django/docs/testing.txt

===========================
Testing Django applications
===========================

Automated testing is an extremely useful bug-killing tool for the modern
Web developer. You can use a collection of tests -- a **test suite** -- to
solve, or avoid, a number of problems:

    * When you're writing new code, you can use tests to validate your code
      works as expected.

    * When you're refactoring or modifying old code, you can use tests to
      ensure your changes haven't affected your application's behavior
      unexpectedly.

Testing a Web application is a complex task, because a Web application is made
of several layers of logic -- from HTTP-level request handling, to form
validation and processing, to template rendering. With Django's test-execution
framework and assorted utilities, you can simulate requests, insert test data,
inspect your application's output and generally verify your code is doing what
it should be doing.

The best part is, it's really easy.

This document is split into two primary sections. First, we explain how to
write tests with Django. Then, we explain how to run them.

.. admonition:: Note

    This testing framework is currently under development. It may change
    slightly before the next official Django release.

    (That's *no* excuse not to write tests, though!)

Writing tests
=============

There are two primary ways to write tests with Django, corresponding to the
two test frameworks that ship in the Python standard library. The two
frameworks are:

    * **Doctests** -- tests that are embedded in your functions' docstrings and
      are written in a way that emulates a session of the Python interactive
      interpreter. For example::

          def my_func(a_list, idx):
              """
              >>> a = ['larry', 'curly', 'moe']
              >>> my_func(a, 0)
              'larry'
              >>> my_func(a, 1)
              'curly'
              """
              return a_list[idx]

    * **Unit tests** -- tests that are expressed as methods on a Python class
      that subclasses ``unittest.TestCase``. For example::

          import unittest

          class MyFuncTestCase(unittest.TestCase)
              def testBasic(self):
                  a = ['larry', 'curly', 'moe']
                  self.assertEquals(my_func(a, 0), 'larry')
                  self.assertEquals(my_func(a, 1), 'curly')

You can choose the test framework you like, depending on which syntax you
prefer, or you can mix and match, using one framework for some of your code and
the other framework for other code. You can also use any *other* Python test
frameworks, as we'll explain in a bit.

Writing doctests
----------------

Doctests use Python's standard doctest_ module, which searches your docstrings
for statements that resemble a session of the Python interactive interpreter.
A full explanation of how doctest works is out of the scope of this document;
read Python's official documentation for the details.

.. admonition:: What's a **docstring**?

    A good explanation of docstrings (and some guidelines for using them
    effectively) can be found in :PEP:`257`:

        A docstring is a string literal that occurs as the first statement in
        a module, function, class, or method definition.  Such a docstring
        becomes the ``__doc__`` special attribute of that object.

    For example, this function has a docstring that describes what it does::

        def add_two(num):
            "Adds 2 to the given number and returns the result."
            return num + 2

    Because tests often make great documentation, putting tests directly in
    your docstrings is an effective way to document *and* test your code.

For a given Django application, the test runner looks for doctests in two
places:

    * The ``models.py`` file. You can define module-level doctests and/or a
      doctest for individual models. It's common practice to put
      application-level doctests in the module docstring and model-level
      doctests in the model docstrings.

    * A file called ``tests.py`` in the application directory -- i.e., the
      directory that holds ``models.py``. This file is a hook for any and all
      doctests you want to write that aren't necessarily related to models.

Here is an example model doctest::

    # models.py

    from django.db import models

    class Animal(models.Model):
        """
        An animal that knows how to make noise

        # Create some animals
        >>> lion = Animal.objects.create(name="lion", sound="roar")
        >>> cat = Animal.objects.create(name="cat", sound="meow")

        # Make 'em speak
        >>> lion.speak()
        'The lion says "roar"'
        >>> cat.speak()
        'The cat says "meow"'
        """
        name = models.CharField(max_length=20)
        sound = models.CharField(max_length=20)

        def speak(self):
            return 'The %s says "%s"' % (self.name, self.sound)

When you `run your tests`_, the test runner will find this docstring, notice
that portions of it look like an interactive Python session, and execute those
lines while checking that the results match.

