Using PostgreSQL array to store many-to-many relationship - python

Suppose we have a PostgreSQL database with two tables A, B.
table A columns: id, name
table B columns: id, name, array_a
The column array_a in table B contains a variable length array of ids from table A. In SQLAlchemy we have two classes that model those tables, say class A and B.
The following works fine to get all the objects A that are referenced in an object B:
session.query(A).join(B, A.id == func.any(B.array_a)).filter(B.id == <id>).all()
How can we create a relationship in B referencing the objects A corresponding to the array? Tried column comparators using the func.any above but it complains that ANY(array_a) is not a column in the model. Specifying the primaryjoin conditions as above doesn't seem to cut it either.

This anti-pattern is called "Jaywalking"; and PostgreSQL's powerful type system makes it very tempting. you should be using another table:
CREATE TABLE table_a (
id SERIAL PRIMARY KEY,
name VARCHAR
);
CREATE TABLE table_b (
id SERIAL PRIMARY KEY,
name VARCHAR
);
CREATE TABLE a_b (
a_id INTEGER PRIMARY KEY REFERENCES table_a(id),
b_id INTEGER PRIMARY KEY REFERENCES table_b(id)
)
Which is mapped:
from sqlalchemy import *
from sqlalchemy.dialects import postgresql
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import *
Base = declarative_base()
a_b_table = Table("a_b", Base.metadata,
Column("a_id", Integer, ForeignKey("table_a.id"), primary_key=True),
Column("b_id", Integer, ForeignKey("table_b.id"), primary_key=True))
class A(Base):
__tablename__ = "table_a"
id = Column(Integer, primary_key=True)
name = Column(String)
class B(Base):
__tablename__ = "table_b"
id = Column(Integer, primary_key=True)
name = Column(String)
a_set = relationship(A, secondary=a_b_table, backref="b_set")
example:
>>> print Query(A).filter(A.b_set.any(B.name == "foo"))
SELECT table_a.id AS table_a_id, table_a.name AS table_a_name
FROM table_a
WHERE EXISTS (SELECT 1
FROM a_b, table_b
WHERE table_a.id = a_b.a_id AND table_b.id = a_b.b_id AND table_b.name = :name_1)
If you are stuck with the ARRAY column, your best bet is to use an alternate selectable that "looks" like a proper association table.
from sqlalchemy import *
from sqlalchemy.dialects import postgresql
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import *
Base = declarative_base()
class A(Base):
__tablename__ = "table_a"
id = Column(Integer, primary_key=True)
name = Column(String)
class B(Base):
__tablename__ = "table_b"
id = Column(Integer, primary_key=True)
name = Column(String)
array_a = Column(postgresql.ARRAY(Integer))
a_b_selectable = select([func.unnest(B.array_a).label("a_id"),
B.id.label("b_id")]).alias()
A.b_set = relationship(B, secondary=a_b_selectable,
primaryjoin=A.id == a_b_selectable.c.a_id,
secondaryjoin=a_b_selectable.c.b_id == B.id,
viewonly=True,)
B.a_set = relationship(A, secondary=a_b_selectable,
primaryjoin=A.id == a_b_selectable.c.a_id,
secondaryjoin=a_b_selectable.c.b_id == B.id,
viewonly=True)
which gives you:
>>> print Query(A).filter(A.b_set.any(B.name == "foo"))
SELECT table_a.id AS table_a_id, table_a.name AS table_a_name
FROM table_a
WHERE EXISTS (SELECT 1
FROM (SELECT unnest(table_b.array_a) AS a_id, table_b.id AS b_id
FROM table_b) AS anon_1, table_b
WHERE table_a.id = anon_1.a_id AND anon_1.b_id = table_b.id AND table_b.name = :name_1)
And obviously, since there's no real table there, viewonly=True is neccesary and you can't get the nice, dynamic objecty goodness you would if you had avoided jaywalking.

