=========================== Testing Django applications =========================== .. module:: django.test :synopsis: Testing tools for Django applications. Automated testing is an extremely useful bug-killing tool for the modern Web developer. You can use a collection of tests -- a **test suite** -- to solve, or avoid, a number of problems: * When you're writing new code, you can use tests to validate your code works as expected. * When you're refactoring or modifying old code, you can use tests to ensure your changes haven't affected your application's behavior unexpectedly. Testing a Web application is a complex task, because a Web application is made of several layers of logic -- from HTTP-level request handling, to form validation and processing, to template rendering. With Django's test-execution framework and assorted utilities, you can simulate requests, insert test data, inspect your application's output and generally verify your code is doing what it should be doing. The best part is, it's really easy. This document is split into two primary sections. First, we explain how to write tests with Django. Then, we explain how to run them. Writing tests ============= There are two primary ways to write tests with Django, corresponding to the two test frameworks that ship in the Python standard library. The two frameworks are: * **Unit tests** -- tests that are expressed as methods on a Python class that subclasses ``unittest.TestCase`` or Django's customized :class:`TestCase`. For example:: import unittest class MyFuncTestCase(unittest.TestCase): def testBasic(self): a = ['larry', 'curly', 'moe'] self.assertEqual(my_func(a, 0), 'larry') self.assertEqual(my_func(a, 1), 'curly') * **Doctests** -- tests that are embedded in your functions' docstrings and are written in a way that emulates a session of the Python interactive interpreter. For example:: def my_func(a_list, idx): """ >>> a = ['larry', 'curly', 'moe'] >>> my_func(a, 0) 'larry' >>> my_func(a, 1) 'curly' """ return a_list[idx] We'll discuss choosing the appropriate test framework later, however, most experienced developers prefer unit tests. You can also use any *other* Python test framework, as we'll explain in a bit. Writing unit tests ------------------ Django's unit tests use a Python standard library module: unittest_. This module defines tests in class-based approach. .. admonition:: unittest2 .. versionchanged:: 1.3 Python 2.7 introduced some major changes to the unittest library, adding some extremely useful features. To ensure that every Django project can benefit from these new features, Django ships with a copy of unittest2_, a copy of the Python 2.7 unittest library, backported for Python 2.4 compatibility. To access this library, Django provides the ``django.utils.unittest`` module alias. If you are using Python 2.7, or you have installed unittest2 locally, Django will map the alias to the installed version of the unittest library. Otherwise, Django will use it's own bundled version of unittest2. To use this alias, simply use:: from django.utils import unittest wherever you would have historically used:: import unittest If you want to continue to use the base unittest libary, you can -- you just won't get any of the nice new unittest2 features. .. _unittest2: http://pypi.python.org/pypi/unittest2 For a given Django application, the test runner looks for unit tests in two places: * The ``models.py`` file. The test runner looks for any subclass of ``unittest.TestCase`` in this module. * A file called ``tests.py`` in the application directory -- i.e., the directory that holds ``models.py``. Again, the test runner looks for any subclass of ``unittest.TestCase`` in this module. Here is an example ``unittest.TestCase`` subclass:: from django.utils import unittest from myapp.models import Animal class AnimalTestCase(unittest.TestCase): def setUp(self): self.lion = Animal.objects.create(name="lion", sound="roar") self.cat = Animal.objects.create(name="cat", sound="meow") def testSpeaking(self): self.assertEqual(self.lion.speak(), 'The lion says "roar"') self.assertEqual(self.cat.speak(), 'The cat says "meow"') When you :ref:`run your tests `, the default behavior of the test utility is to find all the test cases (that is, subclasses of ``unittest.TestCase``) in ``models.py`` and ``tests.py``, automatically build a test suite out of those test cases, and run that suite. There is a second way to define the test suite for a module: if you define a function called ``suite()`` in either ``models.py`` or ``tests.py``, the Django test runner will use that function to construct the test suite for that module. This follows the `suggested organization`_ for unit tests. See the Python documentation for more details on how to construct a complex test suite. For more details about ``unittest``, see the `standard library unittest documentation`_. .. _unittest: http://docs.python.org/library/unittest.html .. _standard library unittest documentation: unittest_ .. _suggested organization: http://docs.python.org/library/unittest.html#organizing-tests Writing doctests ---------------- Doctests use Python's standard doctest_ module, which searches your docstrings for statements that resemble a session of the Python interactive interpreter. A full explanation of how doctest works is out of the scope of this document; read Python's official documentation for the details. .. admonition:: What's a **docstring**? A good explanation of docstrings (and some guidelines for using them effectively) can be found in :pep:`257`: A docstring is a string literal that occurs as the first statement in a module, function, class, or method definition. Such a docstring becomes the ``__doc__`` special attribute of that object. For example, this function has a docstring that describes what it does:: def add_two(num): "Return the result of adding two to the provided number." return num + 2 Because tests often make great documentation, putting tests directly in your docstrings is an effective way to document *and* test your code. As