In the case of model tests, note that the test runner takes care of creating
its own test database. That is, any test that accesses a database -- by
creating and saving model instances, for example -- will not affect your
production database. Each doctest begins with a "blank slate" -- a fresh
database containing an empty table for each model. (See the section on
fixtures, below, for more on this.)

For more details about how doctest works, see the `standard library
documentation for doctest`_

.. _doctest: http://docs.python.org/lib/module-doctest.html
.. _standard library documentation for doctest: doctest_

Writing unit tests
------------------

Like doctests, Django's unit tests use a standard library module: unittest_.
This module uses a different way of defining tests, taking a class-based
approach.

As with doctests, for a given Django application, the test runner looks for
unit tests in two places:

    * The ``models.py`` file. The test runner looks for any subclass of
      ``unittest.TestCase`` in this module.

    * A file called ``tests.py`` in the application directory -- i.e., the
      directory that holds ``models.py``. Again, the test runner looks for any
      subclass of ``unittest.TestCase`` in this module.

This example ``unittest.TestCase`` subclass is equivalent to the example given
in the doctest section above::

    import unittest
    from myapp.models import Animal

    class AnimalTestCase(unittest.TestCase):
        def setUp(self):
            self.lion = Animal.objects.create(name="lion", sound="roar")
            self.cat = Animal.objects.create(name="cat", sound="meow")

        def testSpeaking(self):
            self.assertEquals(self.lion.speak(), 'The lion says "roar"')
            self.assertEquals(self.cat.speak(), 'The cat says "meow"')

When you `run your tests`_, the default behavior of the test utility is
to find all the test cases (that is, subclasses of ``unittest.TestCase``)
in ``models.py`` and ``tests.py``, automatically build a test suite out of
those test cases, and run that suite.

In the Django development version, there is a second way to define the test
suite for a module: if you define a function called ``suite()`` in either
``models.py`` or ``tests.py``, the Django test runner will use that function
to construct the test suite for that module. This follows the
`suggested organization`_ for unit tests. See the Python documentation for
more details on how to construct a complex test suite.

For more details about ``unittest``, see the `standard library unittest
documentation`_.

.. _unittest: http://docs.python.org/lib/module-unittest.html
.. _standard library unittest documentation: unittest_
.. _run your tests: `Running tests`_
.. _suggested organization: http://docs.python.org/lib/organizing-tests.html

Which should I use?
-------------------

Because Django supports both of the standard Python test frameworks, it's up to
you and your tastes to decide which one to use. You can even decide to use
*both*.

For developers new to testing, however, this choice can seem confusing. Here,
then, are a few key differences to help you decide which approach is right for
you:

    * If you've been using Python for a while, ``doctest`` will probably feel
      more "pythonic". It's designed to make writing tests as easy as possible,
      so it requires no overhead of writing classes or methods. You simply put
      tests in docstrings. This has the added advantage of serving as
      documentation (and correct documentation, at that!).

      If you're just getting started with testing, using doctests will probably
      get you started faster.

    * The ``unittest`` framework will probably feel very familiar to developers
      coming from Java. ``unittest`` is inspired by Java's JUnit, so you'll
      feel at home with this method if you've used JUnit or any test framework
      inspired by JUnit.

    * If you need to write a bunch of tests that share similar code, then
      you'll appreciate the ``unittest`` framework's organization around
      classes and methods. This makes it easy to abstract common tasks into
      common methods. The framework also supports explicit setup and/or cleanup
      routines, which give you a high level of control over the environment
      in which your test cases are run.

Again, remember that you can use both systems side-by-side (even in the same
app). In the end, most projects will eventually end up using both. Each shines
in different circumstances.

Running tests
=============

Once you've written tests, run them using your project's ``manage.py`` utility::

    $ ./manage.py test

By default, this will run every test in every application in ``INSTALLED_APPS``.
If you only want to run tests for a particular application, add the
application name to the command line. For example, if your ``INSTALLED_APPS``
contains ``'myproject.polls'`` and ``'myproject.animals'``, you can run the
``myproject.animals`` unit tests alone with this command::

    # ./manage.py test animals

Note that we used ``animals``, not ``myproject.animals``.

