/docs/topics/testing.txt

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

.. module:: django.test
   :synopsis: Testing tools for 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.

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:

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

          import unittest

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

    * **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]

We'll discuss choosing the appropriate test framework later, however, most
experienced developers prefer unit tests. You can also use any *other* Python
test framework, as we'll explain in a bit.

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

Django's unit tests use a Python standard library module: unittest_. This
module defines tests in class-based approach.

.. admonition:: unittest2

    .. versionchanged:: 1.3

    Python 2.7 introduced some major changes to the unittest library,
    adding some extremely useful features. To ensure that every Django
    project can benefit from these new features, Django ships with a
    copy of unittest2_, a copy of the Python 2.7 unittest library,
    backported for Python 2.4 compatibility.

    To access this library, Django provides the
    ``django.utils.unittest`` module alias. If you are using Python
    2.7, or you have installed unittest2 locally, Django will map the
    alias to the installed version of the unittest library. Otherwise,
    Django will use it's own bundled version of unittest2.

    To use this alias, simply use::

        from django.utils import unittest

    wherever you would have historically used::

        import unittest

    If you want to continue to use the base unittest library, you can --
    you just won't get any of the nice new unittest2 features.

.. _unittest2: http://pypi.python.org/pypi/unittest2

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.

Here is an example ``unittest.TestCase`` subclass::

    from django.utils 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.assertEqual(self.lion.speak(), 'The lion says "roar"')
            self.assertEqual(self.cat.speak(), 'The cat says "meow"')

When you :ref:`run your tests <running-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.

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/library/unittest.html
.. _standard library unittest documentation: unittest_
.. _suggested organization: http://docs.python.org/library/unittest.html#organizing-tests

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):
            "Return the result of adding two to the provided number."
            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.

As with unit tests, 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.

This example doctest is equivalent to the example given in the unittest section
above::

    # 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 :ref:`run your tests <running-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. However, the database is not refreshed between doctests,
so if your doctest requires a certain state you should consider flushing the
database or loading a fixture. (See the section on fixtures, below, for more
on this.) Note that to use this feature, the database user Django is connecting
as must have ``CREATE DATABASE`` rights.

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

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


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!). However, while
      doctests are good for some simple example code, they are not very good if
      you want to produce either high quality, comprehensive tests or high
      quality documentation. Test failures are often difficult to debug
      as it can be unclear exactly why the test failed. Thus, doctests should
      generally be avoided and used primarily for documentation examples only.

    * 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.

    * If you're writing tests for Django itself, you should use ``unittest``.

.. _running-tests:

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

Once you've written tests, run them using the :djadmin:`test` command of
your project's ``manage.py`` utility::

    $ ./manage.py test

By default, this will run every test in every application in
:setting:`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
:setting:`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``.

You can be even *more* specific by naming an individual test case. 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

.. versionadded:: 1.2
   The ability to select individual doctests was added.

You can use the same rules if you're using doctests. Django will use the
test label as a path to the test method or class that you want to run.
If your ``models.py`` or ``tests.py`` has a function with a doctest, or
class with a class-level doctest, you can invoke that test by appending the
name of the test method or class to the label::

    $ ./manage.py test animals.classify

If you want to run the doctest for a specific method in a class, add the
name of the method to the label::

    $ ./manage.py test animals.Classifier.run

If you're using a ``__test__`` dictionary to specify doctests for a
module, Django will use the label as a key in the ``__test__`` dictionary
for defined in ``models.py`` and ``tests.py``.

.. versionadded:: 1.2
   You can now trigger a graceful exit from a test run by pressing ``Ctrl-C``.

If you press ``Ctrl-C`` while the tests are running, the test runner will
wait for the currently running test to complete and then exit gracefully.
During a graceful exit the test runner will output details of any test
failures, report on how many tests were run and how many errors and failures
were encountered, and destroy any test databases as usual. Thus pressing
``Ctrl-C`` can be very useful if you forget to pass the :djadminopt:`--failfast`
option, notice that some tests are unexpectedly failing, and want to get details
on the failures without waiting for the full test run to complete.

If you do not want to wait for the currently running test to finish, you
can press ``Ctrl-C`` a second time and the test run will halt immediately,
but not gracefully. No details of the tests run before the interruption will
be reported, and any test databases created by the run will not be destroyed.

