SQLAlchemy-bulk-lazy-loader

SQLAlchemy Bulk Lazy Loader

A custom lazy loader for SQLAlchemy relations which ensures relations are always loaded efficiently. This loader automatically solves the n+1 query problem <http://use-the-index-luke.com/sql/join/nested-loops-join-n1-problem>_ without needing to manually add joinedload or subqueryload statements to all your queries.

The Problem

The n + 1 query problem arises whenever relationships are lazy-loaded in a loop. For example:

.. code:: python

students = session.query(Student).limit(100).all()
for student in students:
    print('{} studies at {}'.format(student.name, student.school.name))

In the above code 101 SQL queries will be generated - one to load the list of students and then 100 individual queries for each student to load that student's school. The statements look like:

.. code:: sql

SELECT * FROM students LIMIT 100;
SELECT * FROM schools WHERE schools.student_id = 1 LIMIT 1;
SELECT * FROM schools WHERE schools.student_id = 2 LIMIT 1;
SELECT * FROM schools WHERE schools.student_id = 3 LIMIT 1;
SELECT * FROM schools WHERE schools.student_id = 4 LIMIT 1;
...

This is bad.

The traditional way to solve this with SQLAlchemy is to add a joinedload or subqueryload to the initial query to include the schools along with the students, like below:

.. code:: python

students = (
    session.query(Student)
        .options(subqueryload(Student.school))
        .limit(100)
        .all()
)
for student in students:
    print('{} studies at {}'.format(student.name, student.school.name))

While this works, it needs to be added to every query that's performed, and when there's a lot of related models being added you can easily end up with a massive list of subqueryload and joinedload. If you forget even one anywhere then you're silently back to the n + 1 query problem. Also, if you stop needing a relation later you need to remember to remove it from the original query or else you're now loading too much data. Furthermore, it's just a huge pain to have to maintain these lists of related models throughout your code everywhere there's a database query.

Wouldn't it be great if you didn't have to worry about adding subqueryload and joinedload and yet also be guaranteed that all your relations are loading efficiently?

How The Bulk Lazy Loader Works

99% of the time, if there is a list of models loaded in memory and a relation on one of them is lazy-loaded then you're in a loop and the same relationship is going to be requested on every other model. SQLAlchemy Bulk Lazy Loader assumes this is the case and whenever a relation on a model is lazy-loaded, it will look through the current session for any other similar models that need that same relation loaded and will issue a single, bulk SQL statement to load them all at once.

This means you can load all the relations you want in loops while being guaranted that all relations are loaded performantly, and only the relations that are used are loaded. For example, here's the same code from above:

.. code:: python

students = session.query(Student).limit(100).all()
for student in students:
    print('{} studies at {}'.format(student.name, student.school.name))

The Bulk Lazy Loader will issue only 2 SQL statements, the same as if you had specified subqueryload on the initial query, except that now your code is a lot cleaner and you're guaranteed to be loading just the relations you need. Yay!

Installation

SQLAlchemy Bulk Lazy Loader can be installed via pip

pip install SQLAlchemy-bulk-lazy-loader

Usage

Before you declare your SQLAlchemy mappings you need to run the following:

.. code:: python

from sqlalchemy_bulk_lazy_loader import BulkLazyLoader
BulkLazyLoader.register_loader()

This registers the loader with sqlalchemy and makes it available on your relations by specifying lazy='bulk' in your relation mappings. For example:

.. code:: python

class Student(db.model):
    id = db.Column(db.Integer, primary_key=True)
    school_id = db.Column(db.Integer, db.ForeignKey('school.id'))

class School(db.model):
    id = db.Column(db.Integer, primary_key=True)
    students = db.relationship('Student', lazy='bulk', backref=db.backref('school', lazy='bulk'))

And that's it! The bulk lazy loader will be used for student.school and school.students relations.

Limitations

Currently only relations on a single primary key or a simple secondary join are supported.

.. code:: python

students = relationship('Student', lazy='bulk') # OK!
students = relationship('Student', lazy='bulk', order_by=Student.id) # OK!
student = relationship('Student', lazy='bulk', uselist=False) # OK!
students = relationship('Student', lazy='bulk', secondary=school_to_students) # OK!
students = relationship('Student', lazy='bulk', secondary=school_to_students, primaryjoin='and_(...)') # NOT SUPPORTED

Python 2 is not supported.

But I have this one case where I want to load the relations differently!

If you want to load relations in the query still using subqueryload or joinedload you can still do that - the bulk lazy loader will only kick in when it's asked for a relation on a model that isn't already loaded. If you really need fine-grained control of relation loading in a specific case you can also use attributes.set_committed_value(model, <relation_name>, <related_model/s>) to explicitly set related models. In fact this is how BulkLazyLoader works behind the scenes.

Contributing

Contributions are welcome! Create a pull request and make sure to add test coverage. Tests use the SQLAlchemy test framework and can be run with py.test.

Happy loading!