What are some good Python ORM solutions?


Question

I'm evaluating and looking at using CherryPy for a project that's basically a JavaScript front-end from the client-side (browser) that talks to a Python web service on the back-end. So, I really need something fast and lightweight on the back-end that I can implement using Python that then speaks to the PostgreSQL DB via an ORM (JSON to the browser).

I'm also looking at Django, which I like, since its ORM is built-in. However, I think Django might be a little more than I really need (i.e. more features than I really need == slower?).

Anyone have any experience with different Python ORM solutions that can compare and contrast their features and functionality, speed, efficiency, etc.?

1
198
12/8/2014 11:24:03 PM

Accepted Answer

SQLAlchemy is more full-featured and powerful (uses the DataMapper pattern). Django ORM has a cleaner syntax and is easier to write for (ActiveRecord pattern). I don't know about performance differences.

SQLAlchemy also has a declarative layer that hides some complexity and gives it a ActiveRecord-style syntax more similar to the Django ORM.

I wouldn't worry about Django being "too heavy." It's decoupled enough that you can use the ORM if you want without having to import the rest.

That said, if I were already using CherryPy for the web layer and just needed an ORM, I'd probably opt for SQLAlchemy.

90
1/9/2015 2:50:40 PM

If you're looking for lightweight and are already familiar with django-style declarative models, check out peewee: https://github.com/coleifer/peewee

Example:

import datetime
from peewee import *

class Blog(Model):
    name = CharField()

class Entry(Model):
    blog = ForeignKeyField(Blog)
    title = CharField()
    body = TextField()
    pub_date = DateTimeField(default=datetime.datetime.now)

# query it like django
Entry.filter(blog__name='Some great blog')

# or programmatically for finer-grained control
Entry.select().join(Blog).where(Blog.name == 'Some awesome blog')

Check the docs for more examples.


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