Built-in functions

import anon

anon.fake_word(min_size=_min_word_size, max_size=20)
anon.fake_text(max_size=255, max_diff_allowed=5, separator=' ')
anon.fake_small_text(max_size=50)
anon.fake_name(max_size=15)
anon.fake_username(max_size=10, separator='')
anon.fake_email(max_size=40, suffix='@example.com')
anon.fake_url(max_size=50, scheme='http://', suffix='.com')
anon.fake_phone_number(format='999-999-9999')

Lazy attributes

Lazy attributes can be defined as inline lambdas or methods, as shown below, using the anon.lazy_attribute function/decorator.

import anon

from your_app.models import Person

class PersonAnonymizer(anon.BaseAnonymizer):
   name = anon.lazy_attribute(lambda o: 'x' * len(o.name))

   @lazy_attribute
   def date_of_birth(self):
      # keep year and month
      return self.date_of_birth.replace(day=1)

   class Meta:
      model = Person

The clean method

import anon

class UserAnonymizer(anon.BaseAnonymizer):
   class Meta:
      model = User

   def clean(self, obj):
      obj.set_password('test')
      obj.save()

Defining a custom QuerySet

A custom QuerySet can be used to select the rows that should be anonymized:

import anon

from your_app.models import Person

class PersonAnonymizer(anon.BaseAnonymizer):
   email = anon.fake_email

   class Meta:
      model = Person

   def get_queryset(self):
      # keep admins unmodified
      return Person.objects.exclude(is_admin=True)

High-quality fake data

In order to be really fast, django-anon uses it’s own algorithm to generate fake data. It is really fast, but the generated data is not pretty. If you need something prettier in terms of data, we suggest using Faker, which can be used out-of-the-box as the below:

import anon

from faker import Faker
from your_app.models import Address

faker = Faker()

class PersonAnonymizer(anon.BaseAnonymizer):
   postalcode = faker.postalcode

   class Meta:
      model = Address