**New in Django development version:** If you use unit tests, as opposed to
doctests, you can be even *more* specific in choosing which tests to execute.
To run a single test case in an application (for example, the
``AnimalTestCase`` described in the "Writing unit tests" section), add the
name of the test case to the label on the command line::

    $ ./manage.py test animals.AnimalTestCase

And it gets even more granular than that! To run a *single* test method inside
a test case, add the name of the test method to the label::

    $ ./manage.py test animals.AnimalTestCase.testFluffyAnimals

Understanding the test output
-----------------------------

When you run your tests, you'll see a number of messages as the test runner
prepares itself::

    Creating test database...
    Creating table myapp_animal
    Creating table myapp_mineral
    Loading 'initial_data' fixtures...
    No fixtures found.

This tells you that the test runner is creating a test database -- a blank,
from-scratch database that it will use for any tests that happen to require a
database (namely, model tests).

Don't worry -- the test runner will not touch your "real" (production)
database. It creates a separate database purely for the tests. This test
database gets its name by prepending ``test_`` to the value of the
``DATABASE_NAME`` setting. If you want to use a different name, specify the
``TEST_DATABASE_NAME`` setting.

Aside from using a separate database, the test runner will otherwise use all of
the same database settings you have in your settings file: ``DATABASE_ENGINE``,
``DATABASE_USER``, ``DATABASE_HOST``, etc. The test database is created by the
user specified by ``DATABASE_USER``, so you'll need to make sure that the given
user account has sufficient privileges to create a new database on the system.

**New in Django development version:** For fine-grained control over the
character encoding of your test database, use the ``TEST_DATABASE_CHARSET``
setting. If you're using MySQL, you can also use the ``TEST_DATABASE_COLLATION``
setting to control the particular collation used by the test database. See the
settings_ documentation for details of these advanced settings.

.. _settings: ../settings/

Once the test database has been created, Django will run your tests.
If everything goes well, you'll see something like this::

    ----------------------------------------------------------------------
    Ran 22 tests in 0.221s

    OK

If there are test failures, however, you'll see full details about which tests
failed::

    ======================================================================
    FAIL: Doctest: ellington.core.throttle.models
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/dev/django/test/doctest.py", line 2153, in runTest
        raise self.failureException(self.format_failure(new.getvalue()))
    AssertionError: Failed doctest test for myapp.models
      File "/dev/myapp/models.py", line 0, in models

    ----------------------------------------------------------------------
    File "/dev/myapp/models.py", line 14, in myapp.models
    Failed example:
        throttle.check("actor A", "action one", limit=2, hours=1)
    Expected:
        True
    Got:
        False

    ----------------------------------------------------------------------
    Ran 2 tests in 0.048s

    FAILED (failures=1)

A full explanation of this error output is beyond the scope of this document,
but it's pretty intuitive. You can consult the documentation of Python's
``unittest`` library for details.

Note that the return code for the test-runner script is the total number of
failed and erroneous tests. If all the tests pass, the return code is 0. This
feature is useful if you're using the test-runner script in a shell script and
need to test for success or failure at that level.

Regardless of whether the tests pass or fail, the test database is destroyed when
all the tests have been executed.

Testing tools
=============

Django provides a small set of tools that come in handy when writing tests.

The test client
---------------

The test client is a Python class that acts as a dummy Web browser, allowing
you to test your views and interact with your Django-powered application
programatically.

Some of the things you can do with the test client are:

    * Simulate GET and POST requests on a URL and observe the response --
      everything from low-level HTTP (result headers and status codes) to
      page content.

    * Test that the correct view is executed for a given URL.

    * Test that a given request is rendered by a given Django template, with
      a template context that contains certain values.

Note that the test client is not intended to be a replacement for Twill_,
Selenium_, or other "in-browser" frameworks. Django's test client has
a different focus. In short:

    * Use Django's test client to establish that the correct view is being
      called and that the view is collecting the correct context data.

    * Use in-browser frameworks such as Twill and Selenium to test *rendered*
      HTML and the *behavior* of Web pages, namely JavaScript functionality.

A comprehensive test suite should use a combination of both test types.

