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476 lines
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476 lines
19 KiB
Plaintext
===========================
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Testing Django applications
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===========================
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**New in Django development version**.
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Automated testing is an extremely useful weapon in the bug-killing arsenal
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of the modern developer. When initially writing code, a test suite can be
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used to validate that code behaves as expected. When refactoring or
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modifying code, tests serve as a guide to ensure that behavior hasn't
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changed unexpectedly as a result of the refactor.
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Testing a web application is a complex task, as there are many
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components of a web application that must be validated and tested. To
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help you test your application, Django provides a test execution
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framework, and range of utilities that can be used to simulate and
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inspect various facets of a web application.
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This testing framework is currently under development, and may change
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slightly before the next official Django release.
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(That's *no* excuse not to write tests, though!)
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Writing tests
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=============
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Tests in Django come in two forms: doctests and unit tests.
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Writing doctests
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----------------
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Doctests use Python's standard doctest_ module, which searches for tests in
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your docstrings. Django's test runner looks for doctests in your ``models.py``
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file, and executes any that it finds. Django will also search for a file
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called ``tests.py`` in the application directory (i.e., the directory that
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holds ``models.py``). If a ``tests.py`` is found, it will also be searched
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for doctests.
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.. admonition:: What's a **docstring**?
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A good explanation of docstrings (and some guidlines for using them
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effectively) can be found in :PEP:`257`:
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A docstring is a string literal that occurs as the first statement in
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a module, function, class, or method definition. Such a docstring
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becomes the ``__doc__`` special attribute of that object.
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Since tests often make great documentation, doctest lets you put your
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tests directly in your docstrings.
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You can put doctest strings on any object in your ``models.py``, but it's
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common practice to put application-level doctests in the module docstring, and
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model-level doctests in the docstring for each model.
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For example::
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from django.db import model
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class Animal(models.Model):
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"""
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An animal that knows how to make noise
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# Create some animals
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>>> lion = Animal.objects.create(name="lion", sound="roar")
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>>> cat = Animal.objects.create(name="cat", sound="meow")
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# Make 'em speak
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>>> lion.speak()
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'The lion says "roar"'
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>>> cat.speak()
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'The cat says "meow"'
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"""
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name = models.CharField(maxlength=20)
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sound = models.CharField(maxlength=20)
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def speak(self):
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return 'The %s says "%s"' % (self.name, self.sound)
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When you `run your tests`_, the test utility will find this docstring, notice
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that portions of it look like an interactive Python session, and execute those
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lines while checking that the results match.
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For more details about how doctest works, see the `standard library
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documentation for doctest`_
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.. _doctest: http://docs.python.org/lib/module-doctest.html
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.. _standard library documentation for doctest: doctest_
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Writing unittests
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-----------------
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Like doctests, Django's unit tests use a standard library module: unittest_.
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As with doctests, Django's test runner looks for any unit test cases defined
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in ``models.py``, or in a ``tests.py`` file stored in the application
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directory.
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An equivalent unittest test case for the above example would look like::
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import unittest
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from myapp.models import Animal
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class AnimalTestCase(unittest.TestCase):
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def setUp(self):
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self.lion = Animal.objects.create(name="lion", sound="roar")
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self.cat = Animal.objects.create(name="cat", sound="meow")
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def testSpeaking(self):
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self.assertEquals(self.lion.speak(), 'The lion says "roar"')
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self.assertEquals(self.cat.speak(), 'The cat says "meow"')
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When you `run your tests`_, the test utility will find all the test cases
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(that is, subclasses of ``unittest.TestCase``) in ``models.py`` and
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``tests.py``, automatically build a test suite out of those test cases,
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and run that suite.
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For more details about ``unittest``, see the `standard library unittest
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documentation`_.
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.. _unittest: http://docs.python.org/lib/module-unittest.html
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.. _standard library unittest documentation: unittest_
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.. _run your tests: `Running tests`_
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Which should I use?
