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*Finally* edited docs/testing.txt 

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docs/testing.txt
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......@@ -22,6 +22,9 @@ it should be doing.
The best part is, it's really easy.
This document is split into two primary sections. First, we explain how to
write tests with Django. Then, we explain how to run them.
.. admonition:: Note
This testing framework is currently under development. It may change
......@@ -32,35 +35,81 @@ The best part is, it's really easy.
Writing tests
=============
Tests in Django come in two forms: doctests and unit 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 for tests in
your docstrings. Django's test runner looks for doctests in your ``models.py``
file, and executes any that it finds. Django will also search for a file
called ``tests.py`` in the application directory (i.e., the directory that
holds ``models.py``). If a ``tests.py`` is found, it will also be searched
for 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 guidlines for using them
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.
Since tests often make great documentation, doctest lets you put your
tests directly in your docstrings.
For example, this function has a docstring that describes what it does::
def add_two(num):
"Adds 2 to the given number and returns the result."
return num + 2
Because tests often make great documentation, putting tests directly in
your docstrings is an effective way to document *and* test your code.
For a given Django application, the test runner looks for doctests in two
places:
* The ``models.py`` file. You can define module-level doctests and/or a
doctest for individual models. It's common practice to put
application-level doctests in the module docstring and model-level
doctests in the model docstrings.
* A file called ``tests.py`` in the application directory -- i.e., the
directory that holds ``models.py``. This file is a hook for any and all
doctests you want to write that aren't necessarily related to models.
You can put doctest strings on any object in your ``models.py``, but it's
common practice to put application-level doctests in the module docstring, and
model-level doctests in the docstring for each model.
Here is an example model doctest::
For example::
# models.py
from django.db import models
......@@ -78,38 +127,53 @@ For example::
>>> cat.speak()
'The cat says "meow"'
"""
name = models.CharField(max_length=20)
sound = models.CharField(max_length=20)
def speak(self):
return 'The %s says "%s"' % (self.name, self.sound)
When you `run your tests`_, the test utility will find this docstring, notice
When you `run your tests`_, the test runner will find this docstring, notice
that portions of it look like an interactive Python session, and execute those
lines while checking that the results match.
In the case of model tests, note that the test runner takes care of creating
its own test database. That is, any test that accesses a database -- by
creating and saving model instances, for example -- will not affect your
production database. Each doctest begins with a "blank slate" -- a fresh
database containing an empty table for each model. (See the section on
fixtures, below, for more on this.)
For more details about how doctest works, see the `standard library
documentation for doctest`_
.. _doctest: http://docs.python.org/lib/module-doctest.html
.. _standard library documentation for doctest: doctest_
Writing unittests
-----------------
Writing unit tests
------------------
Like doctests, Django's unit tests use a standard library module: unittest_.
As with doctests, Django's test runner looks for any unit test cases defined
in ``models.py``, or in a ``tests.py`` file stored in the application
directory.
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:
An equivalent unittest test case for the above example would look like::
* 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")
......@@ -123,13 +187,12 @@ 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.
**New in Django development version**
However, if you define a method called ``suite()`` in either ``models.py`` or
``tests.py``, that method will be used 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.
In the Django development version, there is a second way to define the test
suite for a module: if you define a function called ``suite()`` in either
``models.py`` or ``tests.py``, the Django test runner will use that function
to construct the test suite for that module. This follows the
`suggested organization`_ for unit tests. See the Python documentation for
more details on how to construct a complex test suite.
For more details about ``unittest``, see the `standard library unittest
documentation`_.
......@@ -142,304 +205,541 @@ documentation`_.
Which should I use?
-------------------
Choosing a test framework is often contentious, so Django simply supports
both of the standard Python test frameworks. Choosing one is up to each
developer's personal tastes; each is supported equally. Since each test
system has different benefits, the best approach is probably to use both
together, picking the test system to match the type of tests you need to
write.
For developers new to testing, however, this choice can seem
confusing, so here are a few key differences to help you decide whether
doctests or unit tests are 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
there's no overhead of writing classes or methods; you simply put tests in
docstrings. This gives the added advantage of giving your modules automatic
documentation -- well-written doctests can kill both the documentation and the
testing bird with a single stone.
For developers 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. Since ``unittest`` is inspired by Java's JUnit, if
you've used testing frameworks in other languages that similarly were
inspired by JUnit, ``unittest`` should also feel pretty familiar.
Since ``unittest`` is organized around classes and methods, if you need
to write a bunch of tests that all share similar code, you can easily use
subclass to abstract common tasks; this makes test code shorter and cleaner.
There's also support for explicit setup and/or cleanup routines, which give
you a high level of control over the environment your test cases run in.
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
app). In the end, most projects will eventually end up using both. Each shines
in different circumstances.
Testing Tools
Running tests
=============
Once you've written tests, run them using your project's ``manage.py`` utility::
$ ./manage.py test
By default, this will run every test in every application in ``INSTALLED_APPS``.
