SQLAlchemy: Disable lazy loading and load object only on join() - python

I'm working on disabling lazy loading on SQLAlchemy, so it will not load by default all the objects when fetching the records from the database. I'm trying to load for example the user object only from the event object when you specifically join it on the query or if you access it for example event.user. Is this possible somehow with a parameter or is it a bad practice to disabling lazy loading?
I already tried the noload("*") but it disables any join at the end.
For example I have the below model and also the queries which I'm doing my tests.
# Event model
class Event(Base):
__tablename__ = 'events'
id = Column(Integer, primary_key=True, autoincrement=True)
name = Column(String(50), nullable=False)
amount = Column(Integer)
_user_id = Column("user_id", Integer, ForeignKey("users.id"), nullable=False)
user = relationship(User)
# Query - This fetches also the whole user object <-- I don't want such behavior
some_session.query(Event).all()
# Query - I would like to load the user object when I will use the join() if possible
some_session.query(Event).join(Event.user).all()

The default relationship loading strategy is "lazy loading", which works the way you want; the related User is loaded only if the user attribute of an Event object is touched. In your case it is touched by your IDE, when it inspects the object in order to display the attributes as a handy tree, and that triggers the fetch. The same happens easily with custom __repr__() implementations, if not careful.
When you wish to eager load the related users using a join, either use joined loading:
some_session.query(Event).options(joinedload(Event.user)).all()
or if you wish to filter based on User in the same query, explicit join(s) and contains_eager():
some_session.query(Event).join(Event.user).options(contains_eager(Event.user)).all()

Related

How to use the order_by defined on the relationship in SQLAlchemy and contains_eager?

The Zen of Joined Eager Loading docs recommends using contains_eager() if we want to keep the relationship order defined in the model.
"If we wanted to use just one JOIN for collection loading as well as ordering, we use the contains_eager() option, described in Routing Explicit Joins/Statements into Eagerly Loaded Collections below."
But the following example seems to behave otherwise. I must be missing something, but unsure what.
class Parent(Base):
__tablename__ = "parent"
parent_id = Column(types.Integer, primary_key=True)
name = Column(types.String(200), nullable=False)
class Child(Base):
__tablename__ = "child"
order = Column(types.Integer, default=0)
name = Column(types.String(200))
parent_id = Column(types.Integer, ForeignKey(Parent.parent_id))
parent = relationship(
Parent,
backref=backref(
"children",
cascade="all,delete",
order_by="Child.order",
),
)
query = session.query(Parent).options(
contains_eager(Parent.children)
).filter(Parent.parent_id == 99).filter(Child.name == "foo")
Generates the following SQL:
SELECT parent.parent_id, parent.name,
child.order, child.name,
FROM parent, child
WHERE parent.parent_id = 99 AND parent.name = 'foo'
For some reason,
ORDER BY child.order
is missing, even though it's defined in the relationship(). Any hints?
It works fine if the order_by is specified at query time, but I want to avoid writing the same ordering criteria multiple times.
The documentation is correct, and it refers to the fact that if using most out-of-the box eager loading methods, the query is modified and might not be optimal.
The suggestion is then to use contains_eager where:
1) the user is responsible for constructing the correct query (including joins, filters, ordering etc)
2) by using contains_eager the user hints SA that the specified relationship is included in the query.
The way to load relationship eagerly would be to use joinedload:
q_joined = (
session
.query(Parent)
.options(joinedload(Parent.children))
.filter(Parent.parent_id == parent_id)
)
But you cannot apply these additional filters in this case.
Using the contains_eager you would do:
q_manual = (
session
.query(Parent)
.join(Child) # MUST HAVE THIS
.options(contains_eager(Parent.children))
.filter(Parent.parent_id == 99)
# .filter(Child.name == "foo") # you can add this, but you are "tricking" SA into believing that only these 'Child' are part of the Parent.children relationship.
.order_by(Parent.parent_id, Child.order) # JUST ADD THIS to solve the ordering
)

