike' example. It only differs in the mapping for vertical rows. Here,
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we'll use a @hybrid_property to build a smart '.value' attribute that wraps up
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reading and writing those various '_value' columns and keeps the '.type' up to
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date.
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"""
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from sqlalchemy import event
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from sqlalchemy import literal_column
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from sqlalchemy.ext.hybrid import hybrid_property
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from sqlalchemy.orm.interfaces import PropComparator
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from .dictlike import ProxiedDictMixin
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class PolymorphicVerticalProperty(object):
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"""A key/value pair with polymorphic value storage.
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The class which is mapped should indicate typing information
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within the "info" dictionary of mapped Column objects; see
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the AnimalFact mapping below for an example.
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"""
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def __init__(self, key, value=None):
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self.key = key
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self.value = value
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@hybrid_property
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def value(self):
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fieldname, discriminator = self.type_map[self.type]
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if fieldname is None:
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return None
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else:
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return getattr(self, fieldname)
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@value.setter
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def value(self, value):
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py_type = type(value)
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fieldname, discriminator = self.type_map[py_type]
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self.type = discriminator
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if fieldname is not None:
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setattr(self, fieldname, value)
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@value.deleter
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def value(self):
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self._set_value(None)
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@value.comparator
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class value(PropComparator):
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"""A comparator for .value, builds a polymorphic comparison via CASE.
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"""
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def __init__(self, cls):
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self.cls = cls
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def _case(self):
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pairs = set(self.cls.type_map.values())
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whens = [
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(
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literal_column("'%s'" % discriminator),
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cast(getattr(self.cls, attribute), String),
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)
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for attribute, discriminator in pairs
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if attribute is not None
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]
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return case(whens, self.cls.type, null())
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def __eq__(self, other):
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return self._case() == cast(other, String)
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def __ne__(self, other):
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return self._case() != cast(other, String)
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def __repr__(self):
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return "<%s %r=%r>" % (self.__class__.__name__, self.key, self.value)
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@event.listens_for(
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PolymorphicVerticalProperty, "mapper_configured", propagate=True
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)
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def on_new_class(mapper, cls_):
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"""Look for Column objects with type info in them, and work up
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a lookup table."""
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info_dict = {}
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info_dict[type(None)] = (None, "none")
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info_dict["none"] = (None, "none")
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for k in mapper.c.keys():
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col = mapper.c[k]
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if "type" in col.info:
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python_type, discriminator = col.info["type"]
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info_dict[python_type] = (k, discriminator)
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info_dict[discriminator] = (k, discriminator)
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cls_.type_map = info_dict
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if __name__ == "__main__":
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from sqlalchemy import (
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Column,
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Integer,
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Unicode,
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ForeignKey,
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UnicodeText,
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and_,
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or_,
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String,
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Boolean,
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cast,
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null,
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case,
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create_engine,
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)
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from sqlalchemy.orm import relationship, Session
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from sqlalchemy.orm.collections import attribute_mapped_collection
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from sqlalchemy.ext.declarative import declarative_base
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from sqlalchemy.ext.associationproxy import association_proxy
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Base = declarative_base()
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class AnimalFact(PolymorphicVerticalProperty, Base):
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"""A fact about an animal."""
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__tablename__ = "animal_fact"
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animal_id = Column(ForeignKey("animal.id"), primary_key=True)
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key = Column(Unicode(64), primary_key=True)
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type = Column(Unicode(16))
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# add information about storage for different types
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# in the info dictionary of Columns
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int_value = Column(Integer, info={"type": (int, "integer")})
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char_value = Column(UnicodeText, info={"type": (str, "string")})
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boolean_value = Column(Boolean, info={"type": (bool, "boolean")})
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class Animal(ProxiedDictMixin, Base):
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"""an Animal"""
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__tablename__ = "animal"
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id = Column(Integer, primary_key=True)
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name = Column(Unicode(100))
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facts = relationship(
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"AnimalFact", collection_class=attribute_mapped_collection("key")
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)
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_proxied = association_proxy(
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"facts",
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"value",
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creator=lambda key, value: AnimalFact(key=key, value=value),
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)
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def __init__(self, name):
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self.name = name
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def __repr__(self):
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return "Animal(%r)" % self.name
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@classmethod
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def with_characteristic(self, key, value):
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return self.facts.any(key=key, value=value)
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engine = create_engine("sqlite://", echo=True)
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Base.metadata.create_all(engine)
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session = Session(engine)
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stoat = Animal("stoat")
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stoat["color"] = "red"
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stoat["cuteness"] = 7
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stoat["weasel-like"] = True
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session.add(stoat)
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session.commit()
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critter = session.query(Animal).filter(Animal.name == "stoat").one()
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print(critter["color"])
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print(critter["cuteness"])
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print("changing cuteness value and type:")
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critter["cuteness"] = "very cute"
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session.commit()
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marten = Animal("marten")
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marten["cuteness"] = 5
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marten["weasel-like"] = True
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marten["poisonous"] = False
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session.add(marten)
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shrew = Animal("shrew")
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shrew["cuteness"] = 5
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shrew["weasel-like"] = False
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shrew["poisonous"] = True
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session.add(shrew)
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session.commit()
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q = session.query(Animal).filter(
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Animal.facts.any(
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and_(AnimalFact.key == "weasel-like", AnimalFact.value == True)
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)
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)
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print("weasel-like animals", q.all())
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q = session.query(Animal).filter(
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Animal.with_characteristic("weasel-like", True)
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)
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print("weasel-like animals again", q.all())
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q = session.query(Animal).filter(
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Animal.with_characteristic("poisonous", False)
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)
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print("animals with poisonous=False", q.all())
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q = session.query(Animal).filter(
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or_(
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Animal.with_characteristic("poisonous", False),
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~Animal.facts.any(AnimalFact.key == "poisonous"),
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)
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)
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print("non-poisonous animals", q.all())
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q = session.query(Animal).filter(Animal.facts.any(AnimalFact.value == 5))
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print("any animal with a .value of 5", q.all())
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