If you only want to run tests for a particular application, add the
application name to the command line. For example, if your ``INSTALLED_APPS``
contains ``'myproject.polls'`` and ``'myproject.animals'``, you can run the
``myproject.animals`` unit tests alone with this command::
# ./manage.py test animals
Note that we used ``animals``, not ``myproject.animals``.
**New in Django development version:** If you use unit tests, as opposed to
doctests, you can be even *more* specific in choosing which tests to execute.
To run a single test case in an application (for example, the
``AnimalTestCase`` described in the "Writing unit tests" section), add the
name of the test case to the label on the command line::
$ ./manage.py test animals.AnimalTestCase
And it gets even more granular than that! To run a *single* test method inside
a test case, add the name of the test method to the label::
$ ./manage.py test animals.AnimalTestCase.testFluffyAnimals
Understanding the test output
-----------------------------
When you run your tests, you'll see a number of messages as the test runner
prepares itself::
Creating test database...
Creating table myapp_animal
Creating table myapp_mineral
Loading 'initial_data' fixtures...
No fixtures found.
This tells you that the test runner is creating a test database -- a blank,
from-scratch database that it will use for any tests that happen to require a
database (namely, model tests).
Don't worry -- the test runner will not touch your "real" (production)
database. It creates a separate database purely for the tests. This test
database gets its name by prepending ``test_`` to the value of the
``DATABASE_NAME`` setting. If you want to use a different name, specify the
``TEST_DATABASE_NAME`` setting.
Aside from using a separate database, the test runner will otherwise use all of
the same database settings you have in your settings file: ``DATABASE_ENGINE``,
``DATABASE_USER``, ``DATABASE_HOST``, etc. The test database is created by the
user specified by ``DATABASE_USER``, so you'll need to make sure that the given
user account has sufficient privileges to create a new database on the system.
**New in Django development version:** For fine-grained control over the
character encoding of your test database, use the ``TEST_DATABASE_CHARSET``
setting. If you're using MySQL, you can also use the ``TEST_DATABASE_COLLATION``
setting to control the particular collation used by the test database. See the
settings_ documentation for details of these advanced settings.
.. _settings: ../settings/
Once the test database has been created, Django will run your tests.
If everything goes well, you'll see something like this::
----------------------------------------------------------------------
Ran 22 tests in 0.221s
OK
If there are test failures, however, you'll see full details about which tests
failed::
======================================================================
FAIL: Doctest: ellington.core.throttle.models
----------------------------------------------------------------------
Traceback (most recent call last):
File "/dev/django/test/doctest.py", line 2153, in runTest
raise self.failureException(self.format_failure(new.getvalue()))
AssertionError: Failed doctest test for myapp.models
File "/dev/myapp/models.py", line 0, in models
----------------------------------------------------------------------
File "/dev/myapp/models.py", line 14, in myapp.models
Failed example:
throttle.check("actor A", "action one", limit=2, hours=1)
Expected:
True
Got:
False
----------------------------------------------------------------------
Ran 2 tests in 0.048s
FAILED (failures=1)
A full explanation of this error output is beyond the scope of this document,
but it's pretty intuitive. You can consult the documentation of Python's
``unittest`` library for details.
Note that the return code for the test-runner script is the total number of
failed and erroneous tests. If all the tests pass, the return code is 0. This
feature is useful if you're using the test-runner script in a shell script and
need to test for success or failure at that level.
Regardless of whether the tests pass or fail, the test database is destroyed when
all the tests have been executed.
Testing tools
=============
To assist in testing various features of your application, Django provides
tools that can be used to establish tests and test conditions.
Django provides a small set of tools that come in handy when writing tests.
The test client
---------------
The test client is a Python class that acts as a dummy Web browser, allowing
you to test your views and interact with your Django-powered application
programatically.
Some of the things you can do with the test client are:
* `Test Client`_
* `TestCase`_
* `E-mail services`_
* 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 Client
-----------
* Test that the correct view is executed for a given URL.
The Test Client is a simple dummy browser. It allows you to simulate
GET and POST requests on a URL, and observe the response that is received.
This allows you to test that the correct view is executed for a given URL,
and that the view constructs the correct response.
* Test that a given request is rendered by a given Django template, with
a template context that contains certain values.
As the response is generated, the Test Client gathers details on the
Template and Context objects that were used to generate the response. These
Templates and Contexts are then provided as part of the response, and can be
used as test conditions.
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:
.. admonition:: Test Client vs Browser Automation?
* Use Django's test client to establish that the correct view is being
called and that the view is collecting the correct context data.
The Test Client is not intended as a replacement for Twill_, Selenium_,
or other browser automation frameworks - it is intended to allow
testing of the contexts and templates produced by a view,
rather than the HTML rendered to the end-user.
