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        "author": "Tesorio",
        "author_email": "hello@tesorio.com",
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            "Development Status :: 5 - Production/Stable",
            "Framework :: Django",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 3"
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        "description": "\n**django-anon** will help you anonymize your production database so it can be\nshared among developers, helping to reproduce bugs and make performance improvements\nin a production-like environment.\n\n.. image:: https://raw.githubusercontent.com/Tesorio/django-anon/master/django-anon-recording.gif\n\n.. start-features\n\nFeatures\n========\n\n.. start-features-table\n\n.. csv-table::\n\n   \"\ud83d\ude80\", \"**Really fast** data anonymization and database operations using bulk updates to operate over huge tables\"\n   \"\ud83c\udf70\", \"**Flexible** to use your own anonymization functions or external libraries like `Faker <https://faker.readthedocs.io/en/latest/index.html>`_\"\n   \"\ud83d\udc29\", \"**Elegant** solution following consolidated patterns from projects like `Django <https://djangoproject.com/>`_ and `Factory Boy <https://factoryboy.readthedocs.io/en/latest/index.html>`_\"\n   \"\ud83d\udd28\", \"**Powerful**. It can be used on any projects, not only Django, not only Python. Really!\"\n\n.. end-features-table\n.. end-features\n.. start-table-of-contents\n\nTable of Contents\n=================\n.. contents::\n   :local:\n\n.. end-table-of-contents\n.. start-introduction\n\n\nInstallation\n------------\n\n.. code::\n\n   pip install django-anon\n\n\nSupported versions\n------------------\n\n* Python (2.7, 3.7)\n* Django (1.8, 1.11, 2.2, 3.0)\n\n\nLicense\n-------\n\n`MIT <https://github.com/Tesorio/django-anon/blob/master/LICENSE>`_\n\n.. end-introduction\n.. start-usage\n\n\nUsage\n-----\n\nUse ``anon.BaseAnonymizer`` to define your anonymizer classes:\n\n.. code-block:: python\n\n   import anon\n\n   from your_app.models import Person\n\n   class PersonAnonymizer(anon.BaseAnonymizer):\n      email = anon.fake_email\n\n      # You can use static values instead of callables\n      is_admin = False\n\n      class Meta:\n         model = Person\n\n   # run anonymizer: be cautious, this will affect your current database!\n   PersonAnonymizer().run()\n\n\nBuilt-in functions\n~~~~~~~~~~~~~~~~~~\n\n.. code:: python\n\n   import anon\n\n   anon.fake_word(min_size=_min_word_size, max_size=20)\n   anon.fake_text(max_size=255, max_diff_allowed=5, separator=' ')\n   anon.fake_small_text(max_size=50)\n   anon.fake_name(max_size=15)\n   anon.fake_username(max_size=10, separator='')\n   anon.fake_email(max_size=40, suffix='@example.com')\n   anon.fake_url(max_size=50, scheme='http://', suffix='.com')\n   anon.fake_phone_number(format='999-999-9999')\n\n\nLazy attributes\n~~~~~~~~~~~~~~~\n\nLazy attributes can be defined as inline lambdas or methods, as shown below,\nusing the ``anon.lazy_attribute`` function/decorator.\n\n.. code-block:: python\n\n   import anon\n\n   from your_app.models import Person\n\n   class PersonAnonymizer(anon.BaseAnonymizer):\n      name = anon.lazy_attribute(lambda o: 'x' * len(o.name))\n\n      @lazy_attribute\n      def date_of_birth(self):\n         # keep year and month\n         return self.date_of_birth.replace(day=1)\n\n      class Meta:\n         model = Person\n\n\nThe clean method\n~~~~~~~~~~~~~~~~\n\n.. code-block:: python\n\n   import anon\n\n   class UserAnonymizer(anon.BaseAnonymizer):\n      class Meta:\n         model = User\n\n      def clean(self, obj):\n         obj.set_password('test')\n         obj.save()\n\n\nDefining a custom QuerySet\n~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nA custom QuerySet can be used to select the rows that should be anonymized:\n\n.. code-block:: python\n\n   import anon\n\n   from your_app.models import Person\n\n   class PersonAnonymizer(anon.BaseAnonymizer):\n      email = anon.fake_email\n\n      class Meta:\n         model = Person\n\n      def get_queryset(self):\n         # keep admins unmodified\n         return Person.objects.exclude(is_admin=True)\n\n\nHigh-quality fake data\n~~~~~~~~~~~~~~~~~~~~~~\n\nIn order to be really fast, **django-anon** uses it's own algorithm to generate fake data. It is\nreally fast, but the generated data is not pretty. If you need something prettier in terms of data,\nwe suggest using `Faker <https://faker.readthedocs.io/en/latest/index.html>`_, which can be used\nout-of-the-box as the below:\n\n.. code-block:: python\n\n   import anon\n\n   from faker import Faker\n   from your_app.models import Address\n\n   faker = Faker()\n\n   class PersonAnonymizer(anon.BaseAnonymizer):\n      postalcode = faker.postalcode\n\n      class Meta:\n         model = Address\n\n.. end-usage\n\nChangelog\n---------\n\nCheck out `CHANGELOG.rst <https://github.com/Tesorio/django-anon/blob/master/CHANGELOG.rst>`_ for release notes\n\nContributing\n------------\n\nCheck out `CONTRIBUTING.rst <https://github.com/Tesorio/django-anon/blob/master/CONTRIBUTING.rst>`_ for information about getting involved\n\n----\n\n`Icon <icon.svg>`_ made by `Eucalyp <https://www.flaticon.com/authors/eucalyp>`_ from `www.flaticon.com <https://www.flaticon.com/>`_\n\n\n",
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