Or else simply you can join explicitly like below:
class A(Base):
__tablename__ = "table_a"
id = Column(Integer, primary_key=True)
name = Column(String)
class B(Base):
__tablename__ = "table_b"
id = Column(Integer, primary_key=True)
name = Column(String)
array_a = Column(postgresql.ARRAY(Integer))
a_ids= relationship('A',primaryjoin='A.id == any_(foreign(B.array_a))',uselist=True)

Related

SQLAlchemy Complex Polymorphic Mapping And Deep Table Inheritance

I have the following table structure (I have simplified it as much as possible, narrowed down the child/inheriting tables [there are additional] and removed all irrelevant columns from the provided tables):
## Base is my declarative_base
class AbstractQuestion(Base):
questionTypeId: Column = Column(
Integer, ForeignKey("luQuestionTypes.id"), index=True, nullable=False
)
__mapper_args__ = {
"polymorphic_identity": 0,
"polymorphic_on": questionTypeId,
}
class MultiChoiceQuestion(AbstractQuestion):
id: Column = Column(Integer, ForeignKey(AbstractQuestion.id), primary_key=True)
__mapper_args__ = {"polymorphic_identity": 1}
class AbstractSurveyQuestion(AbstractQuestion):
id: Column = Column(Integer, ForeignKey(AbstractQuestion.id), primary_key=True)
surveyQuestionTypeId: Column = Column(
Integer, ForeignKey("luSurveyQuestionTypes.id"), index=True, nullable=False
)
__mapper_args__ = {"polymorphic_identity": 2}
class RatingQuestion(AbstractSurveyQuestion):
id: Column = Column(
Integer, ForeignKey(AbstractSurveyQuestion.id), primary_key=True
)
The challenge I'm facing is, that I'm trying to make AbstractSurveyQuestion have two types of polymorphic mappings - one as a child of AbstractQuestion with a polymorphic_identity that matches the questionTypeId, but I also need it to have a separate polymorphic_on mapper for its own child table, which is RatingQuestion.
The closest thing I could find was this question, but it doesn't seem to be aiming at exactly what I'm looking for.
I also looked at the official docs about inheritance, but again couldn't find an accurate example to what I'm trying to achieve.
Can anyone please help me with this?
Thanks!
I posted the same question on SQLAlchemy's GitHub repo. Got this answer from the maintainer:
https://github.com/sqlalchemy/sqlalchemy/discussions/8089#discussioncomment-2878725
I'll paste the contents below as well:
it sounds like you are looking for mult-level polymorphic_on. We don't support that right now without workarounds, and that's #2555 which is a feature we're unlikely to implement, or if we did it would be a long time from now.
It looks like you are using joined inheritance....so...two ways. The more SQL efficient one is to have an extra "supplemetary" column on your base table that can discriminate for AbstractSurveyQuestion...because if you query for all the AbstractQuestion objects, by default it's just going to query that one table, and needs to know from each row if that row is in fact a RatingQuestion.
the more convoluted way is to use mapper-configured with_polymorphic so that all queries for AbstractQuestion include all the tables (or a subset of tables, can be configured, but at minimum you'd need to join out to AbstractSurveyQuestion) using a LEFT OUTER JOIN (or if you really wanted to go crazy it can be a UNION ALL).
the workarounds are a little ugly since it's not very easy to get a "composed" value out of two columns in SQL, but they are contained to the base classes. Below examples work on SQLite and might need tweaking for other databases.
Here's the discriminator on base table demo, a query here looks like:
SELECT aq.id AS aq_id, aq.d1 AS aq_d1, aq.d2 AS aq_d2, CAST(aq.d1 AS VARCHAR) || ? || CAST(coalesce(aq.d2, ?) AS VARCHAR) AS _sa_polymorphic_on
FROM aq
from typing import Tuple, Optional
from sqlalchemy import cast
from sqlalchemy import Column
from sqlalchemy import create_engine
from sqlalchemy import event
from sqlalchemy import ForeignKey
from sqlalchemy import inspect
from sqlalchemy import Integer, func
from sqlalchemy import String
from sqlalchemy.orm import declarative_base
from sqlalchemy.orm import Session
Base = declarative_base()
class ident_(str):
"""describe a composed identity.
Using a string for easy conversion to a string SQL composition.
"""
_tup: Tuple[int, Optional[int]]
def __new__(cls, d1, d2=None):
self = super().__new__(cls, f"{d1}, {d2 or ''}")