.. admonition:: Test with warnings enabled

    It's a good idea to run your tests with Python warnings enabled:
    ``python -Wall manage.py test``. The ``-Wall`` flag tells Python to
    display deprecation warnings. Django, like many other Python libraries,
    uses these warnings to flag when features are going away. It also might
    flag areas in your code that aren't strictly wrong but could benefit
    from a better implementation.

Running tests outside the test runner
-------------------------------------

If you want to run tests outside of ``./manage.py test`` -- for example,
from a shell prompt -- you will need to set up the test
environment first. Django provides a convenience method to do this::

    >>> from django.test.utils import setup_test_environment
    >>> setup_test_environment()

This convenience method sets up the test database, and puts other
Django features into modes that allow for repeatable testing.

The call to :meth:`~django.test.utils.setup_test_environment` is made
automatically as part of the setup of `./manage.py test`. You only
need to manually invoke this method if you're not using running your
tests via Django's test runner.

The test database
-----------------

Tests that require a database (namely, model tests) will not use your "real"
(production) database. Separate, blank databases are created for the tests.

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

By default the test databases get their names by prepending ``test_``
to the value of the :setting:`NAME` settings for the databases
defined in :setting:`DATABASES`. When using the SQLite database engine
the tests will by default use an in-memory database (i.e., the
database will be created in memory, bypassing the filesystem
entirely!). If you want to use a different database name, specify
:setting:`TEST_NAME` in the dictionary for any given database in
:setting:`DATABASES`.

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

For fine-grained control over the character encoding of your test
database, use the :setting:`TEST_CHARSET` option. If you're using
MySQL, you can also use the :setting:`TEST_COLLATION` option to
control the particular collation used by the test database. See the
:doc:`settings documentation </ref/settings>` for details of these
advanced settings.

.. _topics-testing-masterslave:

Testing master/slave configurations
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. versionadded:: 1.2

If you're testing a multiple database configuration with master/slave
replication, this strategy of creating test databases poses a problem.
When the test databases are created, there won't be any replication,
and as a result, data created on the master won't be seen on the
slave.

To compensate for this, Django allows you to define that a database is
a *test mirror*. Consider the following (simplified) example database
configuration::

    DATABASES = {
        'default': {
            'ENGINE': 'django.db.backends.mysql',
            'NAME': 'myproject',
            'HOST': 'dbmaster',
             # ... plus some other settings
        },
        'slave': {
            'ENGINE': 'django.db.backends.mysql',
            'NAME': 'myproject',
            'HOST': 'dbslave',
            'TEST_MIRROR': 'default'
            # ... plus some other settings
        }
    }

In this setup, we have two database servers: ``dbmaster``, described
by the database alias ``default``, and ``dbslave`` described by the
alias ``slave``. As you might expect, ``dbslave`` has been configured
by the database administrator as a read slave of ``dbmaster``, so in
normal activity, any write to ``default`` will appear on ``slave``.

If Django created two independent test databases, this would break any
tests that expected replication to occur. However, the ``slave``
database has been configured as a test mirror (using the
:setting:`TEST_MIRROR` setting), indicating that under testing,
``slave`` should be treated as a mirror of ``default``.

When the test environment is configured, a test version of ``slave``
will *not* be created. Instead the connection to ``slave``
will be redirected to point at ``default``. As a result, writes to
``default`` will appear on ``slave`` -- but because they are actually
the same database, not because there is data replication between the
two databases.

.. _topics-testing-creation-dependencies:

Controlling creation order for test databases
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. versionadded:: 1.3

By default, Django will always create the ``default`` database first.
However, no guarantees are made on the creation order of any other
databases in your test setup.

If your database configuration requires a specific creation order, you
can specify the dependencies that exist using the
:setting:`TEST_DEPENDENCIES` setting. Consider the following
(simplified) example database configuration::

    DATABASES = {
        'default': {
             # ... db settings
             'TEST_DEPENDENCIES': ['diamonds']
        },
        'diamonds': {
            # ... db settings
        },
        'clubs': {
            # ... db settings
            'TEST_DEPENDENCIES': ['diamonds']
        },
        'spades': {
            # ... db settings
            'TEST_DEPENDENCIES': ['diamonds','hearts']
        },
        'hearts': {
            # ... db settings
            'TEST_DEPENDENCIES': ['diamonds','clubs']
        }
    }

Under this configuration, the ``diamonds`` database will be created first,
as it is the only database alias without dependencies. The ``default`` and
``clubs`` alias will be created next (although the order of creation of this
pair is not guaranteed); then ``hearts``; and finally ``spades``.