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-------------------
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Choosing a test framework is often contentious, so Django simply supports
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both of the standard Python test frameworks. Choosing one is up to each
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developer's personal tastes; each is supported equally. Since each test
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system has different benefits, the best approach is probably to use both
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together, picking the test system to match the type of tests you need to
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write.
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For developers new to testing, however, this choice can seem
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confusing, so here are a few key differences to help you decide whether
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doctests or unit tests are right for you.
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If you've been using Python for a while, ``doctest`` will probably feel more
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"pythonic". It's designed to make writing tests as easy as possible, so
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there's no overhead of writing classes or methods; you simply put tests in
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docstrings. This gives the added advantage of given your modules automatic
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documentation -- well-written doctests can kill both the documentation and the
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testing bird with a single stone.
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For developers just getting started with testing, using doctests will probably
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get you started faster.
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The ``unittest`` framework will probably feel very familiar to developers
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coming from Java. Since ``unittest`` is inspired by Java's JUnit, if
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you've used testing frameworks in other languages that similarly were
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inspired by JUnit, ``unittest`` should also feel pretty familiar.
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Since ``unittest`` is organized around classes and methods, if you need
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to write a bunch of tests that all share similar code, you can easily use
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subclass to abstract common tasks; this makes test code shorter and cleaner.
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There's also support for explicit setup and/or cleanup routines, which give
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you a high level of control over the environment your test cases run in.
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Again, remember that you can use both systems side-by-side (even in the same
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app). In the end, most projects will eventually end up using both; each shines
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in different circumstances.
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Testing Tools
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=============
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To assist in testing various features of your application, Django provides
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tools that can be used to establish tests and test conditions.
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* `Test Client`_
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* Fixtures_
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Test Client
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-----------
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The Test Client is a simple dummy browser. It allows you to simulate
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GET and POST requests on a URL, and observe the response that is received.
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This allows you to test that the correct view is executed for a given URL,
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and that the view constructs the correct response.
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As the response is generated, the Test Client gathers details on the
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Template and Context objects that were used to generate the response. These
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Templates and Contexts are then provided as part of the response, and can be
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used as test conditions.
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.. admonition:: Test Client vs Browser Automation?
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The Test Client is not intended as a replacement for Twill_, Selenium_,
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or other browser automation frameworks - it is intended to allow
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testing of the contexts and templates produced by a view,
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rather than the HTML rendered to the end-user.
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A comprehensive test suite should use a combination of both: Test Client
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tests to establish that the correct view is being called and that
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the view is collecting the correct context data, and Browser Automation
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tests to check that user interface behaves as expected.
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.. _Twill: http://twill.idyll.org/
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.. _Selenium: http://www.openqa.org/selenium/
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Making requests
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~~~~~~~~~~~~~~~
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Creating an instance of ``Client`` (``django.test.client.Client``) requires
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no arguments at time of construction. Once constructed, the following methods
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can be invoked on the ``Client`` instance.
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``get(path, data={})``
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Make a GET request on the provided ``path``. The key-value pairs in the
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data dictionary will be used to create a GET data payload. For example::
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c = Client()
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c.get('/customers/details/', {'name':'fred', 'age':7})
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will result in the evaluation of a GET request equivalent to::
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http://yoursite.com/customers/details/?name=fred&age=7
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``post(path, data={})``
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Make a POST request on the provided ``path``. The key-value pairs in the
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data dictionary will be used to create the POST data payload. This payload
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will be transmitted with the mimetype ``multipart/form-data``.
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However submitting files is a special case. To POST a file, you need only
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provide the file field name as a key, and a file handle to the file you wish to
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upload as a value. The Test Client will populate the two POST fields (i.e.,
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``field`` and ``field_file``) required by FileField. For example::
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c = Client()
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f = open('wishlist.doc')
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c.post('/customers/wishes/', {'name':'fred', 'attachment':f})
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f.close()
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will result in the evaluation of a POST request on ``/customers/wishes/``,
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with a POST dictionary that contains `name`, `attachment` (containing the
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file name), and `attachment_file` (containing the file data). Note that you
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need to manually close the file after it has been provided to the POST.