self._tup = d1, d2
return self
def _as_tuple(self):
return self._tup
class AbstractQuestion(Base):
__tablename__ = "aq"
id = Column(Integer, primary_key=True)
d1 = Column(
Integer, nullable=False
) # this can be your FK to the other table etc.
d2 = Column(
Integer, nullable=True
) # this is a "supplementary" discrim column
__mapper_args__ = {
"polymorphic_identity": ident_(0),
"polymorphic_on": cast(d1, String)
+ ", "
+ cast(func.coalesce(d2, ""), String),
}
#event.listens_for(AbstractQuestion, "init", propagate=True)
def _setup_poly(target, args, kw):
"""receive new AbstractQuestion objects when they are constructed and
set polymorphic identity"""
# this is the ident_() object
ident = inspect(target).mapper.polymorphic_identity
d1, d2 = ident._as_tuple()
kw["d1"] = d1
if d2:
kw["d2"] = d2
class MultiChoiceQuestion(AbstractQuestion):
__tablename__ = "mcq"
id: Column = Column(
Integer, ForeignKey(AbstractQuestion.id), primary_key=True
)
__mapper_args__ = {"polymorphic_identity": ident_(1)}
class AbstractSurveyQuestion(AbstractQuestion):
__tablename__ = "acq"
id: Column = Column(
Integer, ForeignKey(AbstractQuestion.id), primary_key=True
)
__mapper_args__ = {"polymorphic_identity": ident_(2)}
class RatingQuestion(AbstractSurveyQuestion):
__tablename__ = "rq"
id: Column = Column(
Integer, ForeignKey(AbstractSurveyQuestion.id), primary_key=True
)
__mapper_args__ = {"polymorphic_identity": ident_(2, 1)}
e = create_engine("sqlite://", echo=True)
Base.metadata.create_all(e)
s = Session(e)
s.add(MultiChoiceQuestion())
s.add(RatingQuestion())
s.commit()
s.close()
for q in s.query(AbstractQuestion):
print(q)
then there's the one that maintains your schema fully, a query here looks like:
SELECT aq.id AS aq_id, aq.d1 AS aq_d1, CAST(aq.d1 AS VARCHAR) || ? || CAST(coalesce(acq.d2, ?) AS VARCHAR) AS _sa_polymorphic_on, acq.id AS acq_id, acq.d2 AS acq_d2
FROM aq LEFT OUTER JOIN acq ON aq.id = acq.id
from typing import Tuple, Optional
from sqlalchemy import cast
from sqlalchemy import Column
from sqlalchemy import create_engine
from sqlalchemy import event
from sqlalchemy import ForeignKey
from sqlalchemy import func
from sqlalchemy import inspect
from sqlalchemy import Integer
from sqlalchemy import String
from sqlalchemy.orm import declarative_base
from sqlalchemy.orm import Session
Base = declarative_base()
class ident_(str):
"""describe a composed identity.
Using a string for easy conversion to a string SQL composition.
"""
_tup: Tuple[int, Optional[int]]
def __new__(cls, d1, d2=None):
self = super().__new__(cls, f"{d1}, {d2 or ''}")
self._tup = d1, d2
return self
def _as_tuple(self):
return self._tup
class AbstractQuestion(Base):
__tablename__ = "aq"
id = Column(Integer, primary_key=True)
d1 = Column(
Integer, nullable=False
) # this can be your FK to the other table etc.
__mapper_args__ = {
"polymorphic_identity": ident_(0),
}
#event.listens_for(AbstractQuestion, "init", propagate=True)
def _setup_poly(target, args, kw):
"""receive new AbstractQuestion objects when they are constructed and
set polymorphic identity"""
# this is the ident_() object
ident = inspect(target).mapper.polymorphic_identity
d1, d2 = ident._as_tuple()
kw["d1"] = d1
if d2:
kw["d2"] = d2
class MultiChoiceQuestion(AbstractQuestion):
__tablename__ = "mcq"
id: Column = Column(
Integer, ForeignKey(AbstractQuestion.id), primary_key=True
)
__mapper_args__ = {"polymorphic_identity": ident_(1)}
class AbstractSurveyQuestion(AbstractQuestion):
__tablename__ = "acq"
id: Column = Column(
Integer, ForeignKey(AbstractQuestion.id), primary_key=True
)
d2 = Column(Integer, nullable=False)
__mapper_args__ = {
"polymorphic_identity": ident_(2),
"polymorphic_load": "inline", # adds ASQ to all AQ queries
}
# after ASQ is set up, set the discriminator on the base class
# that includes ASQ column
inspect(AbstractQuestion)._set_polymorphic_on(
cast(AbstractQuestion.d1, String)
+ ", "
+ cast(func.coalesce(AbstractSurveyQuestion.d2, ""), String)
)
class RatingQuestion(AbstractSurveyQuestion):
__tablename__ = "rq"
id: Column = Column(
Integer, ForeignKey(AbstractSurveyQuestion.id), primary_key=True
)
__mapper_args__ = {"polymorphic_identity": ident_(2, 1)}
e = create_engine("sqlite://", echo=True)
Base.metadata.create_all(e)
s = Session(e)
s.add(MultiChoiceQuestion())
s.add(RatingQuestion())
s.commit()
s.close()
for q in s.query(AbstractQuestion):
print(q)