.. _Twill: http://twill.idyll.org/
.. _Selenium: http://www.openqa.org/selenium/

Overview and a quick example
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To use the test client, instantiate ``django.test.client.Client`` and retrieve
Web pages::

    >>> from django.test.client import Client
    >>> c = Client()
    >>> response = c.post('/login/', {'username': 'john', 'password': 'smith'})
    >>> response.status_code
    200
    >>> response = c.get('/customer/details/')
    >>> response.content
    '<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 ...'

As this example suggests, you can instantiate ``Client`` from within a session
of the Python interactive interpreter.

Note a few important things about how the test client works:

    * The test client does *not* require the Web server to be running. In fact,
      it will run just fine with no Web server running at all! That's because
      it avoids the overhead of HTTP and deals directly with the Django
      framework. This helps make the unit tests run quickly.

    * When retrieving pages, remember to specify the *path* of the URL, not the
      whole domain. For example, this is correct::

          >>> c.get('/login/')

      This is incorrect::

          >>> c.get('http://www.example.com/login/')

      The test client is not capable of retrieving Web pages that are not
      powered by your Django project. If you need to retrieve other Web pages,
      use a Python standard library module such as urllib_ or urllib2_.

    * To resolve URLs, the test client uses whatever URLconf is pointed-to by
      your ``ROOT_URLCONF`` setting.

    * Although the above example would work in the Python interactive
      interpreter, some of the test client's functionality, notably the
      template-related functionality, is only available *while tests are running*.

      The reason for this is that Django's test runner performs a bit of black
      magic in order to determine which template was loaded by a given view.
      This black magic (essentially a patching of Django's template system in
      memory) only happens during test running.

.. _urllib: http://docs.python.org/lib/module-urllib.html
.. _urllib2: http://docs.python.org/lib/module-urllib2.html

Making requests
~~~~~~~~~~~~~~~

Use the ``django.test.client.Client`` class to make requests. It requires no
arguments at time of construction::

    >>> c = Client()

Once you have a ``Client`` instance, you can call any of the following methods:

``get(path, data={})``
    Makes a GET request on the provided ``path`` and returns a ``Response``
    object, which is documented below.

    The key-value pairs in the ``data`` dictionary are used to create a GET
    data payload. For example::

        >>> c = Client()
        >>> c.get('/customers/details/', {'name': 'fred', 'age': 7})

    ...will result in the evaluation of a GET request equivalent to::

        /customers/details/?name=fred&age=7

``post(path, data={}, content_type=MULTIPART_CONTENT)``
    Makes a POST request on the provided ``path`` and returns a ``Response``
    object, which is documented below.

    The key-value pairs in the ``data`` dictionary are used to submit POST
    data. For example::

        >>> c = Client()
        >>> c.post('/login/', {'name': 'fred', 'passwd': 'secret'})

    ...will result in the evaluation of a POST request to this URL::

        /login/

    ...with this POST data::

        name=fred&passwd=secret

    If you provide ``content_type`` (e.g., ``text/xml`` for an XML payload),
    the contents of ``data`` will be sent as-is in the POST request, using
    ``content_type`` in the HTTP ``Content-Type`` header.

    If you don't provide a value for ``content_type``, the values in
    ``data`` will be transmitted with a content type of ``multipart/form-data``.
    In this case, the key-value pairs in ``data`` will be encoded as a
    multipart message and used to create the POST data payload.

    To submit multiple values for a given key -- for example, to specify
    the selections for a ``<select multiple>`` -- provide the values as a
    list or tuple for the required key. For example, this value of ``data``
    would submit three selected values for the field named ``choices``::

        {'choices': ('a', 'b', 'd')}

    Submitting files is a special case. To POST a file, you need only provide
    the file field name as a key, and a file handle to the file you wish to
    upload as a value. For example::

        >>> c = Client()
        >>> f = open('wishlist.doc')
        >>> c.post('/customers/wishes/', {'name': 'fred', 'attachment': f})
        >>> f.close()

    (The name ``attachment`` here is not relevant; use whatever name your
    file-processing code expects.)

    Note that you should manually close the file after it has been provided to
    ``post()``.

``login(**credentials)``
    **New in Django development version**

    If your site uses Django's `authentication system`_ and you deal with
    logging in users, you can use the test client's ``login()`` method to
    simulate the effect of a user logging into the site.

    After you call this method, the test client will have all the cookies and
    session data required to pass any login-based tests that may form part of
    a view.

    The format of the ``credentials`` argument depends on which
    `authentication backend`_ you're using (which is configured by your
    ``AUTHENTICATION_BACKENDS`` setting). If you're using the standard
    authentication backend provided by Django (``ModelBackend``),
    ``credentials`` should be the user's username and password, provided as
    keyword arguments::

        >>> c = Client()
        >>> c.login(username='fred', password='secret')
        >>> # Now you can access a view that's only available to logged-in users.

    If you're using a different authentication backend, this method may require
    different credentials. It requires whichever credentials are required by
    your backend's ``authenticate()`` method.

    ``login()`` returns ``True`` if it the credentials were accepted and login
    was successful.

    Finally, you'll need to remember to create user accounts before you can use
    this method. As we explained above, the test runner is executed using a
    test database, which contains no users by default. As a result, user
    accounts that are valid on your production site will not work under test
    conditions. You'll need to create users as part of the test suite -- either
    manually (using the Django model API) or with a test fixture.

``logout()``
    **New in Django development version**

    If your site uses Django's `authentication system`_, the ``logout()``
    method can be used to simulate the effect of a user logging out of
    your site.

    After you call this method, the test client will have all the cookies and
    session data cleared to defaults. Subsequent requests will appear to
    come from an AnonymousUser.

.. _authentication system: ../authentication/
.. _authentication backend: ../authentication/#other-authentication-sources

Testing responses
~~~~~~~~~~~~~~~~~

