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testing.txt
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.. _topics-testing:
===========================
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:
* **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):
"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.
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 :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/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 :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/lib/module-unittest.html
.. _standard library unittest documentation: unittest_
.. _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:
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
: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``.
.. versionadded:: 1.0
You can now choose which test to run.
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
The test database
-----------------
Tests that require a database (namely, model tests) will not use your "real"
(production) database. A separate, blank database is created for the tests.
Regardless of whether the tests pass or fail, the test database is destroyed
when all the tests have been executed.
By default this test database gets its name by prepending ``test_`` to the
value of the :setting:`DATABASE_NAME` setting. 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 the :setting:`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:
:setting:`DATABASE_ENGINE`, :setting:`DATABASE_USER`, :setting:`DATABASE_HOST`,
etc. The test database is created by the user specified by
:setting:`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.
.. versionadded:: 1.0
For fine-grained control over the
character encoding of your test database, use the
:setting:`TEST_DATABASE_CHARSET` setting. If you're using MySQL, you can also
use the :setting:`TEST_DATABASE_COLLATION` setting to control the particular
collation used by the test database. See the :ref:`settings documentation
<ref-settings>` for details of these advanced settings.
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 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.
Testing tools
=============
Django provides a small set of tools that come in handy when writing tests.
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://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 :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.
.. _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:
.. 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.
.. versionadded:: 1.1
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 you should manually close the file after it has been provided
to ``post()``.
The ``extra`` argument acts the same as for :meth:`Client.get`.
.. versionchanged:: 1.1
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/?vistor=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)
.. versionadded:: 1.1
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)
.. versionadded:: 1.1
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)
.. versionadded:: 1.1
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)
.. versionadded:: 1.1
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)
.. versionadded:: 1.0
If your site uses Django's :ref:`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()
.. versionadded:: 1.0
If your site uses Django's :ref:`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.
.. versionadded:: 1.1
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.
.. attribute:: 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 :ref:`template
inheritance<template-inheritance>` -- then ``template`` will be a list of
``Template`` instances, in the order in which they were rendered.
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
:ref:`session documentation<topics-http-sessions>` for full details.
.. _Cookie module documentation: http://docs.python.org/lib/module-Cookie.html
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 response 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
--------
.. 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.
.. versionadded:: 1.1
.. 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
~~~~~~~~~~~~~~~~~~~
.. versionadded:: 1.0
.. 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::
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
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)
.. _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 ``manage.py
dumpdata`` command. This assumes you already have some data in your database.
See the :djadmin:`dumpdata documentation<dumpdata>` 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 in a ``fixtures`` directory in one
of your :setting:`INSTALLED_APPS`, 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 :djadmin:`loaddata documentation<loaddata>` 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.