Is there a way to populate one table from multiple on SQLAlchemy

I'm trying to build a database with SQLAlchemy, my problem is that I have two tables with the same columns name and trying to populate a third table from the two others. There is below a simple diagram to illustrate:
I usually set Foreign key on one table and the relationship on the other like that :
class TableA(Base):
__tablename__ = "tableA"
id = Column(Integer, primary_key=True)
name = Column(String(100))
age = Column(Integer)
name_relation = relationship("TableC", backref='owner')
class TableC(Base):
__tablename__ = "tableC"
id = Column(Integer, primary_key=True)
name = Column(String(100), ForeignKey('tableA.name'))
age = Column(Integer)
You can see that this method can only works with two table because my ForeignKey on tableC for the name specifies the name of tableA.
Is there a way to do that ?
Thanks
In SQL, the query you'd be looking for is
INSERT INTO C (id, name, age) (
SELECT *
FROM A
UNION ALL
SELECT *
FROM B
)
As per this answer, this makes the equivalent SQLAlchemy
session = Session()
query = session.query(TableA).union_all(session.query(TableB))
stmt = TableC.insert().from_select(['id', 'name', 'age'], query)
or equivalently
stmt = TableC.insert().from_select(
['id', 'name', 'age'],
TableA.select().union_all(TableB.select())
)
After which you can execute it using connection.execute(stmt) or session.execute(stmt), depending on what you're using.

SQLAlchemy query not iterating over all results from a query

I'm experiencing some odd behavior with SQLAlchemy not iterating over all of the results from a query.
For example, I have the following python code:
engine = create_engine(<connection string>)
Session = sessionmaker(bind=engine)
session = Session()
columns = session.query(Column)
counter = 1
for c in columns
print(counter)
counter = counter + 1
print('count: ' + str(columns.count()))
where Column is a class that I've defined and mapped in the usual SQLAlchemy way:
from base import Base
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, Boolean
class Column(Base):
__tablename__ = 'COLUMNS'
__table_args__ = {'schema' : 'INFORMATION_SCHEMA'}
table_catalog = Column(String)
table_schema = Column(String)
table_name = Column(String)
column_name = Column(String, primary_key=True)
data_type = Column(String)
From my query, I'm expecting 7034 rows to be returned and this is what the final print statement prints out (for columns.count()), but the for loop only ever gets up to 2951 printing out counter.
If I do anything else with the returned data in the for loop, only the 2951 get processed, not all 7034.
Does anyone know why I'm experiencing this discrepancy, and how can I iterate over all 7034 rows, not just the 2951?
I've figured out why I wasn't getting the results I was expecting (I did something silly).
The 'column_name' field in the table the Column class maps to ins't unique, therefore picking it as a primary key filtered out only unique values - which since there are duplicates results in less rows being returned than I expected.
I fixed it by updating the definition of the Column mapping to:
from base import Base
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, Boolean
class Column(Base):
__tablename__ = 'COLUMNS'
__table_args__ = {'schema' : 'INFORMATION_SCHEMA'}
table_catalog = Column(String, primary_key=True)
table_schema = Column(String, primary_key=True)
table_name = Column(String, primary_key=True)
column_name = Column(String, primary_key=True)
data_type = Column(String)

