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
|
"""An advanced association proxy example which
illustrates nesting of association proxies to produce multi-level Python
collections, in this case a dictionary with string keys and sets of integers
as values, which conceal the underlying mapped classes.
This is a three table model which represents a parent table referencing a
dictionary of string keys and sets as values, where each set stores a
collection of integers. The association proxy extension is used to hide the
details of this persistence. The dictionary also generates new collections
upon access of a non-existent key, in the same manner as Python's
"collections.defaultdict" object.
"""
from __future__ import annotations
import operator
from typing import Mapping
from sqlalchemy import create_engine
from sqlalchemy import ForeignKey
from sqlalchemy import select
from sqlalchemy.ext.associationproxy import association_proxy
from sqlalchemy.ext.associationproxy import AssociationProxy
from sqlalchemy.orm import DeclarativeBase
from sqlalchemy.orm import Mapped
from sqlalchemy.orm import mapped_column
from sqlalchemy.orm import relationship
from sqlalchemy.orm import Session
from sqlalchemy.orm.collections import KeyFuncDict
class Base(DeclarativeBase):
id: Mapped[int] = mapped_column(primary_key=True)
class GenDefaultCollection(KeyFuncDict[str, "B"]):
def __missing__(self, key: str) -> B:
self[key] = b = B(key)
return b
class A(Base):
__tablename__ = "a"
associations: Mapped[Mapping[str, B]] = relationship(
"B",
collection_class=lambda: GenDefaultCollection(
operator.attrgetter("key")
),
)
collections: AssociationProxy[dict[str, set[int]]] = association_proxy(
"associations", "values"
)
"""Bridge the association from 'associations' over to the 'values'
association proxy of B.
"""
class B(Base):
__tablename__ = "b"
a_id: Mapped[int] = mapped_column(ForeignKey("a.id"))
elements: Mapped[set[C]] = relationship("C", collection_class=set)
key: Mapped[str]
values: AssociationProxy[set[int]] = association_proxy("elements", "value")
"""Bridge the association from 'elements' over to the
'value' element of C."""
def __init__(self, key: str, values: set[int] | None = None) -> None:
self.key = key
if values:
self.values = values
class C(Base):
__tablename__ = "c"
b_id: Mapped[int] = mapped_column(ForeignKey("b.id"))
value: Mapped[int]
def __init__(self, value: int) -> None:
self.value = value
if __name__ == "__main__":
engine = create_engine("sqlite://", echo=True)
Base.metadata.create_all(engine)
session = Session(engine)
# only "A" is referenced explicitly. Using "collections",
# we deal with a dict of key/sets of integers directly.
session.add_all([A(collections={"1": {1, 2, 3}})])
session.commit()
a1 = session.scalars(select(A)).one()
print(a1.collections["1"])
a1.collections["1"].add(4)
session.commit()
a1.collections["2"].update([7, 8, 9])
session.commit()
print(a1.collections["2"])
|