* 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 Client
tests to establish that the correct view is being called and that
the view is collecting the correct context data, and Browser Automation
tests to check that user interface behaves as expected.
A comprehensive test suite should use a combination of both test types.
.. _Twill: http://twill.idyll.org/
.. _Selenium: http://www.openqa.org/selenium/
Overview and a quick example
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
To use the test client, instantiate ``django.test.client.Client`` and retrieve
Web pages::
>>> from django.test.client import Client
>>> c = Client()
>>> response = c.post('/login/', {'username': 'john', 'password': 'smith'})
>>> response.status_code
200
>>> response = c.get('/customer/details/')
>>> response.content
'<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 ...'
As this example suggests, you can instantiate ``Client`` from within a session
of the Python interactive interpreter.
Note a few important things about how the test client works:
* The test client does *not* require the Web server to be running. In fact,
it will run just fine with no Web server running at all! That's because
it avoids the overhead of HTTP and deals directly with the Django
framework. This helps make the unit tests run quickly.
* When retrieving pages, remember to specify the *path* of the URL, not the
whole domain. For example, this is correct::
>>> c.get('/login/')
This is incorrect::
>>> c.get('http://www.example.com/login/')
The test client is not capable of retrieving Web pages that are not
powered by your Django project. If you need to retrieve other Web pages,
use a Python standard library module such as urllib_ or urllib2_.
* To resolve URLs, the test client uses whatever URLconf is pointed-to by
your ``ROOT_URLCONF`` setting.
* Although the above example would work in the Python interactive
interpreter, some of the test client's functionality, notably the
template-related functionality, is only available *while tests are running*.
The reason for this is that Django's test runner performs a bit of black
magic in order to determine which template was loaded by a given view.
This black magic (essentially a patching of Django's template system in
memory) only happens during test running.
.. _urllib: http://docs.python.org/lib/module-urllib.html
.. _urllib2: http://docs.python.org/lib/module-urllib2.html
Making requests
~~~~~~~~~~~~~~~
Creating an instance of ``Client`` (``django.test.client.Client``) requires
no arguments at time of construction. Once constructed, the following methods
can be invoked on the ``Client`` instance.
Use the ``django.test.client.Client`` class to make requests. It requires no
arguments at time of construction::
>>> c = Client()
Once you have a ``Client`` instance, you can call any of the following methods:
``get(path, data={})``
Make a GET request on the provided ``path``. The key-value pairs in the
data dictionary will be used to create a GET data payload. For example::
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})
>>> c = Client()
>>> c.get('/customers/details/', {'name': 'fred', 'age': 7})
will result in the evaluation of a GET request equivalent to::
...will result in the evaluation of a GET request equivalent to::
http://yoursite.com/customers/details/?name=fred&age=7
/customers/details/?name=fred&age=7
``post(path, data={}, content_type=MULTIPART_CONTENT)``
Make a POST request on the provided ``path``. If you provide a content type
(e.g., ``text/xml`` for an XML payload), the contents of ``data`` will be
sent as-is in the POST request, using the content type in the HTTP
``Content-Type`` header.
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.get('/login/', {'name': 'fred', 'passwd': 'secret'})
...will result in the evaluation of a POST request to this URL::
If you do not provide a value for ``content_type``, the values in
/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``.
The key-value pairs in the data dictionary 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 multiple selection list), provide the values as a
list or tuple for the required key. For example, a data dictionary of
``{'choices': ('a','b','d')}`` would submit three selected rows for the
field named ``choices``.
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. The Test Client will populate the two POST fields (i.e.,
``field`` and ``field_file``) required by Django's FileField. For example::
c = Client()
f = open('wishlist.doc')
c.post('/customers/wishes/', {'name':'fred', 'attachment':f})
f.close()
will result in the evaluation of a POST request on ``/customers/wishes/``,
with a POST dictionary that contains ``name``, ``attachment`` (containing the
file name), and ``attachment_file`` (containing the file data). Note that you
need to manually close the file after it has been provided to the POST.
In this case, the key-value pairs in ``data`` will be encoded as a
multipart message and used to create the POST data payload.
To submit multiple values for a given key -- for example, to specify
the selections for a ``<select multiple>`` -- provide the values as a
list or tuple for the required key. For example, this value of ``data``
would submit three selected values for the field named ``choices``::
{'choices': ('a', 'b', 'd')}
Submitting files is a special case. To POST a file, you need only provide
the file field name as a key, and a file handle to the file you wish to
upload as a value. For example::
>>> c = Client()
>>> f = open('wishlist.doc')
>>> c.post('/customers/wishes/', {'name': 'fred', 'attachment': f})
>>> f.close()
(The name ``attachment`` here is not relevant; use whatever name your
file-processing code expects.)
Note that you should manually close the file after it has been provided to
``post()``.