The ``get()`` and ``post()`` methods both return a ``Response`` object. This
``Response`` object is *not* the same as the ``HttpResponse`` object returned
Django views; this object is simpler and has some additional data useful for
tests.

Specifically, a ``Response`` object has the following attributes:

    ===============  ==========================================================
    Attribute        Description
    ===============  ==========================================================
    ``client``       The test client that was used to make the request that
                     resulted in the response.

    ``content``      The body of the response, as a string. This is the final
                     page content as rendered by the view, or any error
                     message (such as the URL for a 302 redirect).

    ``context``      The template ``Context`` instance that was used to render
                     the template that produced the response content.

                     If the rendered page used multiple templates, then
                     ``context`` will be a list of ``Context``
                     objects, in the order in which they were rendered.

    ``request``      The request data that stimulated the response.

    ``status_code``  The HTTP status of the response, as an integer. See
                     RFC2616_ for a full list of HTTP status codes.

    ``template``     The ``Template`` instance that was used to render the
                     final content. Use ``template.name`` to get the
                     template's file name, if the template was loaded from a
                     file. (The name is a string such as
                     ``'admin/index.html'``.)

                     If the rendered page used multiple templates -- e.g.,
                     using `template inheritance`_ -- then ``template`` will
                     be a list of ``Template`` instances, in the order in
                     which they were rendered.
    ===============  ==========================================================

.. _RFC2616: http://www.w3.org/Protocols/rfc2616/rfc2616-sec10.html
.. _template inheritance: ../templates/#template-inheritance

Exceptions
~~~~~~~~~~

If you point the test client at a view that raises an exception, that exception
will be visible in the test case. You can then use a standard ``try...catch``
block or ``unittest.TestCase.assertRaises()`` to test for exceptions.

The only exceptions that are not visible to the test client are ``Http404``,
``PermissionDenied`` and ``SystemExit``. Django catches these exceptions
internally and converts them into the appropriate HTTP response codes. In these
cases, you can check ``response.status_code`` in your test.

Persistent state
~~~~~~~~~~~~~~~~

The test client is stateful. If a response returns a cookie, then that cookie
will be stored in the test client and sent with all subsequent ``get()`` and
``post()`` requests.

Expiration policies for these cookies are not followed. If you want a cookie
to expire, either delete it manually or create a new ``Client`` instance (which
will effectively delete all cookies).

A test client has two attributes that store persistent state information. You
can access these properties as part of a test condition.

