django-autofixture

This app aims to provide a simple way of loading masses of randomly generated test data into your development database. You can use a management command to load test data through command line.

It is named autofixture because of the similarity of how I mainly used django's fixtures. Usually you add test data through the admin to see how your site looks with non static pages. You export data by using dumpdata to send it to your colleagues or to preserve it before you make a manage.py reset app and so on. Your site gets more and more complex and adding test data gets more and more annoying.

This is the usecase where autofixtures should help you to save time that can actually be spent on hacking.

Installation

You must make the autofixture package available on your python path. Either drop it into your project directory or install it from the python package index with pip install django-autofixture. You can also use easy_install django-autofixture if you don't have pip available.

To use the management command you must add 'autofixture' to the INSTALLED_APPS setting in your django settings file. You don't need to do this if you want to use the autofixture package only as library.

Management command

The loadtestdata accepts the following syntax:

python manage.py loadtestdata [options] app.Model:# [app.Model:# ...]

Its nearly self explanatory. Supply names of models, prefixed with its app name. After that, place a colon and tell the command how many objects you want to create. Here is an example how to create three categories and twenty entries for you blogging app:

python manage.py loadtestdata blog.Category:3 blog.Entry:20

Voila! You have ready to use testing data populated to your database. The model fields are filled with data by producing randomly generated values depending on the type of the field. E.g. text fields are filled with lorem ipsum dummies, date fields are populated with random dates from the last years etc.

There are a few command line options available. Mainly to control the behavior of related fields. If foreingkey or many to many fields should be populated with existing data or if the related models are also generated on the fly. Please have a look at the help page of the command for more information:

python manage.py help loadtestdata

Using autofixtures as tool for unittests

It has proofed that autofixtures have a great use for unittests. It has always bugged me that creating complex models for testing their behaviour was complicated. Sometimes models have strict restrictions or many related objects which they depend on. One solution would be to use traditional fixtures dumped from your production database. But while in development when database schemes are changing frequently, its hard to maintain all fixtures and to know exactly which objects are contained in the dumps etc...

Autofixtures to the rescue! It lets you automatically generate models and all of their dependecies on the fly. Have a look at the following examples.

Lets start with the very basics. We create an AutoFixture instance for the Entry model and tell it to create ten model instances:

from autofixture import AutoFixture
fixture = AutoFixture(Entry)
entries = fixture.create(10)

Now you can play around and test your blog entries. By default dependecies of foreignkeys and many to many relations are solved by randomly selecting an already existing object of the related model. What if you don't have one yet? You can provide the generate_fk attribute which allows the autofixture instance to follow foreignkeys by generating new related models:

fixture = AutoFixture(Entry, generate_fk=True)

This generates new instance for all foreignkey fields of Entry. Unless the model has a foreign key reference to itself, wherein the field will be set to None if allowed or raise a CreateInstanceError if not. This is to prevent max recursion depth errors. Its possible to limit this behaviour to single fields:

fixture = AutoFixture(Entry, generate_fk=['author'])

This will only create new authors automatically and doesn't touch other tables. The same is possible with many to many fields. But you need additionally specify how many objects should be created for the m2m relation:

fixture = AutoFixture(Entry, generate_m2m={'categories': (1,3)})

All created entry models get one to three new categories assigned.

Setting custom values for fields

However its often necessary to be sure that a specific field must have a specific value. This is easily achieved with the field_values attribute of AutoFixture:

fixture = AutoFixture(Entry,
    field_values={'pub_date': datetime(2010, 2, 1)})

Limiting the set of models assigned to a ForeignKey field

You could, for example, limit the Users assigned to a foreignkey field to only non-staff Users. Or create Entries for all Blogs not belonging to Yoko Ono. Use the same construction as ForeignKey.limit_choices_to attribute:

from autofixture import AutoFixture, generators
fixture = AutoFixture(Entry,
        field_values={
            'blog': generators.InstanceSelector(Blog,
                limit_choices_to={'name__ne':"Yoko Ono's blog"})
                      } )

Custom autofixtures

To have custom autofixtures for your model, you can easily subclass AutoFixture somewhere (e.g. in myapp/autofixtures.py)

from models import MyModel
from autofixture import generators, register, AutoFixture

class MyModelAutoFixture(AutoFixture):
    field_values = {
        'name': generators.StaticGenerator('this_is_my_static_name'),
    }

register(MyModel, MyModelAutoFixture)

Then, loadtestdata will automatically use your custom fixtures.

python manage.py loadtestdata app.MyModel:10

You can load all autofixtures.py files of your installed apps automatically like you can do with the admin autodiscover. Do so by running autofixture.autodiscover() somewhere in the code, preferably in the urls.py.

More

There is so much more to explore which might be useful for you and your projects:

• There are ways to register custom AutoFixture subclasses with models that are automatically used when calling loadtestdata on the model.
• More control for related models, even with relations of related models... (e.g. by using generate_fk=['author', 'author__user'])
• Custom constraints that are used to ensure that created the models are valid (e.g. unique and unique_together constraints which are already handled by default)

I hope to explain this in the future with more details in a documentation. It will be written but is not finished yet. I wanted to get this project out to support you in development. But since its only python code you can easily study the source on your own and see in which ways it can be used. There are already some parts documented with doc strings which might also be helpful for you.

Contribute

You can find the latest development version on github. Get there and fork it, file bugs or send me nice wishes.

To start developing, make sure the test suite passes:

virtualenv .env
source .env/bin/activate
pip install -r requirements/tests.txt
python setup.py test

Now go, do some coding.

Feel free to drop me a message about critique or feature requests. You can get in touch with me by mail or twitter.

Happy autofixturing!