If there are any circular dependencies in the
:setting:`TEST_DEPENDENCIES` definition, an ``ImproperlyConfigured``
exception will be raised.

Other test conditions
---------------------

Regardless of the value of the :setting:`DEBUG` setting in your configuration
file, all Django tests run with :setting:`DEBUG`\=False. This is to ensure that
the observed output of your code matches what will be seen in a production
setting.

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

When you run your tests, you'll see a number of messages as the test runner
prepares itself. You can control the level of detail of these messages with the
``verbosity`` option on the command line::

    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, as described
in the previous section.

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 1 for any 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.

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

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

.. _test-client:

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

.. module:: django.test.client
   :synopsis: Django's 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
programmatically.

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://seleniumhq.org/

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 :setting:`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.

    * By default, the test client will disable any CSRF checks
      performed by your site.

      .. versionadded:: 1.2.2

      If, for some reason, you *want* the test client to perform CSRF
      checks, you can create an instance of the test client that
      enforces CSRF checks. To do this, pass in the
      ``enforce_csrf_checks`` argument when you construct your
      client::

          >>> from django.test import Client
          >>> csrf_client = Client(enforce_csrf_checks=True)


.. _urllib: http://docs.python.org/library/urllib.html
.. _urllib2: http://docs.python.org/library/urllib2.html

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

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

.. class:: Client()

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

    .. method:: Client.get(path, data={}, follow=False, **extra)


        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

        The ``extra`` keyword arguments parameter can be used to specify
        headers to be sent in the request. For example::

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

        ...will send the HTTP header ``HTTP_X_REQUESTED_WITH`` to the
        details view, which is a good way to test code paths that use the
        :meth:`django.http.HttpRequest.is_ajax()` method.

        .. admonition:: CGI specification

            The headers sent via ``**extra`` should follow CGI_ specification.
            For example, emulating a different "Host" header as sent in the
            HTTP request from the browser to the server should be passed
            as ``HTTP_HOST``. 

            .. _CGI: http://www.w3.org/CGI/

        If you already have the GET arguments in URL-encoded form, you can
        use that encoding instead of using the data argument. For example,
        the previous GET request could also be posed as::

        >>> c = Client()
        >>> c.get('/customers/details/?name=fred&age=7')

        If you provide a URL with both an encoded GET data and a data argument,
        the data argument will take precedence.

        If you set ``follow`` to ``True`` the client will follow any redirects
        and a ``redirect_chain`` attribute will be set in the response object
        containing tuples of the intermediate urls and status codes.

        If you had an url ``/redirect_me/`` that redirected to ``/next/``, that
        redirected to ``/final/``, this is what you'd see::

            >>> response = c.get('/redirect_me/', follow=True)
            >>> response.redirect_chain
            [(u'http://testserver/next/', 302), (u'http://testserver/final/', 302)]

    .. method:: Client.post(path, data={}, content_type=MULTIPART_CONTENT, follow=False, **extra)

        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 if you wish to use the same file handle for multiple
        ``post()`` calls then you will need to manually reset the file
        pointer between posts. The easiest way to do this is to
        manually close the file after it has been provided to
        ``post()``, as demonstrated above.

        You should also ensure that the file is opened in a way that
        allows the data to be read. If your file contains binary data
        such as an image, this means you will need to open the file in
        ``rb`` (read binary) mode.

        The ``extra`` argument acts the same as for :meth:`Client.get`.

        If the URL you request with a POST contains encoded parameters, these
        parameters will be made available in the request.GET data. For example,
        if you were to make the request::

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

        ... the view handling this request could interrogate request.POST
        to retrieve the username and password, and could interrogate request.GET
        to determine if the user was a visitor.

        If you set ``follow`` to ``True`` the client will follow any redirects
        and a ``redirect_chain`` attribute will be set in the response object
        containing tuples of the intermediate urls and status codes.

    .. method:: Client.head(path, data={}, follow=False, **extra)

        Makes a HEAD request on the provided ``path`` and returns a ``Response``
        object. Useful for testing RESTful interfaces. Acts just like
        :meth:`Client.get` except it does not return a message body.