    ===============  ==========================================================
    Attribute        Description
    ===============  ==========================================================
    ``cookies``      A Python ``SimpleCookie`` object, containing the current
                     values of all the client cookies. See the
                     `Cookie module documentation`_ for more.

    ``session``      A dictionary-like object containing session information.
                     See the `session documentation`_ for full details.
    ===============  ==========================================================

.. _Cookie module documentation: http://docs.python.org/lib/module-Cookie.html
.. _session documentation: ../sessions/

Example
~~~~~~~

The following is a simple unit test using the test client::

    import unittest
    from django.test.client import Client

    class SimpleTest(unittest.TestCase):
        def setUp(self):
            # Every test needs a client.
            self.client = Client()

        def test_details(self):
            # Issue a GET request.
            response = self.client.get('/customer/details/')

            # Check that the respose is 200 OK.
            self.failUnlessEqual(response.status_code, 200)

            # Check that the rendered context contains 5 customers.
            self.failUnlessEqual(len(response.context['customers']), 5)

TestCase
--------

Normal Python unit test classes extend a base class of ``unittest.TestCase``.
Django provides an extension of this base class -- ``django.test.TestCase``
-- that provides some additional capabilities that can be useful for
testing Web sites.

Converting a normal ``unittest.TestCase`` to a Django ``TestCase`` is easy:
just change the base class of your test from ``unittest.TestCase`` to
``django.test.TestCase``. All of the standard Python unit test functionality
will continue to be available, but it will be augmented with some useful
additions.

Default test client
~~~~~~~~~~~~~~~~~~~

**New in Django development version**

Every test case in a ``django.test.TestCase`` instance has access to an
instance of a Django test client. This client can be accessed as
``self.client``. This client is recreated for each test, so you don't have to
worry about state (such as cookies) carrying over from one test to another.

This means, instead of instantiating a ``Client`` in each test::

    import unittest
    from django.test.client import Client

    class SimpleTest(unittest.TestCase):
        def test_details(self):
            client = Client()
            response = client.get('/customer/details/')
            self.failUnlessEqual(response.status_code, 200)

        def test_index(self):
            client = Client()
            response = client.get('/customer/index/')
            self.failUnlessEqual(response.status_code, 200)

...you can just refer to ``self.client``, like so::

    from django.test import TestCase
    from django.test.client import Client

    class SimpleTest(TestCase):
        def test_details(self):
            response = self.client.get('/customer/details/')
            self.failUnlessEqual(response.status_code, 200)

        def test_index(self):
            response = self.client.get('/customer/index/')
            self.failUnlessEqual(response.status_code, 200)

Fixture loading
~~~~~~~~~~~~~~~

A test case for a database-backed Web site isn't much use if there isn't any
data in the database. To make it easy to put test data into the database,
Django's custom ``TestCase`` class provides a way of loading **fixtures**.

A fixture is a collection of data that Django knows how to import into a
database. For example, if your site has user accounts, you might set up a
fixture of fake user accounts in order to populate your database during tests.

The most straightforward way of creating a fixture is to use the
``manage.py dumpdata`` command. This assumes you already have some data in
your database. See the `dumpdata documentation`_ for more details.

.. note::
    If you've ever run ``manage.py syncdb``, you've already used a fixture
    without even knowing it! When you call ``syncdb`` in the database for
    the first time, Django installs a fixture called ``initial_data``.
    This gives you a way of populating a new database with any initial data,
    such as a default set of categories.

    Fixtures with other names can always be installed manually using the
    ``manage.py loaddata`` command.

Once you've created a fixture and placed it somewhere in your Django project,
you can use it in your unit tests by specifying a ``fixtures`` class attribute
on your ``django.test.TestCase`` subclass::

    from django.test import TestCase
    from myapp.models import Animal

    class AnimalTestCase(TestCase):
        fixtures = ['mammals.json', 'birds']

        def setUp(self):
            # Test definitions as before.

        def testFluffyAnimals(self):
            # A test that uses the fixtures.

Here's specifically what will happen:

    * At the start of each test case, before ``setUp()`` is run, Django will
      flush the database, returning the database to the state it was in
      directly after ``syncdb`` was called.

    * Then, all the named fixtures are installed. In this example, Django will
      install any JSON fixture named ``mammals``, followed by any fixture named
      ``birds``. See the `loaddata documentation`_ for more details on defining
      and installing fixtures.

This flush/load procedure is repeated for each test in the test case, so you
can be certain that the outcome of a test will not be affected by
another test, or by the order of test execution.

.. _dumpdata documentation: ../django-admin/#dumpdata-appname-appname
.. _loaddata documentation: ../django-admin/#loaddata-fixture-fixture

Emptying the test outbox
~~~~~~~~~~~~~~~~~~~~~~~~

