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.
I've got two models: User and Group.
User can be in one group so:
class User(db.Model):
# other fields
group_id = db.Column(db.Integer(), db.ForeignKey('group.id'))
but on the other hand I would also have some info about user who create that specific group:
class Group(db.Model):
# other fields
users = db.relationship("User", backref='group')
created_by = db.Column(db.Integer(), db.ForeignKey('user.id'))
Result is:
sqlalchemy.exc.CircularDependencyError: Can't sort tables for DROP; an unresolvable foreign key dependency exists between tables: group, user. Please ensure that the ForeignKey and ForeignKeyConstraint objects involved in the cycle have names so that they can be dropped using DROP CONSTRAINT.
I tried use_alter=True, but it gives me:
sqlalchemy.exc.CompileError: Can't emit DROP CONSTRAINT for constraint ForeignKeyConstraint(
Interestingly I'd expect you to get an AmbiguousForeignKeyError but instead you seem to get a CircularDependencyError? According to the docs this is caused by two scenarios:
In a Session flush operation, if two objects are mutually dependent on each other, they can not be inserted or deleted via INSERT or
DELETE statements alone; an UPDATE will be needed to post-associate or
pre-deassociate one of the foreign key constrained values. The
post_update flag described at Rows that point to themselves / Mutually
Dependent Rows can resolve this cycle.
In a MetaData.sorted_tables
operation, two ForeignKey or ForeignKeyConstraint objects mutually
refer to each other. Apply the use_alter=True flag to one or both, see
Creating/Dropping Foreign Key Constraints via ALTER.
I'm not sure what you're executing that's causing this particular error, but most likely you'll be able to solve it by solving the ambiguous reference.
The ambigious reference is due to SQLAlchemy not being able to figure out how to perform the join when there are multiple references (users and created_by in this case). This can be resolved by specifying how the relationship should join which can be done by either giving the specific foreign key it should use or by explicitly determining the join condition.
You can see these being applied to your example here:
class User(Base):
# Other setup / fields
group_id = Column(Integer, ForeignKey('group.id'))
class Group(Base):
# Other setup / fields
created_by_id = Column(Integer, ForeignKey('user.id'), nullable=False)
created_by = relationship("User", foreign_keys=[created_by_id])
users = relationship("User", backref="group", primaryjoin=id==User.group_id)
Documentation regarding relationship joins: http://docs.sqlalchemy.org/en/latest/orm/join_conditions.html#configuring-how-relationship-joins
I'm attempting to make my first app with flask. This is my node class as of now:
class TreePage(db.Model):
__tablename__ = 'tree'
id = db.Column(db.Integer, primary_key= True)
name = db.Column(db.String(100), nullable= False)
content = db.Column(db.String)
parent_id = db.create_all(db.Integer, db.ForeignKey('id'))
children = db.relationship('TreeNode', cascade = "all",
backref = db.backref("parent", remote_side='TreeNode.id'),
collection_class = db.attribute_mapped_collection('name')
)
Being new to SQLAlchemy and databases in general, lots of the information I'm reading here and on the SQLAlchemy documentation is kind of hard to grasp.
My goal right now is to be able to access a tree and its content, and then if that tree has children to be able to pick which child to study from; this is basically a visual representation of what I want to make.
My guess is this should be a one to many relationship, so I won't have to deal with local/remote sides right? Both of which confuse me at the moment. Next, do I need to worry at all about the cascade parameter, or can I leave it be for now?
Lastly, I want to solidify how self referential relationships work. With two different classes it's easy for me to grasp: the 'one' relationship creates a relationship object, and then the 'many' object creates a foreign key that references the primary key of its owner. But in the case of a self referential relationship, is the 'owner' the object that holds id and parent_id being the id of whatever parent object comes before? thanks and I apologize if this is at all confusing.
I have db that I cannot modify, it has two tables 'people' and 'relation'. The table 'people' has names, ids and the column parent (yes/no). The table 'relation' contains a foreign key 'people.id' for parent and a 'people.id' for its child. I want to join columns in the people table so I can
People.query.filter_by(id='id of the parent')
to get the name of the parent and it's childs. This is my code:
class People(db.model):
__tablename__ = 'people'
id = db.Column(db.integer(), primary_key=True
name = db.Column(db.String())
parent = db.Column(db.Integer()) ##0 for no 1 for yes
parent_id=db.relationship('Link',backref=db.backref('Link.parent_id')
class Link(db.Model):
_tablename__ = 'link'
parent_id=db.Column(db.Integer(),db.ForeignKey('people.id'),primary_key=True)
id = db.Column(db.Integer(), db.ForeignKey('people.id'), primary_key=True)
dateofbirth = db.Column(db.Integer())
SQLAlchemy tells me:
ArgumentError: relationship 'parent_id' expects a class or a mapper argument (received: <class 'sqlalchemy.sql.schema.Table'>)
Excuse me if I messed up, but it's my first question here (and also the first steps with SQLAlchemy)
Typically you would want to set up the foreign key and backref in the same table, like this:
class Link(db.Model):
_tablename__ = 'link'
parent_id = db.Column(db.Integer(),db.ForeignKey('people.id'),primary_key=True)
parent = db.relationship('People', backref='links')
Now you can access each Link entries parent via Link.parent, and you can get a list of each People entries links via People.links (assuming this is a one-to-many relationship).
Also, if People.parent is supposed to represent a boolean value then:
1.) you should follow the standard naming convention and call it something like is_parent
2.) you should declare People.parent as a db.Boolean type, not a db.Integer. In most (probably all) database implementations, using booleans instead of integers (when appropriate) is more memory efficient.
I hope this helped.
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.