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Flask-SQLAlchemy backref function and backref parameter

In Flask-SQLAlchemy, the backref parameter in relationship method allows you to declare a new property under a specified class as seen in the example in their docs:
class Person(db.Model):
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String(50))
addresses = db.relationship('Address', backref='person', lazy='dynamic')
class Address(db.Model):
id = db.Column(db.Integer, primary_key=True)
email = db.Column(db.String(50))
person_id = db.Column(db.Integer, db.ForeignKey('person.id'))
But then there is also a backref function:
class User(db.Model):
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String(50))
addresses = db.relationship('Address',
backref=db.backref('person', lazy='joined'),
lazy='dynamic')
In this case, what's the role of the backref function passed to the backref parameter, especially with the multiple lazy definitions? How is it different from backref='person'?

From the documentation for Flask models:
backref is a simple way to also declare a new property on the Address class. You can then also use my_address.person to get to the person at that address. lazy defines when SQLAlchemy will load the data from the database:
select (which is the default) means that SQLAlchemy will load the data as necessary in one go using a standard select statement.
joined tells SQLAlchemy to load the relationship in the same query as the parent using a JOIN statement.
subquery works like 'joined' but instead, SQLAlchemy will use a subquery.
dynamic is special and useful if you have many items. Instead of loading the items SQLAlchemy will return another query object which you can further refine before loading the items. This is usually what you want if you expect more than a handful of items for this relationship.

the second lazy define the lazy status for backref. For example:
addresses = db.relationship('Address',
backref=db.backref('person', lazy='joined'), lazy='dynamic')
lazy='joined' define the lazy status for 'person'
lazy='dynamic' define the lazy status for addresses

Flask-Sqlalchemy multiple databases (binds) with the same model (class DB.Model)

I'm a beginner with python/Flask/SQLAlchemy so sorry if my questions are dumb.
I want to create an API with Flask using Flask-SQLAlchemy as following:
one sqlite database for users/passwords
SQLALCHEMY_DATABASE_URI = 'sqlite:////path/to/users.db'
class User(DB.Model):
__tablename__ = 'users'
id = DB.Column(DB.Integer, primary_key=True)
username = DB.Column(DB.String(64), index=True)
password = DB.Column(DB.String(128))
Lets say I have multiple "customers" witch a user can create using
$ http POST http://localhost:5000/api/customers/ name=customer1
class Customer(DB.Model):
__tablename__ = 'customer'
customer_id = DB.Column(DB.Integer, primary_key=True)
customer_name = DB.Column(DB.String, unique=True, index=True)
I need to create a separate sqlite file for each "customers" :
SQLALCHEMY_BINDS = {
'customer1' = 'sqlite:////path/customer1.db',
'customer2' = 'sqlite:////path/customer2.db',
...
}
My questions are:
I do not have fixed number of "customers" so I cannot create a model class for each and specify the "bind_key" for each. Is it possible to do this with Flask-SQLAlchemy or I need to use plain SQLAlchemy?
I have 3 "customers" in data/ as customer1.db, customer2.db and customer3.db.
I would start the application and create SQLALCHEMY_BINDS dictionary listing the files in data/ and then DB.create_all() on a request for a specific "customer" .
how can I bind to the right .db file using the Flask-SQLAlchemy
DB.session?
I've read Using different binds in the same class in Flask-SQLAlchemy

Why exactly do you want entirely separate DB files for each customer?
In any case this is easier with straight SQLAlchemy. You can create a getter function which returns a session pointing to your db file.
def get_session(customer_id):
sqlite_url = 'sqlite:////path/customer%s.db' % customer_id
engine = create_engine(sqlite_url)
# initialize the db if it hasn't yet been initialized
Base.metadata.create_all(engine)
Session = sessionmaker(bind=engine)
session = Session()
return session
You can then use and close that session.
But without knowing your specific use case, it is difficult to understand why you would want to do this instead of just using a single SQLite database.

NoForeignKey error on relationship even though SQLAlchemy model specifies foreign key

I am having some difficulty setting up a one to one relationship between two models in my flask application. I have two models Employeeand `Photo'. An employee has only one photo associated with it and vice-versa.
This is the code that I have in my models.py file:
class Employee(db.Model):
__tablename__ = 'employees'
id = db.Column(db.Integer, primary_key=True)
photo = db.relationship("Photo", uselist=False, back_populates='employees')
class Photo(db.Model):
__tablename__ = 'photos'
id = db.Column(db.Integer, primary_key=True)
employee_id = db.Column(db.Integer, db.ForeignKey('employees.id'))
employee = db.relationship('Photo', back_populates='photo')
I've followed the instruction on the SQL Alchemy documentation found hereSQL Alchemy simple relationships. The error that I keep encountering is shown below:
sqlalchemy.exc.NoForeignKeysError: Could not determine join condition between parent/child tables on relationship Photo.employee
- there are no foreign keys linking these tables.
Ensure that referencing columns are associated with a ForeignKey or ForeignKeyConstraint, or specify a 'primaryjoin' expression.
I clearly specify the foreign key right here employee_id = db.Column(db.Integer, db.ForeignKey('employees.id')) . I'm not sure what I'm doing wrong. Additionally, I was reading the documentation and it doesn't help that uselist, backref, and back_populates are so similar.
Can someone assist me with this? Help would be greatly appreciated.
One to One relationship stack overflow question

