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:
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.
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.
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.
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:
Here is an example model doctest:
# models.py
from django.db import models
class Animal(models.Model):
"""
An animal that knows how to make noise
# Create some animals
>>> lion = Animal.objects.create(name="lion", sound="roar")
>>> cat = Animal.objects.create(name="cat", sound="meow")
# Make 'em speak
>>> lion.speak()
'The lion says "roar"'
>>> cat.speak()
'The cat says "meow"'
"""
name = models.CharField(max_length=20)
sound = models.CharField(max_length=20)
def speak(self):
return 'The %s says "%s"' % (self.name, self.sound)
When you run your tests, the test runner will find this docstring, notice that portions of it look like an interactive Python session, and execute those lines while checking that the results match.
In the case of model tests, note that the test runner takes care of creating its own test database. That is, any test that accesses a database -- by creating and saving model instances, for example -- will not affect your production database. 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.
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:
This example unittest.TestCase subclass is equivalent to the example given in the doctest section above:
import unittest
from myapp.models import Animal
class AnimalTestCase(unittest.TestCase):
def setUp(self):
self.lion = Animal.objects.create(name="lion", sound="roar")
self.cat = Animal.objects.create(name="cat", sound="meow")
def testSpeaking(self):
self.assertEquals(self.lion.speak(), 'The lion says "roar"')
self.assertEquals(self.cat.speak(), 'The cat says "meow"')
When you run your tests, the default behavior of the test utility is to find all the test cases (that is, subclasses of unittest.TestCase) in models.py and tests.py, automatically build a test suite out of those test cases, and run that suite.
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.
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.
Once you've written tests, run them using the test subcommand of 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.
You can be even more specific by naming an individual test case. To run a single test case in an application (for example, the AnimalTestCase described in the "Writing unit tests" section), add the name of the test case to the label on the command line:
$ ./manage.py test animals.AnimalTestCase
And it gets even more granular than that! To run a single test method inside a test case, add the name of the test method to the label:
$ ./manage.py test animals.AnimalTestCase.testFluffyAnimals
You can use the same rules if you're using doctests. Django will use the test label as a path to the test method or class that you want to run. If your models.py or tests.py has a function with a doctest, or class with a class-level doctest, you can invoke that test by appending the name of the test method or class to the label:
$ ./manage.py test animals.classify
If you want to run the doctest for a specific method in a class, add the name of the method to the label:
$ ./manage.py test animals.Classifier.run
If you're using a __test__ dictionary to specify doctests for a module, Django will use the label as a key in the __test__ dictionary for defined in models.py and tests.py.
If you press Ctrl-C while the tests are running, the test runner will wait for the currently running test to complete and then exit gracefully. During a graceful exit the test runner will output details of any test failures, report on how many tests were run and how many errors and failures were encountered, and destroy any test databases as usual. Thus pressing Ctrl-C can be very useful if you forget to pass the --failfast option, notice that some tests are unexpectedly failing, and want to get details on the failures without waiting for the full test run to complete.
If you do not want to wait for the currently running test to finish, you can press Ctrl-C a second time and the test run will halt immediately, but not gracefully. No details of the tests run before the interruption will be reported, and any test databases created by the run will not be destroyed.
Tests that require a database (namely, model tests) will not use your "real" (production) database. Separate, blank databases are created for the tests.
Regardless of whether the tests pass or fail, the test databases are destroyed when all the tests have been executed.
By default the test databases get their names by prepending test_ to the value of the NAME settings for the databases defined in DATABASES. When using the SQLite database engine the tests will by default use an in-memory database (i.e., the database will be created in memory, bypassing the filesystem entirely!). If you want to use a different database name, specify TEST_NAME in the dictionary for any given database in DATABASES.
Aside from using a separate database, the test runner will otherwise use all of the same database settings you have in your settings file: ENGINE, USER, HOST, etc. The test database is created by the user specified by USER, so you'll need to make sure that the given user account has sufficient privileges to create a new database on the system.
For fine-grained control over the character encoding of your test database, use the TEST_CHARSET option. If you're using MySQL, you can also use the TEST_COLLATION option to control the particular collation used by the test database. See the settings documentation for details of these advanced settings.
