SQLAlchemy, Declarative layers, and the ORM 'Problem'

There’s been a bit of talk on the Pylons devel list regarding the recommended way to use SQLAlchemy with Pylons mainly regarding how to use SA (SQLAlchemy) in a fashion that is well documented and easy to work with (and maintain!).

Prior to Pylons 0.9.6 and SQLAlchemy 0.4 it was a bit of a mess, with the framework needing to load the config (since thats where your db settings are), then setup globals for SA…. eek. Mike Orr had a good intermediary solution for SA 0.3 called SAContext that handled many of the tricky parts. Unfortunately, this actually caused even more confusion as more ways of doing the same thing came about. SAContext solved some of the global config grabbing issues, but the additional layer of indirection made trouble shooting even harder (despite how small of a library it was).

Less is More

So the fix? Less intermediary layers, less indirection… essentially, KISS. Despite how much Pylons was attempting to help a user to get the db going, the additional layers in the end actually caused more problems then they solved. Of course, I shouldn’t have been too surprised…. Mike Bayer did warn me about many of these things at the beginning. Being overly eager to make things “easier” for new users, I ignored him. :)

This is why Pylons does not recommend Elixir, and with SA 0.4 the recommended usage of SA is to use its plain mapper functionality should you need an ORM layer. Yes, that’s right, despite almost every web framework out there pushing its ORM on you (or someone else’s ORM), there are many times when an app doesn’t even need a full-blown ORM.

Declarative vs Basic SA

For a better look at why one might consider additional layers on SA a bad thing lets compare a fairly basic table setup consisting of users and groups. Each user can be in multiple groups, and lets use proper referential integrity to ensure that groups aren’t deleted when users are still in them.

Compare the following two ways of setting up a basic many to many relation and the tables:

SQLAlchemy 0.4


from sqlalchemy import Column, ForeignKey, MetaData, Table, types
from sqlalchemy.orm import mapper, relation

metadata = MetaData()

person_table = Table('person’, metadata, Column('id’, types.Integer, primary_key=True), Column('name’, types.String, nullable=False), Column('age’, types.String)
)

group_table = Table('group’, metadata, Column('id’, types.Integer, primary_key=True), Column('name’, types.String, nullable=False)
)

persongroups_table = Table('person_groups’, metadata, Column('person_id’, types.Integer, ForeignKey('person.id’, ondelete='CASCADE’), primary_key=True), Column('group_id’, types.Integer, ForeignKey('group.id’, ondelete='RESTRICT’), primary_key=True),
)

class Person(object): pass

class Group(object): pass

mapper(Person, person_table, properties=dict( groups=relation(Group, backref='people’, lazy=False)
))
mapper(Group, group_table)

Elixir


from elixir import *
class Person(Entity): has_field('name’, String) has_and_belongs_to_many('groups’, of_kind='Group’)

class Group(Entity): has_field('name’, String) has_and_belongs_to_many('people’, of_kind='Person’)

On first glance, its pretty obvious that everyone should love Elixir vs the obviously more tedious SA approach of layout out your tables, then mapping them to the class objects. However, look at these two examples, and try to quickly answer the following questions:

  • How do you add a column to the many to many table to store an additional bit of info for the join?
  • Do they both enforce referential integrity?
  • How do you control whether SA is eager loading the relation? Can you restrict it to just one column of the relation?
  • What are the table names used?
  • How many tables are in your database?
  • Where do you change the id column name?
  • Which one is closer to the Zen of Python?

I think the explicit setup makes many of these questions easier to answer just at a glance. Those with enough Elixir experience can fairly easily answer most of these questions, but consider what that implies. Not only do you need to know SQLAlchemy options and parameters, but you need to know Elixir options and how they map to the SQLAlchemy functions. The desire to reduce the up-front setup of the ORM actually increases the amount of knowledge a user has to have in order to use it, and the most worrisome aspect… how to troubleshoot it.

Setups that Grow with You

With Pylons, a goal has been to provide out of the box recommendations that grow with you. That is, using the set of recommended tools may not be as apparently “easy” as some other frameworks. However, the pay-off is that you don’t hit a wall in 2 months when your application inevitably gets a little more advanced and needs to do something the simple tools either can’t do at all, or it’s incredibly difficult to do even slightly complicated things (eager load 2 columns off a related table, but not all of them). This way, the toolset you learned, you can keep using as you get more advanced and you don’t “outgrow” your tools.

While Elixir definitely appears to be easier at first glance, when you need to get more complicated you can’t exactly turn to the SA docs since Elixir has put a layer between you and SA. This can be very crippling when you eventually hit a wall, and so much ‘magic’ is wrapped up in the declarative layer that you have to troubleshoot additional layers of code when something goes wrong. The result of this is that to effectively use Elixir in complicated setups with SQLAlchemy, you need to really really know both of them which actually requires more work for a user than plain SQLAlchemy.

The SA example clearly requires a little more up-front setup, however, are you really adding tables to your database every day? How often are you going to be actually touching the table and mapper code, vs just adding domain model methods to your Person/Group class? Did the layer make it easier or harder to use multiple databases and/or put more between you and advanced SA functionality you might need later?

Adam Gomaa pointed out some interesting issues with Django’s ORM and Elixir but unfortunately tries to do the same thing Elixir and TurboEntity do…. add more layers. More layers more indirection more to wade through when you need to do something that should be pretty basic with SQLAlchemy (and is probably nicely documented on the SA site, which won’t help with these layers until you dig through the layer to find the basic SA objects the SA site refers to…).

What really makes a lot of this even more trouble-some with SA, is that when setting up complex relationships, the order of declaring table objects becomes important, since relations need to refer to them and the ORM classes. This usually results in some interesting metaclass hackery when you have these Entity’s in multiple modules, importing each other, and doing other fairly common stuff.

SQLAlchemy 0.4

In the end, I’ve been using plain SQLAlchemy 0.4 (at beta5 now, but quite stable) a lot lately, and its really great. Yes, setting up the tables (generally a one-time thing) took me probably 15 mins longer than it would’ve with Elixir. But I’m fairly certain I’ve saved myself significantly more time in the long run since I won’t need to worry about diving into Elixir code to try and find SA objects when I need a complex query, or trying to figure out how to hack Elixir’s connection should I need multiple db connections at once, etc.

So please, new users to SQLAlchemy, use just SQLAlchemy. It definitely seems daunting at first, but the flexibility and comprehensive documentation give you a solution that scales to meet your needs, with no walls in sight.

On a side-note, its interesting to compare my position on this issue to the Django team lack of AJAX helpers. The Django team rightfully claims that Javascript isn’t that hard, so “get over it” and learn a nice Javascript library so you can do powerful things. Also note that by including AJAX helpers, Pylons is encouraging one part that doesn’t scale… as the AJAX helpers will have you hitting a wall sooner or later.