        If you set ``follow`` to ``True`` the client will follow any redirects
        and a ``redirect_chain`` attribute will be set in the response object
        containing tuples of the intermediate urls and status codes.

    .. method:: Client.options(path, data={}, follow=False, **extra)

        Makes an OPTIONS request on the provided ``path`` and returns a
        ``Response`` object. Useful for testing RESTful interfaces.

        If you set ``follow`` to ``True`` the client will follow any redirects
        and a ``redirect_chain`` attribute will be set in the response object
        containing tuples of the intermediate urls and status codes.

        The ``extra`` argument acts the same as for :meth:`Client.get`.

    .. method:: Client.put(path, data={}, content_type=MULTIPART_CONTENT, follow=False, **extra)

        Makes a PUT request on the provided ``path`` and returns a
        ``Response`` object. Useful for testing RESTful interfaces. Acts just
        like :meth:`Client.post` except with the PUT request method.

        If you set ``follow`` to ``True`` the client will follow any redirects
        and a ``redirect_chain`` attribute will be set in the response object
        containing tuples of the intermediate urls and status codes.

    .. method:: Client.delete(path, follow=False, **extra)

        Makes an DELETE request on the provided ``path`` and returns a
        ``Response`` object. Useful for testing RESTful interfaces.

        If you set ``follow`` to ``True`` the client will follow any redirects
        and a ``redirect_chain`` attribute will be set in the response object
        containing tuples of the intermediate urls and status codes.

        The ``extra`` argument acts the same as for :meth:`Client.get`.

    .. method:: Client.login(**credentials)

        If your site uses Django's :doc:`authentication system</topics/auth>`
        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
        :ref:`authentication backend <authentication-backends>` you're using
        (which is configured by your :setting:`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. Remember that if you want your test user to have a password,
        you can't set the user's password by setting the password attribute
        directly -- you must use the
        :meth:`~django.contrib.auth.models.User.set_password()` function to
        store a correctly hashed password. Alternatively, you can use the
        :meth:`~django.contrib.auth.models.UserManager.create_user` helper
        method to create a new user with a correctly hashed password.

    .. method:: Client.logout()

        If your site uses Django's :doc:`authentication system</topics/auth>`,
        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.

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; the test response object has some additional data useful for
test code to verify.

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

.. class:: Response()

    .. attribute:: client

        The test client that was used to make the request that resulted in the
        response.

    .. attribute:: content

        The body of the response, as a string. This is the final page content as
        rendered by the view, or any error message.

    .. attribute:: 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.

        Regardless of the number of templates used during rendering, you can
        retrieve context values using the ``[]`` operator. For example, the
        context variable ``name`` could be retrieved using::

            >>> response = client.get('/foo/')
            >>> response.context['name']
            'Arthur'

    .. attribute:: request

        The request data that stimulated the response.

    .. attribute:: status_code

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

    .. versionadded:: 1.3

    .. attribute:: templates

        A list of ``Template`` instances used to render the final content, in
        the order they were rendered. For each template in the list, 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'``.)

You can also use dictionary syntax on the response object to query the value
of any settings in the HTTP headers. For example, you could determine the
content type of a response using ``response['Content-Type']``.

.. _RFC2616: http://www.w3.org/Protocols/rfc2616/rfc2616-sec10.html

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...except``
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:: Client.cookies

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

.. attribute:: Client.session

    A dictionary-like object containing session information. See the
    :doc:`session documentation</topics/http/sessions>` for full details.

    To modify the session and then save it, it must be stored in a variable
    first (because a new ``SessionStore`` is created every time this property
    is accessed)::

        def test_something(self):
            session = self.client.session
            session['somekey'] = 'test'
            session.save()