``login(**credentials)``
**New in Django development version**
On a production site, it is likely that some views will be protected from
anonymous access through the use of the @login_required decorator, or some
other login checking mechanism. The ``login()`` method can be used to
simulate the effect of a user logging into the site. As a result of calling
this method, the Client will have all the cookies and session data required
to pass any login-based tests that may form part of a view.
If your site uses Django's `authentication system`_ and you deal with
logging in users, you can use the test client's ``login()`` method to
simulate the effect of a user logging into the site.
In most cases, the ``credentials`` required by this method are the username
and password of the user that wants to log in, provided as keyword
arguments::
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.
c = Client()
c.login(username='fred', password='secret')
# Now you can access a login protected view
The format of the ``credentials`` argument depends on which
`authentication backend`_ you're using (which is configured by your
``AUTHENTICATION_BACKENDS`` setting). If you're using the standard
authentication backend provided by Django (``ModelBackend``),
``credentials`` should be the user's username and password, provided as
keyword arguments::
If you are using a different authentication backend, this method may
require different credentials.
>>> 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.
Note that since the test suite will be executed using the test database,
which contains no users by default. As a result, logins that are valid
on your production site will not work under test conditions. You will
need to create users as part of the test suite (either manually, or
using a test fixture).
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.
.. _authentication system: ../authentication/
.. _authentication backend: ../authentication/#other-authentication-sources
Testing Responses
Testing responses
~~~~~~~~~~~~~~~~~
The ``get()`` and ``post()`` methods both return a Response object. This
Response object has the following properties that can be used for testing
purposes:
The ``get()`` and ``post()`` methods both return a ``Response`` object. This
``Response`` object is *not* the same as the ``HttpResponse`` object returned
Django views; this object is simpler and has some additional data useful for
tests.
Specifically, a ``Response`` object has the following attributes::
=============== ==========================================================
Property Description
Attribute Description
=============== ==========================================================
``status_code`` The HTTP status of the response. See RFC2616_ for a
full list of HTTP status codes.
``content`` The body of the response. This is the final page
content as rendered by the view, or any error message
(such as the URL for a 302 redirect).
``template`` The Template instance that was used to render the final
content. Testing ``template.name`` can be particularly
useful; if the template was loaded from a file,
``template.name`` will be the file name that was loaded.
If multiple templates were rendered, (e.g., if one
template includes another template),``template`` will
be a list of Template objects, in the order in which
they were rendered.
``context`` The Context that was used to render the template that
produced the response content.
As with ``template``, if multiple templates were rendered
``context`` will be a list of Context objects, stored in
the order in which they were rendered.
``status_code`` The HTTP status of the response, as an integer. See
RFC2616_ for a full list of HTTP status codes.
``content`` The body of the response, as a string. This is the final
page content as rendered by the view, or any error
message (such as the URL for a 302 redirect).
``template`` The ``Template`` instance that was used to render the
final content. Use ``template.name`` to get the
template's file name, if the template was loaded from a
file. (The name is a string such as
``'admin/index.html'``.)
If the rendered page used multiple templates -- e.g.,
using `template inheritance`_ -- then ``template`` will
be a list of ``Template`` instances, in the order in
which they were rendered.
``context`` The template ``Context`` instance that was used to render
the template that produced the response content.
As with ``template``, if the rendered page used multiple
templates, then ``context`` will be a list of ``Context``
objects, in the order in which they were rendered.
=============== ==========================================================
.. _RFC2616: http://www.w3.org/Protocols/rfc2616/rfc2616-sec10.html
.. _template inheritance: ../templates/#template-inheritance
Exceptions
~~~~~~~~~~
If you point the Test Client at a view that raises an exception, that exception
If you point the test client at a view that raises an exception, that exception
will be visible in the test case. You can then use a standard ``try...catch``
block, or ``unittest.TestCase.assertRaises()`` to test for exceptions.
block or ``unittest.TestCase.assertRaises()`` to test for exceptions.
The only exceptions that are not visible in a Test Case are ``Http404``,
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 responses codes.
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 cookie is returned as part of a response,
that cookie is provided as part of the next request issued by that Client
instance. Expiry 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).
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).
There are two properties of the Test Client which are used to store persistent
state information. If necessary, these properties can be interrogated as
part of a test condition.
A test client has two attributes that store persistent state information. You
can access these properties as part of a test condition.
=============== ==========================================================
Property Description
Attribute Description
=============== ==========================================================
``cookies`` A Python ``SimpleCookie`` object, containing the current
values of all the client cookies.
values of all the client cookies. See the
`Cookie module documentation`_ for more.
``session`` A dictionary-like object containing session information.
See the `session documentation`_ for full details.
