Metadata-Version: 1.0
Name: django-anonymizer
Version: 0.1.1
Summary: App to anonymize data in Django models.
Home-page: https://bitbucket.org/spookylukey/django-anonymizer/
Author: Luke Plant
Author-email: L.Plant.98@cantab.net
License: MIT
Description: ===================
         Django Anonymizer
        ===================
        
        This app aims to help you anonymize data in a database used for development.
        
        It is common practice in develpment to use a database that is very similar in
        content to the real data. The problem is that this can lead to have copies of
        sensitive customer data on development machines (and backups etc). This Django
        app helps by giving an easy and customizable way to anonymize data in your
        models.
        
        The basic method is go through all the models that you specify, and generate
        fake data for all the fields specified. Introspection of the models will produce
        an anonymizer that will attempt to provide sensible fake data for each field,
        leaving you to fill in the gaps.
        
        Please note that the methods provided will not provide full anonymity. Even if
        you anonymize the names and other details of your customers, there may well be
        enough data to identify them. Relationships between records in the database are
        not altered, in order to preserve the characteristic structure of data in your
        application, but this may leave you open to information leaks which might not be
        acceptable for your data. This application **should** be good enough for simpler
        policies like 'remove all real telephone numbers from the database'.
        
        Usage:
        
        * Install using setup.py or pip/easy_install.
        
        * Add 'anonymizer' to your ``INSTALLED_APPS`` setting.
        
        * To create some stub files for your anonymizers, do::
        
            ./manage.py create_anonymizers app_name1 [app_name2...]
        
          This will create a file ``anonymizers.py`` in each of the apps you specify.
          (It will not overwrite existing files).
        
          The file will contain autogenerated classes that attempt to use appropriate
          functions for generating fake data.
        
        * Edit the generated ``anonymizers.py`` files, filling out the details, and
          adding any filtering. You can override any of the public methods defined in
          ``anonymizer.base.Anonymizer`` in order to do filtering and other
          customization.
        
          The 'attributes' dictionary is the key attribute to edit. The keys are the
          attribute names of attributes on the model that need to be set.  The values
          are either strings (as a shortcut, see below), or callables that take the
          following arguments:
        
          * The Anonymizer instance
          * The object being edited.
          * The field being edited
          * The current value of the field.
        
        
          The Anonymizer instance has an attribute 'faker' attribute which is useful for
          generating faked data.
        
          If the value is a string, e.g. 'email', it is turned into a lambda
          as follows::
        
             lambda self, obj, field, val: self.faker.email(field=field)
        
          For some fields, you will want to remove them from the list of attributes, so
          that the values will be unchanged - especially things like denormalised
          fields. You may need to override the 'alter_object' to fix up any fields like
          that.
        
          An example Anonymizer for django.contrib.auth.models.User might look like
          this::
        
              from datetime import datetime
        
              from anonymizer import Anonymizer
              from django.contrib.auth.models import User
        
              class UserAnonymizer(Anonymizer):
        
                  model = User
        
                  attributes = {
                      'username':   'username',
                      'first_name': 'first_name',
                      'last_name':  'last_name',
                      'email':      'email',
                      # Set the date_joined to a similar time to when they actually
                      # joined, by passing the 'val' parameter to faker.datetime
                      'date_joined': lambda self, obj, field, val: self.faker.datetime(field=field, val=val),
                      # Set to today:
                      'last_login': lambda *args: datetime.now()
                  }
        
                  def alter_object(self, obj):
                      if obj.is_superuser:
                          return False # don't change, so we can still log in.
                      super(UserAnonymizer, self).alter_object(obj)
                      # Destroy all passwords for everyone else
                      obj.set_unusable_password()
        
        * If you need to create anonymizers for apps that you do not control, you may
          want to move the contents of the anonymizers.py file to an app that you **do**
          control. It doesn't matter if the anonymizer classes are for models that do
          not correspond to the applications they are contained it.
        
          (For example, if you want to anonymize the models in django.contrib.auth, you
          will probably want to move the contents of django/contrib/auth/anonymizers.py
          into yourprojectapp/anonymizers.py)
        
        * To run the anonymizers, do::
        
            ./manage.py anonymize_data app_name1 [app_name2...]
        
          This will DESTRUCTIVELY UPDATE all your data. Make sure you have backups,
          use at own risk, yada yada.
        
        
        
        Version 0.1.1
        -------------
        
        * Removed some debug code
        * Better handling of SlugField and skipped fields in introspection
        
        Version 0.1
        -----------
        
        Initial release
        
        
        
Keywords: django data database anonymize private
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Web Environment
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Framework :: Django
Classifier: Topic :: Software Development :: Testing
Classifier: Topic :: Database