If you're testing a multiple database configuration with master/slave replication, this strategy of creating test databases poses a problem. When the test databases are created, there won't be any replication, and as a result, data created on the master won't be seen on the slave.
To compensate for this, Django allows you to define that a database is a test mirror. Consider the following (simplified) example database configuration:
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.mysql',
'NAME': 'myproject',
'HOST': 'dbmaster',
# ... plus some other settings
},
'slave': {
'ENGINE': 'django.db.backends.mysql',
'NAME': 'myproject',
'HOST': 'dbslave',
'TEST_MIRROR': 'default'
# ... plus some other settings
}
}
In this setup, we have two database servers: dbmaster, described by the database alias default, and dbslave described by the alias slave. As you might expect, dbslave has been configured by the database administrator as a read slave of dbmaster, so in normal activity, any write to default will appear on slave.
If Django created two independent test databases, this would break any tests that expected replication to occur. However, the slave database has been configured as a test mirror (using the TEST_MIRROR setting), indicating that under testing, slave should be treated as a mirror of default.
When the test environment is configured, a test version of slave will not be created. Instead the connection to slave will be redirected to point at default. As a result, writes to default will appear on slave -- but because they are actually the same database, not because there is data replication between the two databases.
Regardless of the value of the DEBUG setting in your configuration file, all Django tests run with DEBUG=False. This is to ensure that the observed output of your code matches what will be seen in a production setting.
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.
Django provides a small set of tools that come in handy when writing tests.
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:
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:
A comprehensive test suite should use a combination of both test types.
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.
Use the django.test.client.Client class to make requests. It requires no arguments at time of construction:
Once you have a Client instance, you can call any of the following methods:
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 django.http.HttpRequest.is_ajax() method.
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)]
Makes a POST request on the provided path and returns a Response object, which is documented below.
The key-value pairs in the data dictionary are used to submit POST data. For example:
>>> c = Client()
>>> c.post('/login/', {'name': 'fred', 'passwd': 'secret'})
...will result in the evaluation of a POST request to this URL:
/login/
...with this POST data:
name=fred&passwd=secret
If you provide content_type (e.g., text/xml for an XML payload), the contents of data will be sent as-is in the POST request, using content_type in the HTTP Content-Type header.
If you don't provide a value for content_type, the values in data will be transmitted with a content type of multipart/form-data. In this case, the key-value pairs in data will be encoded as a multipart message and used to create the POST data payload.
To submit multiple values for a given key -- for example, to specify the selections for a <select multiple> -- provide the values as a list or tuple for the required key. For example, this value of data would submit three selected values for the field named choices:
{'choices': ('a', 'b', 'd')}
Submitting files is a special case. To POST a file, you need only provide the file field name as a key, and a file handle to the file you wish to upload as a value. For example:
>>> c = Client()
>>> f = open('wishlist.doc')
>>> c.post('/customers/wishes/', {'name': 'fred', 'attachment': f})
>>> f.close()
(The name attachment here is not relevant; use whatever name your file-processing code expects.)
Note that if you wish to use the same file handle for multiple post() calls then you will need to manually reset the file pointer between posts. The easiest way to do this is to manually close the file after it has been provided to post(), as demonstrated above.
You should also ensure that the file is opened in a way that allows the data to be read. If your file contains binary data such as an image, this means you will need to open the file in rb (read binary) mode.
The extra argument acts the same as for Client.get().
If the URL you request with a POST contains encoded parameters, these parameters will be made available in the request.GET data. For example, if you were to make the request:
>>> c.post('/login/?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.
Makes a HEAD request on the provided path and returns a Response object. Useful for testing RESTful interfaces. Acts just like 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.
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 Client.get().
Makes a PUT request on the provided path and returns a Response object. Useful for testing RESTful interfaces. Acts just like 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.
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 Client.get().
If your site uses Django's authentication system and you deal with logging in users, you can use the test client's login() method to simulate the effect of a user logging into the site.
After you call this method, the test client will have all the cookies and session data required to pass any login-based tests that may form part of a view.
The format of the credentials argument depends on which authentication backend you're using (which is configured by your AUTHENTICATION_BACKENDS setting). If you're using the standard authentication backend provided by Django (ModelBackend), credentials should be the user's username and password, provided as keyword arguments:
>>> c = Client()
>>> c.login(username='fred', password='secret')
# Now you can access a view that's only available to logged-in users.
If you're using a different authentication backend, this method may require different credentials. It requires whichever credentials are required by your backend's authenticate() method.
login() returns True if it the credentials were accepted and login was successful.