.. _Cookie module documentation: http://docs.python.org/library/cookie.html

Example
~~~~~~~

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

    from django.utils 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 response is 200 OK.
            self.assertEqual(response.status_code, 200)

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

The request factory
-------------------

.. Class:: RequestFactory

.. versionadded:: 1.3

The :class:`~django.test.client.RequestFactory` shares the same API as
the test client. However, instead of behaving like a browser, the
RequestFactory provides a way to generate a request instance that can
be used as the first argument to any view. This means you can test a
view function the same way as you would test any other function -- as
a black box, with exactly known inputs, testing for specific outputs.

The API for the :class:`~django.test.client.RequestFactory` is a slightly
restricted subset of the test client API:

    * It only has access to the HTTP methods :meth:`~Client.get()`,
      :meth:`~Client.post()`, :meth:`~Client.put()`,
      :meth:`~Client.delete()`, :meth:`~Client.head()` and
      :meth:`~Client.options()`.

    * These methods accept all the same arguments *except* for
      ``follows``. Since this is just a factory for producing
      requests, it's up to you to handle the response.

    * It does not support middleware. Session and authentication
      attributes must be supplied by the test itself if required
      for the view to function properly.

Example
~~~~~~~

The following is a simple unit test using the request factory::

    from django.utils import unittest
    from django.test.client import RequestFactory

    class SimpleTest(unittest.TestCase):
        def setUp(self):
            # Every test needs access to the request factory.
            self.factory = RequestFactory()

        def test_details(self):
            # Create an instance of a GET request.
            request = self.factory.get('/customer/details')

            # Test my_view() as if it were deployed at /customer/details
            response = my_view(request)
            self.assertEqual(response.status_code, 200)

TestCase
--------

.. currentmodule:: django.test

Normal Python unit test classes extend a base class of ``unittest.TestCase``.
Django provides an extension of this base class:

.. class:: TestCase()

This class 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, including:

    * Automatic loading of fixtures.

    * Wraps each test in a transaction.

    * Creates a TestClient instance.

    * Django-specific assertions for testing for things
      like redirection and form errors.

.. class:: TransactionTestCase()

Django ``TestCase`` classes make use of database transaction facilities, if
available, to speed up the process of resetting the database to a known state
at the beginning of each test. A consequence of this, however, is that the
effects of transaction commit and rollback cannot be tested by a Django
``TestCase`` class. If your test requires testing of such transactional
behavior, you should use a Django ``TransactionTestCase``.

``TransactionTestCase`` and ``TestCase`` are identical except for the manner
in which the database is reset to a known state and the ability for test code
to test the effects of commit and rollback. A ``TransactionTestCase`` resets
the database before the test runs by truncating all tables and reloading
initial data. A ``TransactionTestCase`` may call commit and rollback and
observe the effects of these calls on the database.

A ``TestCase``, on the other hand, does not truncate tables and reload initial
data at the beginning of a test. Instead, it encloses the test code in a
database transaction that is rolled back at the end of the test.  It also
prevents the code under test from issuing any commit or rollback operations
on the database, to ensure that the rollback at the end of the test restores
the database to its initial state. In order to guarantee that all ``TestCase``
code starts with a clean database, the Django test runner runs all ``TestCase``
tests first, before any other tests (e.g. doctests) that may alter the
database without restoring it to its original state.

When running on a database that does not support rollback (e.g. MySQL with the
MyISAM storage engine), ``TestCase`` falls back to initializing the database
by truncating tables and reloading initial data.


.. note::
    The ``TestCase`` use of rollback to un-do the effects of the test code
    may reveal previously-undetected errors in test code.  For example,
    test code that assumes primary keys values will be assigned starting at
    one may find that assumption no longer holds true when rollbacks instead
    of table truncation are being used to reset the database.  Similarly,
    the reordering of tests so that all ``TestCase`` classes run first may
    reveal unexpected dependencies on test case ordering.  In such cases a
    quick fix is to switch the ``TestCase`` to a ``TransactionTestCase``.
    A better long-term fix, that allows the test to take advantage of the
    speed benefit of ``TestCase``, is to fix the underlying test problem.


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

.. attribute:: TestCase.client

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::

    from django.utils import unittest
    from django.test.client import Client

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

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

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

    from django.test import TestCase

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

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

Customizing the test client
~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. versionadded:: 1.3

.. attribute:: TestCase.client_class

If you want to use a different ``Client`` class (for example, a subclass
with customized behavior), use the :attr:`~TestCase.client_class` class
attribute::

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

    class MyTestClient(Client):
        # Specialized methods for your environment...

    class MyTest(TestCase):
        client_class = MyTestClient

        def test_my_stuff(self):
            # Here self.client is an instance of MyTestClient...

.. _topics-testing-fixtures:

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

.. attribute:: TestCase.fixtures

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
:djadmin:`manage.py dumpdata <dumpdata>` com…