Python/SQLAlchemy - Need to convert an inner join query with 3 tables into Python

I need some help converting this query into SQLAlchemy.
select field from table t1 join table t2 on t1.detail_id = t2.id join table t3 on t3.id = t2.rate_id where t2.name = 'fred' and t3.rate_type = 'Custom' and t3.description = 'Default';
I have been able to convert inner join queries with two tables, but need some help with this one.
Appreciate your help.TIA.
If simple SQL query is enough you can try:
session.execute("SELECT t1.field AS t1_field "
"FROM t1 JOIN t2 ON t1.detail_id = t2.id JOIN t3 ON t2.rate_id = t3.id "
"WHERE t2.name = :name AND t3.rate_type = :rate_type AND t3.description = :description",
{'name': 'fred', 'rate_type': 'Custom', 'description': 'Default'})
But if you want to use SQLAlchemy declarative base then the query would look like:
results = session.query(T1.field).join(T2, T1.detail_id == T2.id).join(T3, T2.rate_id == T3.id).\
filter(T2.name == 'fred').\
filter(T3.rate_type == 'custom').\
filter(T3.description == 'lorem ipsum').all()
For the following models:
from sqlalchemy import create_engine, Integer, ForeignKey, String, Column
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
class T1(Base):
__tablename__ = 't1'
id = Column(Integer, primary_key=True)
field = Column(String)
detail_id = Column(Integer, ForeignKey("t1.id"))
class T2(Base):
__tablename__ = 't2'
id = Column(Integer, primary_key=True)
name = Column(String)
rate_id = Column(Integer, ForeignKey("t1.id"))
class T3(Base):
__tablename__ = 't3'
id = Column(Integer, primary_key=True)
rate_type = Column(String)
description = Column(String)
I hope it helps.
SQLAlchemy provide both ORM way and SQL way to operate database. You can use exactly the raw SQL language (or SQLAlachemy SQL Express) to query.
(1) RAW SQL QUERY,Sample code:
engine = create_engine(...)
q = 'SELECT foo FROM t_bar WHERE col_name=:v_parameters'
rs = engine.execute(sqlalchemy.text(q), v_parameters=your_actual_value)
Check execute and basic usage. Also take look at ResultProxy to understand how to operate on returned result.
(2) ORM. If you want to use ORM, firstly you have to define models and mapper class. Sample Code.
from sqlalchemy import Column, ForeignKey
from sqlalchemy.types import String, Integer
from sqlalchemy.orm import relationship
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
class Father(Base):
id = Column(Integer, primary_key=True)
name = Column(String(31), unique=True, nullable=False)
# Relationship attributes
children = relationship('Sons',
passive_deletes=True,
back_populates='father')
class Son(Base):
id = Column(Integer, primary_key=True)
name = Column(String(31), unique=True, nullable=False)
# foreign keys
p_id = Column(Integer, ForeignKey('Father.id',
ondelete='CASCADE',
onupdate='CASCADE'))
# Relationship attributes
parent = relationship('Father',
passive_deletes=True,
back_populates='sons')
Then you can do ORM query operations
session.query(Father).join(Father.sons).filter(Son.name=='Sam')
is equal to SQL query
SELECT father.id, father.name FROM father JOIN son ON father.id=son.p_id WHERE son.name='Sam'.
Please check ORM mapper and ORM Query for more information.
For you application. If you have well mapped all of your tables, then you can use ORM way. If you do not need ORM feature, you can just use RAW SQL query.
Thank.