filter nested children sqlalchemy to arbitrary depth

I have a complex model. Let's say it contains 100 entities, all of which are related to each other in some way. Some are many to many, some are one to one, some are many to one, and so on.
These entities all have start and end timestamps indicating valid time ranges. When loading these entities via query, I wish to populate the relationship fields only with entities that have start and end stamps wrapping a given timestamp: for example datetime.now(), or yesterday, or whenever.
I'll define two models here for example, but assume there are a vast number of others:
class User(base):
__tablename__ = 'User'
class Role(base):
__tablename__ = 'Role'
user_id = Column(Integer, ForeignKey('User.uid'))
user = relationship(User, backref=backref('Role')
start = Column(DateTime, default=func.current_timestamp())
end = Column(DateTime))
Now, I want to return entities via restful endpoints in flask. So, a get might look something like this in flask:
def get(self, uid=None) -> Tuple[Dict, int]:
query = User.query
if uid:
query.filter_by(uid=uid)
return create_response(
query.all()
200
)
Now, I want to restrict the Role entities returned as children to the User returned by the above query. Obviously, this could easily be done by just extending the query to filter the Roles. The problem comes when this scales up. Consider 100 nested levels of child relationships. Now consider restful endpoints providing a get for any one of them. It would be practically impossible to write out a query to properly filter every different level of child.
My desired solution was to define loading behavior on each entity, making everything composable. For example:
class User(base):
__tablename__ = 'User'
role = relationship("Role",
primaryjoin="and_(Role.start<={desired_timestamp} "
"Role.end>={desired_timestamp})")
The problem, of course, is that we don't know our desired_timestamp at class definition time as it is passed at runtime. I have thought of some hacks for this such as redefining everything during every runtime, but I'm not happy with them. Does anyone have some insight as to the "right" way to do something like this?

Why I need both relationship and foreign key for Many to One relationship?

In the docs for SQLAlchemy for Many to One relationships it shows the following example:
class Parent(Base):
__tablename__ = 'parent'
id = Column(Integer, primary_key=True)
child_id = Column(Integer, ForeignKey('child.id'))
child = relationship("Child")
class Child(Base):
__tablename__ = 'child'
id = Column(Integer, primary_key=True)
Many parents for a single child. Then, when if we create a Parent, we need to populate child_id and child, which seems kind of redundant? Is this mandatory, or what's the purpose of each thing?
child = Child()
Parent(child_id=child, child=child)
Also, in Flask-SQLAlchemy, there is this example for a simple relationship in which it creates a post like this:
Post(title='Hello Python!', body='Python is pretty cool', category=py)
without providing a category_id. If I replicate that scenario, category_id value is None.
For the purpose of creating new objects like Parent(child=child), would it be enough to add foreign_keys=[child_id] or does it have further implications?
It is not mandatory; you do not need to populate both. Setting the foreign key to the related instance can be an error waiting to manifest itself. The only thing you need to do is
child = Child()
parent = Parent(child=child)
After this parent.child_id is None, but they represent the object part of ORM just fine. parent.child is a reference to the created child. They have not been persisted to the database and have no identity, other than their Python object ID. Only when you add them to a Session and flush the changes to the database do they receive an identity, due to them using generated surrogate keys. Here is where the mapping from the object world to the relational world happens. SQLAlchemy automatically fills in parent.child_id, so that their relationship is recorded in the database as well (note that this is not what "relational" in relational model means).
Returning to the example, adding some printing helps keep track of what happens and when:
child = Child()
parent = Parent(child=child)
print(parent.child_id) # None
session.add(parent)
session.flush() # Send changes held in session to DB
print(parent.child_id) # The ID assigned to child
You can also reverse the situation: you might have the ID of an existing Child, but not the actual object. In that case you can simply assign child_id yourself.
So, to answer the title: you do not need the ORM relationship in order to have a DB foreign key relationship, but you can use it to map the DB relationship to the object world.