Finally, you'll need to remember to create user accounts before you can use this method. As we explained above, the test runner is executed using a test database, which contains no users by default. As a result, user accounts that are valid on your production site will not work under test conditions. You'll need to create users as part of the test suite -- either manually (using the Django model API) or with a test fixture. 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 set_password() function to store a correctly hashed password. Alternatively, you can use the create_user() helper method to create a new user with a correctly hashed password.
If your site uses Django's authentication system, the logout() method can be used to simulate the effect of a user logging out of your site.
After you call this method, the test client will have all the cookies and session data cleared to defaults. Subsequent requests will appear to come from an AnonymousUser.
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:
The template Context instance that was used to render the template that produced the response content.
If the rendered page used multiple templates, then context will be a list of Context objects, in the order in which they were rendered.
Regardless of the number of templates used during rendering, you can retrieve context values using the [] operator. For example, the context variable name could be retrieved using:
>>> response = client.get('/foo/')
>>> response.context['name']
'Arthur'
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.
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'].
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.
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.
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)
Normal Python unit test classes extend a base class of unittest.TestCase. Django provides an extension of this base class:
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.
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.
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)
A test case for a database-backed Web site isn't much use if there isn't any data in the database. To make it easy to put test data into the database, Django's custom TestCase class provides a way of loading fixtures.
A fixture is a collection of data that Django knows how to import into a database. For example, if your site has user accounts, you might set up a fixture of fake user accounts in order to populate your database during tests.
The most straightforward way of creating a fixture is to use the manage.py dumpdata command. This assumes you already have some data in your database. See the dumpdata documentation for more details.
Note
If you've ever run manage.py syncdb, you've already used a fixture without even knowing it! When you call syncdb in the database for the first time, Django installs a fixture called initial_data. This gives you a way of populating a new database with any initial data, such as a default set of categories.
Fixtures with other names can always be installed manually using the manage.py loaddata command.
Once you've created a fixture and placed it in a fixtures directory in one of your 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.
call_setup_methods()
def testFluffyAnimals(self):
# A test that uses the fixtures.
call_some_test_code()
Here's specifically what will happen:
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.
If your application provides views, you may want to include tests that use the test client to exercise those views. However, an end user is free to deploy the views in your application at any URL of their choosing. This means that your tests can't rely upon the fact that your views will be available at a particular URL.
In order to provide a reliable URL space for your test, django.test.TestCase provides the ability to customize the URLconf configuration for the duration of the execution of a test suite. If your TestCase instance defines an urls attribute, the TestCase will use the value of that attribute as the ROOT_URLCONF for the duration of that test.
For example:
from django.test import TestCase
class TestMyViews(TestCase):
urls = 'myapp.test_urls'
def testIndexPageView(self):
# Here you'd test your view using ``Client``.
call_some_test_code()
This test case will use the contents of myapp.test_urls as the URLconf for the duration of the test case.
Django sets up a test database corresponding to every database that is defined in the DATABASES definition in your settings file. However, a big part of the time taken to run a Django TestCase is consumed by the call to flush that ensures that you have a clean database at the start of each test run. If you have multiple databases, multiple flushes are required (one for each database), which can be a time consuming activity -- especially if your tests don't need to test multi-database activity.
As an optimization, Django only flushes the default database at the start of each test run. If your setup contains multiple databases, and you have a test that requires every database to be clean, you can use the multi_db attribute on the test suite to request a full flush.
For example:
class TestMyViews(TestCase):
multi_db = True
def testIndexPageView(self):
call_some_test_code()
This test case will flush all the test databases before running testIndexPageView.
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.
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:
The failure messages given by the assertion methods can be customized with the msg_prefix argument. This string will be prefixed to any failure message generated by the assertion. This allows you to provide additional details that may help you to identify the location and cause of an failure in your test suite.
Asserts that a field on a form raises the provided list of errors when rendered on the form.
form is the name the Form instance was given in the template context.
field is the name of the field on the form to check. If field has a value of None, non-field errors (errors you can access via form.non_field_errors()) will be checked.
errors is an error string, or a list of error strings, that are expected as a result of form validation.