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``login(path, username, password)``
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In a production site, it is likely that some views will be protected with
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the @login_required decorator provided by ``django.contrib.auth``. Interacting
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with a URL that has been login protected is a slightly complex operation,
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so the Test Client provides a simple method to automate the login process. A
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call to ``login()`` stimulates the series of GET and POST calls required
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to log a user into a @login_required protected view.
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If login is possible, the final return value of ``login()`` is the response
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that is generated by issuing a GET request on the protected URL. If login
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is not possible, ``login()`` returns False.
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Note that since the test suite will be executed using the test database,
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which contains no users by default. As a result, logins for your production
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site will not work. You will need to create users as part of the test suite
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to be able to test logins to your application.
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Testing Responses
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~~~~~~~~~~~~~~~~~
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The ``get()``, ``post()`` and ``login()`` methods all return a Response
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object. This Response object has the following properties that can be used
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for testing purposes:
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=============== ==========================================================
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Property Description
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=============== ==========================================================
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``status_code`` The HTTP status of the response. See RFC2616_ for a
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full list of HTTP status codes.
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``content`` The body of the response. The is the final page
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content as rendered by the view, or any error message
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(such as the URL for a 302 redirect).
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``template`` The Template instance that was used to render the final
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content. Testing ``template.name`` can be particularly
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useful; if the template was loaded from a file,
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``template.name`` will be the file name that was loaded.
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If multiple templates were rendered, (e.g., if one
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template includes another template),``template`` will
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be a list of Template objects, in the order in which
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they were rendered.
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``context`` The Context that was used to render the template that
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produced the response content.
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As with ``template``, if multiple templates were rendered
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``context`` will be a list of Context objects, stored in
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the order in which they were rendered.
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=============== ==========================================================
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.. _RFC2616: http://www.w3.org/Protocols/rfc2616/rfc2616-sec10.html
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Persistent state
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~~~~~~~~~~~~~~~~
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The Test Client is stateful; if a cookie is returned as part of a response,
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that cookie is provided as part of the next request issued by that Client
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instance. Expiry policies for these cookies are not followed; if you want
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a cookie to expire, either delete it manually or create a new Client
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instance (which will effectively delete all cookies).
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There are two properties of the Test Client which are used to store persistent
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state information. If necessary, these properties can be interrogated as
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part of a test condition.
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=============== ==========================================================
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Property Description
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=============== ==========================================================
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``cookies`` A Python ``SimpleCookie`` object, containing the current
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values of all the client cookies.
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``session`` A dictionary-like object containing session information.
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See the `session documentation`_ for full details.
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.. _`session documentation`: ../sessions/
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Example
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~~~~~~~
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The following is a simple unit test using the Test Client::
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import unittest
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from django.test.client import Client
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class SimpleTest(unittest.TestCase):
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def setUp(self):
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# Every test needs a client
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self.client = Client()
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def test_details(self):
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# Issue a GET request
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response = self.client.get('/customer/details/')
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# Check that the respose is 200 OK
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self.failUnlessEqual(response.status_code, 200)
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# Check that the rendered context contains 5 customers
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self.failUnlessEqual(len(response.context['customers']), 5)
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Fixtures
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--------
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Feature still to come...
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Running tests
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=============
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Run your tests using your project's ``manage.py`` utility::
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$ ./manage.py test
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If you only want to run tests for a particular application, add the
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application name to the command line. For example, if your
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``INSTALLED_APPS`` contains ``myproject.polls`` and ``myproject.animals``,
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but you only want to run the animals unit tests, run::
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$ ./manage.py test animals
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When you run your tests, you'll see a bunch of text flow by as the test
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database is created and models are initialized. This test database is
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created from scratch every time you run your tests.
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By default, the test database gets its name by prepending ``test_`` to
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the database name specified by the ``DATABASE_NAME`` setting; all other
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database settings will the same as they would be for the project normally.