=============== ==========================================================
.. _`session documentation`: ../sessions/
.. _Cookie module documentation: http://docs.python.org/lib/module-Cookie.html
.. _session documentation: ../sessions/
Example
~~~~~~~
The following is a simple unit test using the Test Client::
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
# Every test needs a client.
self.client = Client()
def test_details(self):
# Issue a GET request
# Issue a GET request.
response = self.client.get('/customer/details/')
# Check that the respose is 200 OK
# Check that the respose is 200 OK.
self.failUnlessEqual(response.status_code, 200)
# Check that the rendered context contains 5 customers
# Check that the rendered context contains 5 customers.
self.failUnlessEqual(len(response.context['customers']), 5)
TestCase
--------
Normal python unit tests extend a base class of ``unittest.testCase``.
Django provides an extension of this base class - ``django.test.TestCase``
- that provides some additional capabilities that can be useful for
testing web sites.
Normal Python unit test classes extend a base class of ``unittest.TestCase``.
Django provides an extension of this base class -- ``django.test.TestCase``
-- that provides some additional capabilities that can be useful for
testing Web sites.
Moving from 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 facilities
will continue to be available, but they will be augmented with some useful
extra facilities.
Converting a normal ``unittest.TestCase`` to a Django ``TestCase`` is easy:
just change the base class of your test from ``unittest.TestCase`` to
``django.test.TestCase``. All of the standard Python unit test functionality
will continue to be available, but it will be augmented with some useful
additions.
Default Test Client
Default test client
~~~~~~~~~~~~~~~~~~~
**New in Django development version**
Every test case in a ``django.test.TestCase`` instance has access to an
instance of a Django `Test Client`_. This Client can be accessed as
``self.client``. This client is recreated for each test.
instance of a Django test client. This client can be accessed as
``self.client``. This client is recreated for each test, so you don't have to
worry about state (such as cookies) carrying over from one test to another.
This means, instead of instantiating a ``Client`` in each test::
import unittest
from django.test.client import Client
class SimpleTest(unittest.TestCase):
def test_details(self):
client = Client()
response = client.get('/customer/details/')
self.failUnlessEqual(response.status_code, 200)
def test_index(self):
client = Client()
response = client.get('/customer/index/')
self.failUnlessEqual(response.status_code, 200)
...you can just refer to ``self.client``, like so::
from django.test import TestCase
from django.test.client import Client
class SimpleTest(TestCase):
def test_details(self):
response = self.client.get('/customer/details/')
self.failUnlessEqual(response.status_code, 200)
def test_index(self):
response = self.client.get('/customer/index/')
self.failUnlessEqual(response.status_code, 200)
Fixture loading
~~~~~~~~~~~~~~~
A test case for a database-backed website isn't much use if there isn't any
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 provides a fixtures framework.
Django's custom ``TestCase`` class provides a way of loading **fixtures**.
A *Fixture* is a collection of files that contain the serialized contents of
the database. Each fixture has a unique name; however, the files that
comprise the fixture can be distributed over multiple directories, in
multiple applications.
A fixture is a collection of data that Django knows how to import into a
database. For example, if your site has user accounts, you might set up a
fixture of fake user accounts in order to populate your database during tests.
The most straightforward way of creating a fixture is to use the
``manage.py dumpdata`` command. This assumes you already have some data in
your database. See the `dumpdata documentation`_ for more details.
.. note::
If you have synchronized a Django project, you have already experienced
the use of one fixture -- the ``initial_data`` fixture. Every time you
synchronize the database, Django installs the ``initial_data`` fixture.
This provides a mechanism to populate a new database with any initial
data (such as a default set of categories). Fixtures with other names
can be installed manually using ``django-admin.py loaddata``.
However, for the purposes of unit testing, each test must be able to
guarantee the contents of the database at the start of each and every
test.
To define a fixture for a test, all you need to do is add a class
attribute to your test describing the fixtures you want the test to use.
For example, the test case from `Writing unittests`_ would
look like::
If you've ever run ``manage.py syncdb``, you've already used a fixture
without even knowing it! When you call ``syncdb`` in the database for
the first time, Django installs a fixture called ``initial_data``.
This gives you a way of populating a new database with any initial data,
such as a default set of categories.
Fixtures with other names can always be installed manually using the
``manage.py loaddata`` command.
Once you've created a fixture and placed it somewhere in your Django project,
you can use it in your unit tests by specifying a ``fixtures`` class attribute
on your ``django.test.TestCase`` subclass::
from django.test import TestCase
from myapp.models import Animal
......@@ -448,260 +748,205 @@ look like::
fixtures = ['mammals.json', 'birds']
def setUp(self):
# test definitions as before
# Test definitions as before.
def testFluffyAnimals(self):
# A test that uses the fixtures
# A test that uses the fixtures.
At the start of each test case, before ``setUp()`` is run, Django will
flush the database, returning the database the state it was in directly
after ``syncdb`` was called. Then, all the named fixtures are installed.
In this example, any JSON fixture called ``mammals``, and any fixture
named ``birds`` will be installed. See the documentation on
`loading fixtures`_ for more details on defining and installing fixtures.
