factory-djoy 0.5.0

Factories for Django, creating valid instances every time

Simple wrappers around Factory Boy for Django which call full_clean when creating instances to ensure that only valid data enters your Django database.

Works on latest flavours of Django 1.8, 1.9 and 1.10, with Factory Boy version 2 or greater.

Installation

Install with pip:

pip install factory_djoy

Usage

CleanModelFactory

This is a generic wrapper for DjangoModelFactory. It provides all the functionality of DjangoModelFactory but extends create to call full_clean at post-generation time. This validation ensures that your test factories only create instances that meet your models’ field level and model level validation requirements - this leads to better tests.

Example

Given a very simple model called Item which has one name field that is required and has a max length of 5 characters:

class Item(Model):
    """
    Single Item with one required field 'name'
    """
    name = CharField(max_length=5, unique=True)

Then we can create a clean factory for it using CleanModelFactory:

from factory_djoy import CleanModelFactory

from yourapp.models import Item


class SimpleItemFactory(CleanModelFactory):
    class Meta:
        model = Item

Now we haven’t defined any default value for the name field, so if we use this factory with no keyword arguments then ValidationError is raised:

>>> SimpleItemFactory()
Traceback (most recent call last):
...
django.core.exceptions.ValidationError: {'name': ['This field cannot be blank.']}

However, if we pass a valid name, then everything works OK:

>>> SimpleItemFactory(name='tap')

Automatically generating values

The point of using CleanModelFactory is not to make testing harder because lots of keyword arguments are needed for each factory call, instead it should be easier and more reliable. Really the work with SimpleItemFactory above is not complete.

Now we replace SimpleItemFactory with a new ItemFactory that generates the required name field by default. We’re going to use factory_boy’s Fuzzy attributes to generate random default values each time the model is instantiated and because full_clean is called every time an instance is created, we will know that every instance passed validation.

from factory.fuzzy import FuzzyText
from factory_djoy import CleanModelFactory


class ItemFactory(CleanModelFactory):
    class Meta:
        model = Item

    name = FuzzyText(length=5)

Now we can happily generate multiple instances of Item leaving the factory to create random names for us.

>>> item = ItemFactory()
>>> item.name
'TcEBK'

Alternatively, if you wanted all your created Item instances to have the name value for name each time, you can just set that in the factory declaration.

class FixedItemFactory(CleanModelFactory):
    class Meta:
        model = Item

    name = 'thing'

However, in this instance, you will receive ValidationErrors because name is expected to be unique.

>>> FixedItemFactory.create_batch(2)
Traceback (most recent call last):
...
django.core.exceptions.ValidationError: {'name': ['Item with this Name already exists.']}

full_clean is triggered only with the create strategy. Therefore using build followed by save can provide a way to emulate “bad” data in your Django database if that’s required. In this example, we can create an Item instance without a name.

>>> item = FixedItemFactory.build(name='')
>>> item.save()
>>> assert item.id

After saving successfully, if full_clean is called then the saved Item will fail validation because it does not have a name:

>>> item.full_clean()
Traceback (most recent call last):
...
django.core.exceptions.ValidationError: {'name': ['This field cannot be blank.']}

Side note: The ItemFactory example above is used in testing factory_djoy. The models.py can be found in test_framework and the tests can be found in the tests folder.

UserFactory

>>> from factory_djoy import UserFactory

UserFactory provides a simple wrapper over the django.contrib.auth.User model which validates the generated User instance with full_clean before it is saved. You can use it anywhere that you need a User instance to be created in your project’s factories.

Given a simple test that requires a User instance, UserFactory can generate that at test time. All validated fields have valid values created for them. This example is a bit contrived, but it works:

>>> from django.test import Client
>>> UserFactory(username='user_1', password='test')
>>> assert Client().login(username='user_1', password='test')

The field-level validation built in to UserFactory requires that the User.username field only contains certain permitted characters. Therefore UserFactory will raise ValidationError if it attempts to create a User instance with an invalid username, or any other field value:

>>> UserFactory(username='user name')
Traceback (most recent call last):
...
ValidationError: {'username': ['Enter a valid username. This value may contain only letters, numbers and @/./+/-/_ characters.']}

Same as with CleanModelFactory, the build strategy is available if tests require invalid data:

>>> UserFactory.build(username='user name').save()

Motivation: Testing first

Primarily the goal of factories is to provide “easy to generate” data at test time - however this data must be 100% reliable, otherwise it’s too easy to create false positive and false negative test results. By calling full_clean on every Django instance that is built, this helps to create certainty in the data used by tests - the instances will be valid as if they were created through the default Django admin.

Therefore, since it’s so important that each factory creates valid data, these wrappers are tested rigorously using Django projects configured in the test_framework folder.

Contribution

• Please see Issues. There are a number of outstanding tasks.

• Please ensure that any provided code:

  • Has been developed with “test first” process.

  • Can be auto-merged in GitHub.

  • Passes testing on Circle CI.

• Check out the development documentation for info on how to build, test and upload.

See also

• django-factory_boy which implements more factories for Django’s stock models, but doesn’t validate generated instances and has less tests.

• Django Factory Audit which compares every Django factory library I could find with respect to how they create valid instances.

• Django’s model save vs full_clean for an explanation of how Django can screw up your data when saving.