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This is a straight reformat run using black as is, with no edits applied at all. The black run will format code consistently, however in some cases that are prevalent in SQLAlchemy code it produces too-long lines. The too-long lines will be resolved in the following commit that will resolve all remaining flake8 issues including shadowed builtins, long lines, import order, unused imports, duplicate imports, and docstring issues. Change-Id: I7eda77fed3d8e73df84b3651fd6cfcfe858d4dc9
176 lines
4.9 KiB
Python
176 lines
4.9 KiB
Python
"""Mapping a vertical table as a dictionary.
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This example illustrates accessing and modifying a "vertical" (or
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"properties", or pivoted) table via a dict-like interface. These are tables
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that store free-form object properties as rows instead of columns. For
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example, instead of::
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# A regular ("horizontal") table has columns for 'species' and 'size'
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Table('animal', metadata,
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Column('id', Integer, primary_key=True),
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Column('species', Unicode),
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Column('size', Unicode))
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A vertical table models this as two tables: one table for the base or parent
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entity, and another related table holding key/value pairs::
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Table('animal', metadata,
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Column('id', Integer, primary_key=True))
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# The properties table will have one row for a 'species' value, and
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# another row for the 'size' value.
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Table('properties', metadata
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Column('animal_id', Integer, ForeignKey('animal.id'),
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primary_key=True),
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Column('key', UnicodeText),
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Column('value', UnicodeText))
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Because the key/value pairs in a vertical scheme are not fixed in advance,
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accessing them like a Python dict can be very convenient. The example below
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can be used with many common vertical schemas as-is or with minor adaptations.
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"""
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from __future__ import unicode_literals
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class ProxiedDictMixin(object):
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"""Adds obj[key] access to a mapped class.
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This class basically proxies dictionary access to an attribute
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called ``_proxied``. The class which inherits this class
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should have an attribute called ``_proxied`` which points to a dictionary.
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"""
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def __len__(self):
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return len(self._proxied)
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def __iter__(self):
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return iter(self._proxied)
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def __getitem__(self, key):
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return self._proxied[key]
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def __contains__(self, key):
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return key in self._proxied
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def __setitem__(self, key, value):
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self._proxied[key] = value
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def __delitem__(self, key):
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del self._proxied[key]
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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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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(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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value = Column(UnicodeText)
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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://")
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Base.metadata.create_all(engine)
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session = Session(bind=engine)
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stoat = Animal("stoat")
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stoat["color"] = "reddish"
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stoat["cuteness"] = "somewhat"
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# dict-like assignment transparently creates entries in the
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# stoat.facts collection:
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print(stoat.facts["color"])
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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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critter["cuteness"] = "very"
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print("changing cuteness:")
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marten = Animal("marten")
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marten["color"] = "brown"
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marten["cuteness"] = "somewhat"
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session.add(marten)
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shrew = Animal("shrew")
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shrew["cuteness"] = "somewhat"
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shrew["poisonous-part"] = "saliva"
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session.add(shrew)
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loris = Animal("slow loris")
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loris["cuteness"] = "fairly"
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loris["poisonous-part"] = "elbows"
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session.add(loris)
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q = session.query(Animal).filter(
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Animal.facts.any(
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and_(AnimalFact.key == "color", AnimalFact.value == "reddish")
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)
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)
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print("reddish animals", q.all())
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q = session.query(Animal).filter(
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Animal.with_characteristic("color", "brown")
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)
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print("brown animals", q.all())
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q = session.query(Animal).filter(
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~Animal.with_characteristic("poisonous-part", "elbows")
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)
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print("animals without poisonous-part == elbows", q.all())
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q = session.query(Animal).filter(Animal.facts.any(value="somewhat"))
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print('any animal with any .value of "somewhat"', q.all())
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