Generic query in SQLAlchemy

I have following code:
class ArchaeologicalRecord(Base, ObservableMixin, ConcurrentMixin):
author_id = Column(Integer, ForeignKey('authors.id'))
author = relationship('Author', backref=backref('record'))
horizont_id = Column(Integer, ForeignKey('horizonts.id'))
horizont = relationship('Horizont', backref=backref('record'))
.....
somefield_id = Column(Integer, ForeignKey('somefields.id'))
somefield = relationship('SomeModel', backref=backref('record'))
At the moment I have one of entry (Author or Horizont or any other entry which related to arch.record). And I want to ensure that no one record has reference to this field. But I hate to write a lot of code for each case and want to do it most common way.
So, actually I have:
instance of ArchaeologicalRecord
instance of child entity, for example, Horizont
(from previous) it's class definition.
How to check whether any ArchaeologicalRecord contains (or does not) reference to Horizont (or any other child entity) without writing great chunk of copy-pasted code?
Are you asking how to find orphaned authors, horzonts, somefields etc?
Assuming all your relations are many-to-one (ArchaelogicalRecord-to-Author), you could try something like:
from sqlalchemy.orm.properties import RelationshipProperty
from sqlalchemy.orm import class_mapper
session = ... # However you setup the session
# ArchaelogicalRecord will have various properties defined,
# some of these are RelationshipProperties, which hold the info you want
for rp in class_mapper(ArchaeologicalRecord).iterate_properties:
if not isinstance(rp, RelationshipProperty):
continue
query = session.query(rp.mapper.class_)\
.filter(~getattr(rp.mapper.class_, rp.backref[0]).any())
orphans = query.all()
if orphans:
# Do something...
print rp.mapper.class_
print orphans
This will fail when rp.backref is None (i.e. where you've defined a relationship without a backref) - in this case you'd probably have to construct the query a bit more manually, but the RelationshipProperty, and it's .mapper and .mapper.class_ attributes should get you all the info you need to do this in a generic way.