Here's specifically what will happen:
.. _`loading fixtures`: ../django-admin/#loaddata-fixture-fixture
* At the start of each test case, before ``setUp()`` is run, Django will
flush the database, returning the database to the state it was in
directly after ``syncdb`` was called.
* Then, all the named fixtures are installed. In this example, Django will
install any JSON fixture named ``mammals``, followed by any fixture named
``birds``. See the `loaddata documentation`_ for more details on defining
and installing fixtures.
This flush/load procedure is repeated for each test in the test case, so you
can be certain that the outcome of a test will not be affected by
another test, or the order of test execution.
another test, or by the order of test execution.
.. _dumpdata documentation: ../django-admin/#dumpdata-appname-appname
.. _loaddata documentation: ../django-admin/#loaddata-fixture-fixture
Emptying the test outbox
~~~~~~~~~~~~~~~~~~~~~~~~
**New in Django development version**
At the start of each test case, in addition to installing fixtures,
Django clears the contents of the test e-mail outbox.
If you use Django's custom ``TestCase`` class, the test runner will clear the
contents of the test e-mail outbox at the start of each test case.
For more detail on e-mail services during tests, see `E-mail services`_.
Assertions
~~~~~~~~~~
**New in Django development version**
Normal Python unit tests have a wide range of assertions, such as
``assertTrue`` and ``assertEquals`` that can be used to validate behavior.
``django.TestCase`` adds to these, providing some assertions
that can be useful in testing the behavior of web sites.
As Python's normal ``unittest.TestCase`` class implements assertion
methods such as ``assertTrue`` and ``assertEquals``, Django's custom
``TestCase`` class provides a number of custom assertion methods that are
useful for testing Web applications:
``assertContains(response, text, count=None, status_code=200)``
Assert that a response indicates that a page could be retrieved and
produced the nominated status code, and that ``text`` in the content
of the response. If ``count`` is provided, ``text`` must occur exactly
``count`` times in the response.
Asserts that a ``Response`` instance produced the given ``status_code`` and
that ``text`` appears in the content of the response. If ``count`` is
provided, ``text`` must occur exactly ``count`` times in the response.
``assertFormError(response, form, field, errors)``
Assert that a field on a form raised the provided list of errors when
Asserts that a field on a form raises the provided list of errors when
rendered on the form.
``form`` is the name the form object was given in the template context.
``form`` is the name the ``Form`` instance was given in the template
context. Note that this works only for ``newforms.Form`` instances, not
``oldforms.Form`` instances.
``field`` is the name of the field on the form to check. If ``field``
has a value of ``None``, non-field errors will be checked.
has a value of ``None``, non-field errors (errors you can access via
``form.non_field_errors()``) will be checked.
``errors`` is an error string, or a list of error strings, that are
expected as a result of form validation.
``assertTemplateNotUsed(response, template_name)``
Assert that the template with the given name was *not* used in rendering
Asserts that the template with the given name was *not* used in rendering
the response.
``assertRedirects(response, expected_path, status_code=302, target_status_code=200)``
Assert that the response received produced the nominated status code,
redirects the browser to the provided path, and that retrieving the provided
path yields a response with the target status code.
Asserts that the response return a ``status_code`` redirect status,
it redirected to ``expected_path`` and the subsequent page was received with
``target_status_code``.
``assertTemplateUsed(response, template_name)``
Assert that the template with the given name was used in rendering the
Asserts that the template with the given name was used in rendering the
response.
The name is a string such as ``'admin/index.html'``.
E-mail services
---------------
**New in Django development version**
If your view makes use of the `Django e-mail services`_, you don't really
want e-mail to be sent every time you run a test using that view.
When the Django test framework is initialized, it transparently replaces the
normal `SMTPConnection`_ class with a dummy implementation that redirects all
e-mail to a dummy outbox. This outbox, stored as ``django.core.mail.outbox``,
is a simple list of all `EmailMessage`_ instances that have been sent.
For example, during test conditions, it would be possible to run the following
code::
If any of your Django views send e-mail using `Django's e-mail functionality`_,
you probably don't want to send e-mail each time you run a test using that
view. For this reason, Django's test runner automatically redirects all
Django-sent e-mail to a dummy outbox. This lets you test every aspect of
sending e-mail -- from the number of messages sent to the contents of each
message -- without actually sending the messages.
The test runner accomplishes this by transparently replacing the normal
`SMTPConnection`_ class with a different version. (Don't worry -- this has no
effect on any other e-mail senders outside of Django, such as your machine's
mail server, if you're running one.)
During test running, each outgoing e-mail is saved in
``django.core.mail.outbox``. This is a simple list of all `EmailMessage`_
instances that have been sent. It does not exist under normal execution
conditions, i.e., when you're not running unit tests. The outbox is created
during test setup, along with the dummy `SMTPConnection`_. When the test
framework is torn down, the standard `SMTPConnection`_ class is restored, and
the test outbox is destroyed.