backref automatically adds the reverse relationship to the related model. You can pass a db.backref object to it to specify options to the relationship. back_populates tells SQLAlchemy to populate an existing reverse relationship, rather than creating it. uselist tells SQLAlchemy whether the relationship is a list or not, for cases where it can't determine that automatically.
In your example, you need one relationship, with one backref that is a single item.
You have two typos in your code. First, back_populates='employees' should refer to 'employee', which is what you called the property on the related model. Second, employee = relationship('Photo' is pointing at the wrong model, it should relate to Employee.
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
app = Flask(__name__)
db = SQLAlchemy(app)
db.engine.echo = True
class Photo(db.Model):
id = db.Column(db.Integer, primary_key=True)
class Employee(db.Model):
id = db.Column(db.Integer, primary_key=True)
photo_id = db.Column(db.ForeignKey(Photo.id))
photo = db.relationship(Photo, backref=db.backref('employee', uselist=False))
db.create_all()
db.session.add(Employee(photo=Photo()))
db.session.commit()
print(Employee.query.get(1).photo)

SQLAlchemy low performance when use relationship

I have SQLAlchemy models in my Flask application:
class User(db.Model):
__tablename__ = 'users'
id = db.Column(db.Integer, primary_key=True)
photos = db.relationship('Photo', lazy='joined')
class Photo(db.Model):
__tablename__ = 'photos'
id = db.Column(db.Integer, primary_key=True)
user_id = db.Column(db.Integer, db.ForeignKey('users.id'))
photo = db.Column(db.String(255))
When i query user i get user with his photos automatically. But i noticed if user has a lot of photos, query u = User.query.get(1) become very slow. I do the same but manually with lazy='noload' option
u = User.query.get(1)
photos = Photo.query.filter_by(user_id == 1)
and on the same data it works faster in times. Where is problem, is sql join slow(don`t think so, because it start hang on 100-1kk photo objects, not so big data) or something wrong in the SQLAlchemy?

From my experiences I suggest you to get familiar with SQLAlchemy Loading Relationships. Sometimes even if relationship functionality is easy, usefull in larger datasets is better to do not use it, or even execute plain text SQL. This will be better from performance point of view on larger data sets.

What's the proper way to describe an associative object by SQLalchemy the declarative way

I'm looking for a way to describe an associative object the declarative way. Beyond storing the foreign keys in the association table, I need to store information like the creation date of the association.
Today, my model looks like that :
# Define the User class
class User(Base):
__tablename__ = 'users'
# Define User fields
id = schema.Column(types.Integer(unsigned=True),
schema.Sequence('users_seq_id', optional=True), primary_key=True)
password = schema.Column(types.Unicode(64), nullable=False)
# Define the UserSubset class
class UserSubset(Base):
__tablename__ = 'subsets'
# Define UserSubset fields
id = schema.Column(types.Integer(unsigned=True),
schema.Sequence('subsets_seq_id', optional=True), primary_key=True)
some_short_description = schema.Column(types.Unicode(50), nullable=False)
# Define the subset memberships table
subset_memberships = schema.Table('group_memberships', Base.metadata,
schema.Column('user_id', types.Integer(unsigned=True), ForeignKey('users.id')),
schema.Column('subset_id', types.Integer(unsigned=True), ForeignKey('subsets.id')),
schema.Column('created', types.DateTime(), default=now, nullable=False),
)
Can I connect everything in an associative object ? Or should I change stop using the declarative way ?

What you are using at the moment is just a Many-to-Many-relation. How to work with association objects is described in the docs.
There is also an extension called associationproxy which simplifies the relation.

As you can see in the manual, configuring a one to many relation is really simple:
class User(Base):
__tablename__ = 'users'
id = Column(Integer, primary_key=True)
name = Column(String(50))
addresses = relation("Address", backref="user")
class Address(Base):
__tablename__ = 'addresses'
id = Column(Integer, primary_key=True)
email = Column(String(50))
user_id = Column(Integer, ForeignKey('users.id'))
Many to many relations isn't much harder:
There’s nothing special about many-to-many with declarative. The secondary argument to relation() still requires a Table object, not a declarative class. The Table should share the same MetaData object used by the declarative base:
keywords = Table('keywords', Base.metadata,
Column('author_id', Integer, ForeignKey('authors.id')),
Column('keyword_id', Integer, ForeignKey('keywords.id'))
)
class Author(Base):
__tablename__ = 'authors'
id = Column(Integer, primary_key=True)
keywords = relation("Keyword", secondary=keywords)
You should generally not map a class and also specify its table in a many-to-many relation, since the ORM may issue duplicate INSERT and DELETE statements.
Anyway, what you seem to be doing might be better served with inheritance. Of course, there can be complex table relations that will be a pathological case for the declarative way, but this doesn't seem to be one of them.
One more thing, code comments should state what the following code does ans why, not how it does it. Having a # Define the User class comment is almost like having a line of code saying a = 1 # assing value 1 to variable "a".