SQLAlchemy: cascade delete

I must be missing something trivial with SQLAlchemy's cascade options because I cannot get a simple cascade delete to operate correctly -- if a parent element is a deleted, the children persist, with null foreign keys.
I've put a concise test case here:
from sqlalchemy import Column, Integer, ForeignKey
from sqlalchemy.orm import relationship
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
class Parent(Base):
__tablename__ = "parent"
id = Column(Integer, primary_key = True)
class Child(Base):
__tablename__ = "child"
id = Column(Integer, primary_key = True)
parentid = Column(Integer, ForeignKey(Parent.id))
parent = relationship(Parent, cascade = "all,delete", backref = "children")
engine = create_engine("sqlite:///:memory:")
Base.metadata.create_all(engine)
Session = sessionmaker(bind=engine)
session = Session()
parent = Parent()
parent.children.append(Child())
parent.children.append(Child())
parent.children.append(Child())
session.add(parent)
session.commit()
print "Before delete, children = {0}".format(session.query(Child).count())
print "Before delete, parent = {0}".format(session.query(Parent).count())
session.delete(parent)
session.commit()
print "After delete, children = {0}".format(session.query(Child).count())
print "After delete parent = {0}".format(session.query(Parent).count())
session.close()
Output:
Before delete, children = 3
Before delete, parent = 1
After delete, children = 3
After delete parent = 0
There is a simple, one-to-many relationship between Parent and Child. The script creates a parent, adds 3 children, then commits. Next, it deletes the parent, but the children persist. Why? How do I make the children cascade delete?
The problem is that sqlalchemy considers Child as the parent, because that is where you defined your relationship (it doesn't care that you called it "Child" of course).
If you define the relationship on the Parent class instead, it will work:
children = relationship("Child", cascade="all,delete", backref="parent")
(note "Child" as a string: this is allowed when using the declarative style, so that you are able to refer to a class that is not yet defined)
You might want to add delete-orphan as well (delete causes children to be deleted when the parent gets deleted, delete-orphan also deletes any children that were "removed" from the parent, even if the parent is not deleted)
EDIT: just found out: if you really want to define the relationship on the Child class, you can do so, but you will have to define the cascade on the backref (by creating the backref explicitly), like this:
parent = relationship(Parent, backref=backref("children", cascade="all,delete"))
(implying from sqlalchemy.orm import backref)
#Steven's asnwer is good when you are deleting through session.delete() which never happens in my case. I noticed that most of the time I delete through session.query().filter().delete() (which doesn't put elements in the memory and deletes directly from db).
Using this method sqlalchemy's cascade='all, delete' doesn't work. There is a solution though: ON DELETE CASCADE through db (note: not all databases support it).
class Child(Base):
__tablename__ = "children"
id = Column(Integer, primary_key=True)
parent_id = Column(Integer, ForeignKey("parents.id", ondelete='CASCADE'))
class Parent(Base):
__tablename__ = "parents"
id = Column(Integer, primary_key=True)
child = relationship(Child, backref="parent", passive_deletes=True)
Pretty old post, but I just spent an hour or two on this, so I wanted to share my finding, especially since some of the other comments listed aren't quite right.
TL;DR
Give the child table a foreign or modify the existing one, adding ondelete='CASCADE':
parent_id = db.Column(db.Integer, db.ForeignKey('parent.id', ondelete='CASCADE'))
And one of the following relationships:
a) This on the parent table:
children = db.relationship('Child', backref='parent', passive_deletes=True)
b) Or this on the child table:
parent = db.relationship('Parent', backref=backref('children', passive_deletes=True))
Details
First off, despite what the accepted answer says, the parent/child relationship is not established by using relationship, it's established by using ForeignKey. You can put the relationship on either the parent or child tables and it will work fine. Although, apparently on the child tables, you have to use the backref function in addition to the keyword argument.
Option 1 (preferred)
Second, SqlAlchemy supports two different kinds of cascading. The first, and the one I recommend, is built into your database and usually takes the form of a constraint on the foreign key declaration. In PostgreSQL it looks like this:
CONSTRAINT child_parent_id_fkey FOREIGN KEY (parent_id)
REFERENCES parent_table(id) MATCH SIMPLE
ON DELETE CASCADE
This means that when you delete a record from parent_table, then all the corresponding rows in child_table will be deleted for you by the database. It's fast and reliable and probably your best bet. You set this up in SqlAlchemy through ForeignKey like this (part of the child table definition):
parent_id = db.Column(db.Integer, db.ForeignKey('parent.id', ondelete='CASCADE'))
parent = db.relationship('Parent', backref=backref('children', passive_deletes=True))
The ondelete='CASCADE' is the part that creates the ON DELETE CASCADE on the table.
Gotcha!
There's an important caveat here. Notice how I have a relationship specified with passive_deletes=True? If you don't have that, the entire thing will not work. This is because by default when you delete a parent record SqlAlchemy does something really weird. It sets the foreign keys of all child rows to NULL. So if you delete a row from parent_table where id = 5, then it will basically execute
UPDATE child_table SET parent_id = NULL WHERE parent_id = 5
Why you would want this I have no idea. I'd be surprised if many database engines even allowed you to set a valid foreign key to NULL, creating an orphan. Seems like a bad idea, but maybe there's a use case. Anyway, if you let SqlAlchemy do this, you will prevent the database from being able to clean up the children using the ON DELETE CASCADE that you set up. This is because it relies on those foreign keys to know which child rows to delete. Once SqlAlchemy has set them all to NULL, the database can't delete them. Setting the passive_deletes=True prevents SqlAlchemy from NULLing out the foreign keys.
You can read more about passive deletes in the SqlAlchemy docs.
Option 2
The other way you can do it is to let SqlAlchemy do it for you. This is set up using the cascade argument of the relationship. If you have the relationship defined on the parent table, it looks like this:
children = relationship('Child', cascade='all,delete', backref='parent')
If the relationship is on the child, you do it like this:
parent = relationship('Parent', backref=backref('children', cascade='all,delete'))
Again, this is the child so you have to call a method called backref and putting the cascade data in there.
With this in place, when you delete a parent row, SqlAlchemy will actually run delete statements for you to clean up the child rows. This will likely not be as efficient as letting this database handle if for you so I don't recommend it.
Here are the SqlAlchemy docs on the cascading features it supports.
Alex Okrushko answer almost worked best for me. Used ondelete='CASCADE' and passive_deletes=True combined. But I had to do something extra to make it work for sqlite.
Base = declarative_base()
ROOM_TABLE = "roomdata"
FURNITURE_TABLE = "furnituredata"
class DBFurniture(Base):
__tablename__ = FURNITURE_TABLE
id = Column(Integer, primary_key=True)
room_id = Column(Integer, ForeignKey('roomdata.id', ondelete='CASCADE'))
class DBRoom(Base):
__tablename__ = ROOM_TABLE
id = Column(Integer, primary_key=True)
furniture = relationship("DBFurniture", backref="room", passive_deletes=True)
Make sure to add this code to ensure it works for sqlite.
from sqlalchemy import event
from sqlalchemy.engine import Engine
from sqlite3 import Connection as SQLite3Connection
#event.listens_for(Engine, "connect")
def _set_sqlite_pragma(dbapi_connection, connection_record):
if isinstance(dbapi_connection, SQLite3Connection):
cursor = dbapi_connection.cursor()
cursor.execute("PRAGMA foreign_keys=ON;")
cursor.close()
Stolen from here: SQLAlchemy expression language and SQLite's on delete cascade
Steven is correct in that you need to explicitly create the backref, this results in the cascade being applied on the parent (as opposed to it being applied to the child like in the test scenario).
However, defining the relationship on the Child does NOT make sqlalchemy consider Child the parent. It doesn't matter where the relationship is defined (child or parent), its the foreign key that links the two tables that determines which is the parent and which is the child.
It makes sense to stick to one convention though, and based on Steven's response, I'm defining all my child relationships on the parent.
Steven's answer is solid. I'd like to point out an additional implication.
By using relationship, you're making the app layer (Flask) responsible for referential integrity. That means other processes that access the database not through Flask, like a database utility or a person connecting to the database directly, will not experience those constraints and could change your data in a way that breaks the logical data model you worked so hard to design.
Whenever possible, use the ForeignKey approach described by d512 and Alex. The DB engine is very good at truly enforcing constraints (in an unavoidable way), so this is by far the best strategy for maintaining data integrity. The only time you need to rely on an app to handle data integrity is when the database can't handle them, e.g. versions of SQLite that don't support foreign keys.
If you need to create further linkage among entities to enable app behaviors like navigating parent-child object relationships, use backref in conjunction with ForeignKey.
I struggled with the documentation as well, but found that the docstrings themselves tend to be easier than the manual. For example, if you import relationship from sqlalchemy.orm and do help(relationship), it will give you all the options you can specify for cascade. The bullet for delete-orphan says:
if an item of the child's type with no parent is detected, mark it for deletion.
Note that this option prevents a pending item of the child's class from being
persisted without a parent present.
I realize your issue was more with the way the documentation for defining parent-child relationships. But it seemed that you might also be having a problem with the cascade options, because "all" includes "delete". "delete-orphan" is the only option that's not included in "all".
Even tho this question is very old, it comes up first when searched for in Google so I'll post my solution to add up to what others said (I've spent few hours even after reading all the answers in here).
As d512 explained, it is all about Foreign Keys. It was quite a surprise to me but not all databases / engines support Foreign Keys. I'm running a MySQL database. After long investigation, I noticed that when I create new table it defaults to an engine (MyISAM) that doesn't support Foreign Keys. All I had to do was to set it to InnoDB by adding mysql_engine='InnoDB' when defining a Table. In my project I'm using an imperative mapping and it looks like so:
db.Table('child',
Column('id', Integer, primary_key=True),
# other columns
Column('parent_id',
ForeignKey('parent.id', ondelete="CASCADE")),
mysql_engine='InnoDB')
Answer by Stevan is perfect. But if you are still getting the error. Other possible try on top of that would be -
http://vincentaudebert.github.io/python/sql/2015/10/09/cascade-delete-sqlalchemy/
Copied from the link-
Quick tip if you get in trouble with a foreign key dependency even if you have specified a cascade delete in your models.
Using SQLAlchemy, to specify a cascade delete you should have cascade='all, delete' on your parent table. Ok but then when you execute something like:
session.query(models.yourmodule.YourParentTable).filter(conditions).delete()
It actually triggers an error about a foreign key used in your children tables.
The solution I used it to query the object and then delete it:
session = models.DBSession()
your_db_object = session.query(models.yourmodule.YourParentTable).filter(conditions).first()
if your_db_object is not None:
session.delete(your_db_object)
This should delete your parent record AND all the children associated with it.
TLDR: If the above solutions don't work, try adding nullable=False to your column.
I'd like to add a small point here for some people who may not get the cascade function to work with the existing solutions (which are great). The main difference between my work and the example was that I used automap. I do not know exactly how that might interfere with the setup of cascades, but I want to note that I used it. I am also working with a SQLite database.
I tried every solution described here, but rows in my child table continued to have their foreign key set to null when the parent row was deleted. I'd tried all the solutions here to no avail. However, the cascade worked once I set the child column with the foreign key to nullable = False.
On the child table, I added:
Column('parent_id', Integer(), ForeignKey('parent.id', ondelete="CASCADE"), nullable=False)
Child.parent = relationship("parent", backref=backref("children", passive_deletes=True)
With this setup, the cascade functioned as expected.

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