Sqlalchemy exists with joined inheritance and Firebird

I tried to use sqlaclhemy joined table inheritance and had a strange occurrence.
class CommonObject(Base):
__tablename__ = "objects"
id = Column("objid", Integer, primary_key=True)
objname = Column(String(32))
...
class GoodsPlacement(Container, Loadable, Dumpable):
__tablename__ = "goods_placements"
id = Column("objid", Integer, ForeignKey("containers.objid"), primary_key=True)
...
class Departure(CommonObject):
__tablename__ = "departures"
id = Column(Integer, ForeignKey("objects.objid"), primary_key=True)
content_id = Column(Integer, ForeignKey("goods_placements.objid"))
content = relationship("GoodsPlacement",
primaryjoin="Departure.content_id==GoodsPlacement.id",
foreign_keys=[content_id],
lazy='joined',
backref="departures")
...
When I write query:
session.query(GoodsPlacement).filter(~GoodsPlacement.departures.any(Departure.status_id < 2))
it generates me something like this:
SELECT
objects.objid AS objects_objid,
goods_placements.objid AS goods_placements_objid,
objects.objname AS objects_objname
FROM objects
JOIN goods_placements ON objects.objid = goods_placements.objid
WHERE NOT (EXISTS (
SELECT 1
FROM (
SELECT
objects.objid AS objects_objid,
objects.objname AS objects_objname,
departures.id AS departures_id,
departures.content_id AS departures_content_id,
departures.status_id AS departures_status_id
FROM objects
JOIN departures ON objects.objid = departures.id)
AS anon_1, objects
WHERE anon_1.departures_content_id = objects.objid
AND anon_1.departures_status_id < :status_id_1)
)
And this doesn't work because objects in exist clause overrides outer objects.
As workaround I used exists from sqlexpression directly,
session.query(GoodsPlacement).filter(~exists([1],
and_("departures.status_id<2",
"departures.content_id=goods_placements.objid"),
from_obj="departures"))
but it strongly depends from column and table names.
How I can specify alias for object table in exists statement?
Debian wheezy, python-2.7.3rc2, sqlaclhemy 0.7.7-1
there's a bug involving the declarative system in how it sets up columns. The "objid" name you're giving the columns, distinct from the "id" attribute name, is the source of the issue here. The below test case approximates your above system and shows a workaround until the bug is fixed:
from sqlalchemy import *
from sqlalchemy.orm import *
from sqlalchemy.ext.declarative import declarative_base
Base= declarative_base()
class CommonObject(Base):
__tablename__ = "objects"
id = Column("objid", Integer, primary_key=True)
objname = Column(String(32))
class Container(CommonObject):
__tablename__ = 'containers'
id = Column("objid", Integer, ForeignKey("objects.objid"), primary_key=True)
class GoodsPlacement(Container):
__tablename__ = "goods_placements"
id = Column("objid", Integer, ForeignKey("containers.objid"), primary_key=True)
class Departure(CommonObject):
__tablename__ = "departures"
id = Column(Integer, ForeignKey("objects.objid"), primary_key=True)
content_id = Column(Integer, ForeignKey("goods_placements.objid"))
status_id = Column(Integer)
content = relationship("GoodsPlacement",
primaryjoin=lambda:Departure.__table__.c.content_id==GoodsPlacement.__table__.c.objid,
backref="departures"
)
session = Session()
print session.query(GoodsPlacement).filter(~GoodsPlacement.departures.any(Departure.status_id < 2))
output:
SELECT objects.objid AS objects_objid, containers.objid AS containers_objid, goods_placements.objid AS goods_placements_objid, objects.objname AS objects_objname
FROM objects JOIN containers ON objects.objid = containers.objid JOIN goods_placements ON containers.objid = goods_placements.objid
WHERE NOT (EXISTS (SELECT 1
FROM (SELECT objects.objid AS objects_objid, objects.objname AS objects_objname, departures.id AS departures_id, departures.content_id AS departures_content_id, departures.status_id AS departures_status_id
FROM objects JOIN departures ON objects.objid = departures.id) AS anon_1
WHERE anon_1.departures_content_id = goods_placements.objid AND anon_1.departures_status_id < :status_id_1))

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