Asserts that the template with the given name was used in rendering the response.
The name is a string such as 'admin/index.html'.
Asserts that the response return a status_code redirect status, it redirected to expected_url (including any GET data), and the final page was received with target_status_code.
If your request used the follow argument, the expected_url and target_status_code will be the url and status code for the final point of the redirect chain.
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 email backend with a testing backend. (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. The outbox attribute is a special attribute that is created only when the locmem e-mail backend is used. It doesn't normally exist as part of the django.core.mail module and you can't import it directly. The code below shows how to access this attribute correctly.
Here's an example test that examines django.core.mail.outbox for length and contents:
from django.core import mail
from django.test import TestCase
class EmailTest(TestCase):
def test_send_email(self):
# Send message.
mail.send_mail('Subject here', 'Here is the message.',
'from@example.com', ['to@example.com'],
fail_silently=False)
# Test that one message has been sent.
self.assertEquals(len(mail.outbox), 1)
# Verify that the subject of the first message is correct.
self.assertEquals(mail.outbox[0].subject, 'Subject here')
As noted previously, the test outbox is emptied at the start of every test in a Django TestCase. To empty the outbox manually, assign the empty list to mail.outbox:
from django.core import mail
# Empty the test outbox
mail.outbox = []
Clearly, doctest and unittest are not the only Python testing frameworks. While Django doesn't provide explicit support for alternative frameworks, it does provide a way to invoke tests constructed for an alternative framework as if they were normal Django tests.
When you run ./manage.py test, Django looks at the TEST_RUNNER setting to determine what to do. By default, TEST_RUNNER points to 'django.test.simple.DjangoTestSuiteRunner'. This class defines the default Django testing behavior. This behavior involves:
If you define your own test runner class and point TEST_RUNNER at that class, 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, or to modify the Django test execution process to satisfy whatever testing requirements you may have.
A test runner is a class defining a run_tests() method. Django ships with a DjangoTestSuiteRunner class that defines the default Django testing behavior. This class defines the run_tests() entry point, plus a selection of other methods that are used to by run_tests() to set up, execute and tear down the test suite.
verbosity determines the amount of notification and debug information that will be printed to the console; 0 is no output, 1 is normal output, and 2 is verbose output.
If interactive is True, the test suite has permission to ask the user for instructions when the test suite is executed. An example of this behavior would be asking for permission to delete an existing test database. If interactive is False, the test suite must be able to run without any manual intervention.
If failfast is True, the test suite will stop running after the first test failure is detected.
Django will, from time to time, extend the capabilities of the test runner by adding new arguments. The **kwargs declaration allows for this expansion. If you subclass DjangoTestSuiteRunner or write your own test runner, ensure accept and handle the **kwargs parameter.
Run the test suite.
test_labels is a list of strings describing the tests to be run. A test label can take one of three forms:
If test_labels has a value of None, the test runner should run search for tests in all the applications in INSTALLED_APPS.
extra_tests is a list of extra TestCase instances to add to the suite that is executed by the test runner. These extra tests are run in addition to those discovered in the modules listed in test_labels.
This method should return the number of tests that failed.
Constructs a test suite that matches the test labels provided.
test_labels is a list of strings describing the tests to be run. A test label can take one of three forms:
If test_labels has a value of None, the test runner should run search for tests in all the applications in INSTALLED_APPS.
extra_tests is a list of extra TestCase instances to add to the suite that is executed by the test runner. These extra tests are run in addition to those discovered in the modules listed in test_labels.
Returns a TestSuite instance ready to be run.
Creates the test databases.
Returns a data structure that provides enough detail to undo the changes that have been made. This data will be provided to the teardown_databases() function at the conclusion of testing.
Runs the test suite.
Returns the result produced by the running the test suite.
Destroys the test databases, restoring pre-test conditions.
old_config is a data structure defining the changes in the database configuration that need to be reversed. It is the return value of the setup_databases() method.
To assist in the creation of your own test runner, Django provides a number of utility methods in the django.test.utils module.
The creation module of the database backend (connection.creation) also provides some utilities that can be useful during testing.
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:
Returns the name of the test database that it created.
create_test_db() has the side effect of modifying the value of NAME in DATABASES to match the name of the test database.
Jul 05, 2010