/usr/share/doc/python-sqlalchemy-doc/examples/join_conditions/threeway.py is in python-sqlalchemy-doc 0.9.8+dfsg-0.1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 | """Illustrate a "three way join" - where a primary table joins to a remote
table via an association table, but then the primary table also needs
to refer to some columns in the remote table directly.
E.g.::
first.first_id -> second.first_id
second.other_id --> partitioned.other_id
first.partition_key ---------------------> partitioned.partition_key
For a relationship like this, "second" is a lot like a "secondary" table,
but the mechanics aren't present within the "secondary" feature to allow
for the join directly between first and partitioned. Instead, we
will derive a selectable from partitioned and second combined together, then
link first to that derived selectable.
If we define the derived selectable as::
second JOIN partitioned ON second.other_id = partitioned.other_id
A JOIN from first to this derived selectable is then::
first JOIN (second JOIN partitioned
ON second.other_id = partitioned.other_id)
ON first.first_id = second.first_id AND
first.partition_key = partitioned.partition_key
We will use the "non primary mapper" feature in order to produce this.
A non primary mapper is essentially an "extra" :func:`.mapper` that we can
use to associate a particular class with some selectable that is
not its usual mapped table. It is used only when called upon within
a Query (or a :func:`.relationship`).
"""
from sqlalchemy import *
from sqlalchemy.orm import *
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
class First(Base):
__tablename__ = 'first'
first_id = Column(Integer, primary_key=True)
partition_key = Column(String)
def __repr__(self):
return ("First(%s, %s)" % (self.first_id, self.partition_key))
class Second(Base):
__tablename__ = 'second'
first_id = Column(Integer, primary_key=True)
other_id = Column(Integer, primary_key=True)
class Partitioned(Base):
__tablename__ = 'partitioned'
other_id = Column(Integer, primary_key=True)
partition_key = Column(String, primary_key=True)
def __repr__(self):
return ("Partitioned(%s, %s)" % (self.other_id, self.partition_key))
j = join(Partitioned, Second, Partitioned.other_id == Second.other_id)
partitioned_second = mapper(Partitioned, j, non_primary=True, properties={
# note we need to disambiguate columns here - the join()
# will provide them as j.c.<tablename>_<colname> for access,
# but they retain their real names in the mapping
"other_id": [j.c.partitioned_other_id, j.c.second_other_id],
})
First.partitioned = relationship(
partitioned_second,
primaryjoin=and_(
First.partition_key == partitioned_second.c.partition_key,
First.first_id == foreign(partitioned_second.c.first_id)
), innerjoin=True)
# when using any database other than SQLite, we will get a nested
# join, e.g. "first JOIN (partitioned JOIN second ON ..) ON ..".
# On SQLite, SQLAlchemy needs to render a full subquery.
e = create_engine("sqlite://", echo=True)
Base.metadata.create_all(e)
s = Session(e)
s.add_all([
First(first_id=1, partition_key='p1'),
First(first_id=2, partition_key='p1'),
First(first_id=3, partition_key='p2'),
Second(first_id=1, other_id=1),
Second(first_id=2, other_id=1),
Second(first_id=3, other_id=2),
Partitioned(partition_key='p1', other_id=1),
Partitioned(partition_key='p1', other_id=2),
Partitioned(partition_key='p2', other_id=2),
])
s.commit()
for row in s.query(First, Partitioned).join(First.partitioned):
print(row)
for f in s.query(First):
for p in f.partitioned:
print(f.partition_key, p.partition_key)
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