**New in Django development version**

If you use Django's custom ``TestCase`` class, the test runner will clear the
contents of the test e-mail outbox at the start of each test case.

For more detail on e-mail services during tests, see `E-mail services`_.

Assertions
~~~~~~~~~~

**New in Django development version**

As Python's normal ``unittest.TestCase`` class implements assertion
methods such as ``assertTrue`` and ``assertEquals``, Django's custom
``TestCase`` class provides a number of custom assertion methods that are
useful for testing Web applications:

``assertContains(response, text, count=None, status_code=200)``
    Asserts that a ``Response`` instance produced the given ``status_code`` and
    that ``text`` appears in the content of the response. If ``count`` is
    provided, ``text`` must occur exactly ``count`` times in the response.

``assertFormError(response, form, field, errors)``
    Asserts that a field on a form raises the provided list of errors when
    rendered on the form.

    ``form`` is the name the ``Form`` instance was given in the template
    context. Note that this works only for ``newforms.Form`` instances, not
    ``oldforms.Form`` instances.

    ``field`` is the name of the field on the form to check. If ``field``
    has a value of ``None``, non-field errors (errors you can access via
    ``form.non_field_errors()``) will be checked.

    ``errors`` is an error string, or a list of error strings, that are
    expected as a result of form validation.

``assertTemplateNotUsed(response, template_name)``
    Asserts that the template with the given name was *not* used in rendering
    the response.

``assertRedirects(response, expected_url, status_code=302, target_status_code=200)``
    Asserts that the response return a ``status_code`` redirect status,
    it redirected to ``expected_url`` (including any GET data), and the subsequent
    page was received with ``target_status_code``.

``assertTemplateUsed(response, template_name)``
    Asserts that the template with the given name was used in rendering the
    response.

    The name is a string such as ``'admin/index.html'``.

E-mail services
---------------

**New in Django development version**

If any of your Django views send e-mail using `Django's e-mail functionality`_,
you probably don't want to send e-mail each time you run a test using that
view. For this reason, Django's test runner automatically redirects all
Django-sent e-mail to a dummy outbox. This lets you test every aspect of
sending e-mail -- from the number of messages sent to the contents of each
message -- without actually sending the messages.

The test runner accomplishes this by transparently replacing the normal
`SMTPConnection`_ class with a different version. (Don't worry -- this has no
effect on any other e-mail senders outside of Django, such as your machine's
mail server, if you're running one.)

During test running, each outgoing e-mail is saved in
``django.core.mail.outbox``. This is a simple list of all `EmailMessage`_
instances that have been sent. It does not exist under normal execution
conditions, i.e., when you're not running unit tests. The outbox is created
during test setup, along with the dummy `SMTPConnection`_. When the test
framework is torn down, the standard `SMTPConnection`_ class is restored, and
the test outbox is destroyed.

Here's an example test that examines ``django.core.mail.outbox`` for length
and contents::

    from django.core import mail
    from django.test import TestCase

    class EmailTest(TestCase):
        def test_send_email(self):
            # Send message.
            mail.send_mail('Subject here', 'Here is the message.',
                'from@example.com', ['to@example.com'],
                fail_silently=False)

            # Test that one message has been sent.
            self.assertEqual(len(mail.outbox), 1)

            # Verify that the subject of the first message is correct.
            self.assertEqual(mail.outbox[0].subject, 'Subject here')

As noted `previously`_, the test outbox is emptied at the start of every
test in a Django ``TestCase``. To empty the outbox manually, assign the
empty list to ``mail.outbox``::

    from django.core import mail

    # Empty the test outbox
    mail.outbox = []

.. _`Django's e-mail functionality`: ../email/
.. _`SMTPConnection`: ../email/#the-emailmessage-and-smtpconnection-classes
.. _`EmailMessage`: ../email/#the-emailmessage-and-smtpconnection-classes
.. _`previously`: #emptying-the-test-outbox

Using different testing frameworks