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If you wish to use a name other than the default for the test database,
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you can use the ``TEST_DATABASE_NAME`` setting to provide a name.
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Once the test database has been established, Django will run your tests.
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If everything goes well, at the end you'll see::
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----------------------------------------------------------------------
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Ran 22 tests in 0.221s
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OK
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If there are test failures, however, you'll see full details about what tests
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failed::
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======================================================================
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FAIL: Doctest: ellington.core.throttle.models
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----------------------------------------------------------------------
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Traceback (most recent call last):
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File "/dev/django/test/doctest.py", line 2153, in runTest
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raise self.failureException(self.format_failure(new.getvalue()))
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AssertionError: Failed doctest test for myapp.models
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File "/dev/myapp/models.py", line 0, in models
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----------------------------------------------------------------------
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File "/dev/myapp/models.py", line 14, in myapp.models
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Failed example:
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throttle.check("actor A", "action one", limit=2, hours=1)
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Expected:
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True
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Got:
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False
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----------------------------------------------------------------------
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Ran 2 tests in 0.048s
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FAILED (failures=1)
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When the tests have all been executed, the test database is destroyed.
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Using a different testing framework
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===================================
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Doctest and Unittest are not the only Python testing frameworks. While
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Django doesn't provide explicit support these alternative frameworks,
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it does provide a mechanism to allow you to invoke tests constructed for
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an alternative framework as if they were normal Django tests.
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When you run ``./manage.py test``, Django looks at the ``TEST_RUNNER``
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setting to determine what to do. By default, ``TEST_RUNNER`` points to ``django.test.simple.run_tests``. This method defines the default Django
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testing behavior. This behavior involves:
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#. Performing global pre-test setup
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#. Creating the test database
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#. Running ``syncdb`` to install models and initial data into the test database
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#. Looking for Unit Tests and Doctests in ``models.py`` and ``tests.py`` file for each installed application
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#. Running the Unit Tests and Doctests that are found
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#. Destroying the test database.
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#. Performing global post-test teardown
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If you define your own test runner method and point ``TEST_RUNNER``
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at that method, Django will execute your test runner whenever you run
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``./manage.py test``. In this way, it is possible to use any test
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framework that can be executed from Python code.
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Defining a test runner
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----------------------
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By convention, a test runner should be called ``run_tests``; however, you
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can call it anything you want. The only requirement is that it accept two
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arguments:
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``run_tests(module_list, verbosity=1)``
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The module list is the list of Python modules that contain the models to be
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tested. This is the same format returned by ``django.db.models.get_apps()``
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Verbosity determines the amount of notification and debug information that
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will be printed to the console; `0` is no output, `1` is normal output,
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and `2` is verbose output.
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Testing utilities
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-----------------
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To assist in the creation of your own test runner, Django provides
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a number of utility methods in the ``django.test.utils`` module.
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``setup_test_environment()``
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Performs any global pre-test setup, such as the installing the
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instrumentation of the template rendering system.
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``teardown_test_environment()``
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Performs any global post-test teardown, such as removing the instrumentation
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of the template rendering system.
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``create_test_db(verbosity=1, autoclobber=False)``
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Creates a new test database, and run ``syncdb`` against it.
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``verbosity`` has the same behavior as in the test runner.
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``Autoclobber`` describes the behavior that will occur if a database with
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the same name as the test database is discovered. If ``autoclobber`` is False,
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the user will be asked to approve destroying the existing database. ``sys.exit``
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is called if the user does not approve. If autoclobber is ``True``, the database
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will be destroyed without consulting the user.
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``create_test_db()`` has the side effect of modifying
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``settings.DATABASE_NAME`` to match the name of the test database.
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``destroy_test_db(old_database_name, verbosity=1)``
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Destroys the database with the name ``settings.DATABASE_NAME`` matching,
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and restores the value of ``settings.DATABASE_NAME`` to the provided name.
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``verbosity`` has the same behavior as in the test runner.
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