Here's an example test that examines ``django.core.mail.outbox`` for length
and contents::
from django.core import mail
from django.test import TestCase
# Send message
mail.send_mail('Subject here', 'Here is the message.', 'from@example.com',
['to@example.com'], fail_silently=False)
class EmailTest(TestCase):
def test_send_email(self):
# Send message.
mail.send_mail('Subject here', 'Here is the message.',
'from@example.com', ['to@example.com'],
fail_silently=False)
# One message has been sent
# Test that one message has been sent.
self.assertEqual(len(mail.outbox), 1)
# Subject of first message is correct
self.assertEqual(mail.outbox[0].subject, 'Subject here')
The ``mail.outbox`` object does not exist under normal execution conditions.
The outbox is created during test setup, along with the dummy `SMTPConnection`_.
When the test framework is torn down, the standard `SMTPConnection`_ class
is restored, and the test outbox is destroyed.
# Verify that the subject of the first message is correct.
self.assertEqual(mail.outbox[0].subject, 'Subject here')
As noted `previously`_, the test outbox is emptied at the start of every
test in a Django TestCase. To empty the outbox manually, assign the empty list
to mail.outbox::
test in a Django ``TestCase``. To empty the outbox manually, assign the
empty list to ``mail.outbox``::
from django.core import mail
# Empty the test outbox
mail.outbox = []
.. _`Django e-mail services`: ../email/
.. _`Django's e-mail functionality`: ../email/
.. _`SMTPConnection`: ../email/#the-emailmessage-and-smtpconnection-classes
.. _`EmailMessage`: ../email/#the-emailmessage-and-smtpconnection-classes
.. _`previously`: #emptying-the-test-outbox
Running tests
=============
Run your tests using your project's ``manage.py`` utility::
$ ./manage.py test
If you only want to run tests for a particular application, add the
application name to the command line. For example, if your
``INSTALLED_APPS`` contains ``myproject.polls`` and ``myproject.animals``,
but you only want to run the animals unit tests, run::
$ ./manage.py test animals
**New in Django development version:** If you use unit tests, you can be more
specific in the tests that are executed. To run a single test case in an
application (for example, the AnimalTestCase described previously), add the
name of the test case to the label on the command line::
$ ./manage.py test animals.AnimalTestCase
**New in Django development version:** 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
When you run your tests, you'll see a bunch of text flow by as the test
database is created and models are initialized. This test database is
created from scratch every time you run your tests.
By default, the test database gets its name by prepending ``test_`` to
the database name specified by the ``DATABASE_NAME`` setting; all other
database settings will the same as they would be for the project normally.
If you wish to use a name other than the default for the test database,
you can use the ``TEST_DATABASE_NAME`` setting to provide a name.
**New in Django development version:** For fine-grained control over the
character encoding of your database, use the ``TEST_DATABASE_CHARSET`` setting.
If you're using MySQL, you can also use the ``TEST_DATABASE_COLLATION`` setting
to control the particular collation used by the test database. See the
settings_ documentation for details of these advanced settings.
.. _settings: ../settings/
The test database is created by the user in the ``DATABASE_USER`` setting.
This user needs to have sufficient privileges to create a new database on the
system.
Once the test database has been established, Django will run your tests.
If everything goes well, at the end you'll see::
Using different testing frameworks
==================================
----------------------------------------------------------------------
Ran 22 tests in 0.221s
OK
Clearly, ``doctest`` and ``unittest`` are not the only Python testing
frameworks. While Django doesn't provide explicit support for alternative
frameworks, it does provide a way to invoke tests constructed for an
alternative framework as if they were normal Django tests.
If there are test failures, however, you'll see full details about what 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
When you run ``./manage.py test``, Django looks at the ``TEST_RUNNER``
setting to determine what to do. By default, ``TEST_RUNNER`` points to
``'django.test.simple.run_tests'``. This method defines the default Django
testing behavior. This behavior involves:
FAILED (failures=1)
#. Performing global pre-test setup.
The return code for the script is the total number of failed and erroneous
tests. If all the tests pass, the return code is 0.
#. Creating the test database.
Regardless of whether the tests pass or fail, the test database is destroyed when
all the tests have been executed.
#. Running ``syncdb`` to install models and initial data into the test
database.
Using a different testing framework
===================================
#. Looking for unit tests and doctests in the ``models.py`` and
``tests.py`` files in each installed application.
Doctest and Unittest are not the only Python testing frameworks. While
Django doesn't provide explicit support these alternative frameworks,
it does provide a mechanism to allow you to invoke tests constructed for
an alternative framework as if they were normal Django tests.
#. Running the unit tests and doctests that are found.
When you run ``./manage.py test``, Django looks at the ``TEST_RUNNER``
setting to determine what to do. By default, ``TEST_RUNNER`` points to
``django.test.simple.run_tests``. This method defines the default Django
testing behavior. This behavior involves:
#. Destroying the test database.