==================================

Clearly, ``doctest`` and ``unittest`` are not the only Python testing
frameworks. While Django doesn't provide explicit support for alternative
frameworks, it does provide a way to invoke tests constructed for an
alternative framework as if they were normal Django tests.

When you run ``./manage.py test``, Django looks at the ``TEST_RUNNER``
setting to determine what to do. By default, ``TEST_RUNNER`` points to
``'django.test.simple.run_tests'``. This method defines the default Django
testing behavior. This behavior involves:

    #. Performing global pre-test setup.

    #. Creating the test database.

    #. Running ``syncdb`` to install models and initial data into the test
       database.

    #. Looking for unit tests and doctests in the ``models.py`` and
       ``tests.py`` files in each installed application.

    #. Running the unit tests and doctests that are found.

    #. Destroying the test database.

    #. Performing global post-test teardown.

If you define your own test runner method and point ``TEST_RUNNER`` at that
method, Django will execute your test runner whenever you run
``./manage.py test``. In this way, it is possible to use any test framework
that can be executed from Python code.

Defining a test runner
----------------------

**New in Django development version**

By convention, a test runner should be called ``run_tests``. The only strict
requirement is that it has the same arguments as the Django test runner:

``run_tests(test_labels, verbosity=1, interactive=True, extra_tests=[])``

    ``test_labels`` is a list of strings describing the tests to be run. A test
    label can take one of three forms:

        * ``app.TestCase.test_method`` -- Run a single test method in a test case.
        * ``app.TestCase`` -- Run all the test methods in a test case.
        * ``app`` -- Search for and run all tests in the named application.

    If ``test_labels`` has a value of ``None``, the test runner should run
    search for tests in all the applications in ``INSTALLED_APPS``.

    ``verbosity`` determines the amount of notification and debug information
    that will be printed to the console; ``0`` is no output, ``1`` is normal
    output, and ``2`` is verbose output.

    If ``interactive`` is ``True``, the test suite has permission to ask the
    user for instructions when the test suite is executed. An example of this
    behavior would be asking for permission to delete an existing test
    database. If ``interactive`` is ``False``, the test suite must be able to
    run without any manual intervention.

    ``extra_tests`` is a list of extra ``TestCase`` instances to add to the
    suite that is executed by the test runner. These extra tests are run
    in addition to those discovered in the modules listed in ``module_list``.

    This method should return the number of tests that failed.

Testing utilities
-----------------

To assist in the creation of your own test runner, Django provides
a number of utility methods in the ``django.test.utils`` module.

``setup_test_environment()``
    Performs any global pre-test setup, such as the installing the
    instrumentation of the template rendering system and setting up
    the dummy ``SMTPConnection``.

``teardown_test_environment()``
    Performs any global post-test teardown, such as removing the
    black magic hooks into the template system and restoring normal e-mail
    services.

``create_test_db(verbosity=1, autoclobber=False)``
    Creates a new test database and runs ``syncdb`` against it.

    ``verbosity`` has the same behavior as in ``run_tests()``.

    ``autoclobber`` describes the behavior that will occur if a database with
    the same name as the test database is discovered:

        * If ``autoclobber`` is ``False``, the user will be asked to approve
          destroying the existing database. ``sys.exit`` is called if the user
          does not approve.

        * If autoclobber is ``True``, the database will be destroyed without
          consulting the user.

    ``create_test_db()`` has the side effect of modifying
    ``settings.DATABASE_NAME`` to match the name of the test database.

    New in the Django development version, this function returns the name of
    the test database that it created.

``destroy_test_db(old_database_name, verbosity=1)``
    Destroys the database whose name is in the ``DATABASE_NAME`` setting
    and restores the value of ``DATABASE_NAME`` to the provided name.

    ``verbosity`` has the same behavior as in ``run_tests()``.