#. Performing global pre-test setup
#. Creating the test database
#. Running ``syncdb`` to install models and initial data into the test database
#. Looking for Unit Tests and Doctests in ``models.py`` and ``tests.py`` file for each installed application
#. Running the Unit Tests and Doctests that are found
#. Destroying the test database
#. Performing global post-test teardown
#. Performing global post-test teardown.
If you define your own test runner method and point ``TEST_RUNNER``
at that method, Django will execute your test runner whenever you run
``./manage.py test``. In this way, it is possible to use any test
framework that can be executed from Python code.
If you define your own test runner method and point ``TEST_RUNNER`` at that
method, Django will execute your test runner whenever you run
``./manage.py test``. In this way, it is possible to use any test framework
that can be executed from Python code.
Defining a test runner
----------------------
By convention, a test runner should be called ``run_tests``; however, you
can call it anything you want. The only requirement is that it has the
same arguments as the Django test runner:
**New in Django development version**
By convention, a test runner should be called ``run_tests``. The only strict
requirement is that it has the same arguments as the Django test runner:
``run_tests(test_labels, verbosity=1, interactive=True, extra_tests=[])``
**New in Django development version:** ``test_labels`` is a list of
strings describing the tests to be run. A test label can take one of
three forms:
``test_labels`` is a list of strings describing the tests to be run. A test
label can take one of three forms:
* ``app.TestCase.test_method`` - Run a single test method in a test case
* ``app.TestCase`` - Run all the test methods in a test case
* ``app`` - Search for and run all tests in the named application.
* ``app.TestCase.test_method`` -- Run a single test method in a test case.
* ``app.TestCase`` -- Run all the test methods in a test case.
* ``app`` -- Search for and run all tests in the named application.
If ``test_labels`` has a value of ``None``, the test runner should run
search for tests in all the applications in ``INSTALLED_APPS``.
Verbosity determines the amount of notification and debug information that
will be printed to the console; ``0`` is no output, ``1`` is normal output,
and ``2`` is verbose output.
``verbosity`` determines the amount of notification and debug information
that will be printed to the console; ``0`` is no output, ``1`` is normal
output, and ``2`` is verbose output.
**New in Django development version:** If ``interactive`` is ``True``, the
test suite may ask the user for instructions when the test suite is
executed. An example of this behavior would be asking for permission to
delete an existing test database. If ``interactive`` is ``False``, the
test suite must be able to run without any manual intervention.
If ``interactive`` is ``True``, the test suite has permission to ask the
user for instructions when the test suite is executed. An example of this
behavior would be asking for permission to delete an existing test
database. If ``interactive`` is ``False``, the test suite must be able to
run without any manual intervention.
``extra_tests`` is a list of extra ``TestCase`` instances to add to the
suite that is executed by the test runner. These extra tests are run
......@@ -718,28 +963,33 @@ a number of utility methods in the ``django.test.utils`` module.
``setup_test_environment()``
Performs any global pre-test setup, such as the installing the
instrumentation of the template rendering system and setting up
the dummy SMTPConnection.
the dummy ``SMTPConnection``.
``teardown_test_environment()``
Performs any global post-test teardown, such as removing the instrumentation
of the template rendering system and restoring normal e-mail services.
Performs any global post-test teardown, such as removing the
black magic hooks into the template system and restoring normal e-mail
services.
``create_test_db(verbosity=1, autoclobber=False)``
Creates a new test database, and run ``syncdb`` against it.
Creates a new test database and runs ``syncdb`` against it.
``verbosity`` has the same behavior as in ``run_tests()``.
``autoclobber`` describes the behavior that will occur if a database with
the same name as the test database is discovered:
``verbosity`` has the same behavior as in the test runner.
* If ``autoclobber`` is ``False``, the user will be asked to approve
destroying the existing database. ``sys.exit`` is called if the user
does not approve.
``Autoclobber`` describes the behavior that will occur if a database with
the same name as the test database is discovered. If ``autoclobber`` is False,
the user will be asked to approve destroying the existing database. ``sys.exit``
is called if the user does not approve. If autoclobber is ``True``, the database
will be destroyed without consulting the user.
* If autoclobber is ``True``, the database will be destroyed without
consulting the user.
``create_test_db()`` has the side effect of modifying
``settings.DATABASE_NAME`` to match the name of the test database.
``destroy_test_db(old_database_name, verbosity=1)``
Destroys the database with the name ``settings.DATABASE_NAME`` matching,
and restores the value of ``settings.DATABASE_NAME`` to the provided name.
Destroys the database whose name is in the ``DATABASE_NAME`` setting
and restores the value of ``DATABASE_NAME`` to the provided name.
``verbosity`` has the same behavior as in the test runner.
``verbosity`` has the same behavior as in ``run_tests()``.
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