with unit tests, for a given Django application, the test runner looks for doctests in two places: * The ``models.py`` file. You can define module-level doctests and/or a doctest for individual models. It's common practice to put application-level doctests in the module docstring and model-level doctests in the model docstrings. * A file called ``tests.py`` in the application directory -- i.e., the directory that holds ``models.py``. This file is a hook for any and all doctests you want to write that aren't necessarily related to models. This example doctest is equivalent to the example given in the unittest section above:: # models.py from django.db import models class Animal(models.Model): """ An animal that knows how to make noise # Create some animals >>> lion = Animal.objects.create(name="lion", sound="roar") >>> cat = Animal.objects.create(name="cat", sound="meow") # Make 'em speak >>> lion.speak() 'The lion says "roar"' >>> cat.speak() 'The cat says "meow"' """ name = models.CharField(max_length=20) sound = models.CharField(max_length=20) def speak(self): return 'The %s says "%s"' % (self.name, self.sound) When you :ref:`run your tests `, the test runner will find this docstring, notice that portions of it look like an interactive Python session, and execute those lines while checking that the results match. In the case of model tests, note that the test runner takes care of creating its own test database. That is, any test that accesses a database -- by creating and saving model instances, for example -- will not affect your production database. However, the database is not refreshed between doctests, so if your doctest requires a certain state you should consider flushing the database or loading a fixture. (See the section on fixtures, below, for more on this.) Note that to use this feature, the database user Django is connecting as must have ``CREATE DATABASE`` rights. For more details about how doctest works, see the `standard library documentation for doctest`_. .. _doctest: http://docs.python.org/library/doctest.html .. _standard library documentation for doctest: doctest_ Which should I use? ------------------- Because Django supports both of the standard Python test frameworks, it's up to you and your tastes to decide which one to use. You can even decide to use *both*. For developers new to testing, however, this choice can seem confusing. Here, then, are a few key differences to help you decide which approach is right for you: * If you've been using Python for a while, ``doctest`` will probably feel more "pythonic". It's designed to make writing tests as easy as possible, so it requires no overhead of writing classes or methods. You simply put tests in docstrings. This has the added advantage of serving as documentation (and correct documentation, at that!). However, while doctests are good for some simple example code, they are not very good if you want to produce either high quality, comprehensive tests or high quality documentation. Test failures are often difficult to debug as it can be unclear exactly why the test failed. Thus, doctests should generally be avoided and used primarily for documentation examples only. * The ``unittest`` framework will probably feel very familiar to developers coming from Java. ``unittest`` is inspired by Java's JUnit, so you'll feel at home with this method if you've used JUnit or any test framework inspired by JUnit. * If you need to write a bunch of tests that share similar code, then you'll appreciate the ``unittest`` framework's organization around classes and methods. This makes it easy to abstract common tasks into common methods. The framework also supports explicit setup and/or cleanup routines, which give you a high level of control over the environment in which your test cases are run. * If you're writing tests for Django itself, you should use ``unittest``. .. _running-tests: Running tests ============= Once you've written tests, run them using the :djadmin:`test` command of your project's ``manage.py`` utility:: $ ./manage.py test By default, this will run every test in every application in :setting:`INSTALLED_APPS`. If you only want to run tests for a particular application, add the application name to the command line. For example, if your :setting:`INSTALLED_APPS` contains ``'myproject.polls'`` and ``'myproject.animals'``, you can run the ``myproject.animals`` unit tests alone with this command:: $ ./manage.py test animals Note that we used ``animals``, not ``myproject.animals``. You can be even *more* specific by naming an individual test case. To run a single test case in an application (for example, the ``AnimalTestCase`` described in the "Writing unit tests" section), add the name of the test case to the label on the command line:: $ ./manage.py test animals.AnimalTestCase And it gets even more granular than that! To run a *single* test method inside a test case, add the name of the test method to the label:: $ ./manage.py test animals.AnimalTestCase.testFluffyAnimals .. versionadded:: 1.2 The ability to select individual doctests was added. You can use the same rules if you're using doctests. Django will use the test label as a path to the test method or class that you want to run. If your ``models.py`` or ``tests.py`` has a function with a doctest, or class with a class-level doctest, you can invoke that test by appending the name of the test method or class to the label:: $ ./manage.py test animals.classify If you want to run the doctest for a specific method in a class, add the name of the method to the label:: $ ./manage.py test animals.Classifier.run If you're using a ``__test__`` dictionary to specify doctests for a module, Django will use the label as a key in the ``__test__`` dictionary for defined in ``models.py`` and ``tests.py``. .. versionadded:: 1.2 You can now trigger a graceful exit from a test run by pressing ``Ctrl-C``. If you press ``Ctrl-C`` while the tests are running, the test runner will wait for the currently running test to complete and then exit gracefully. During a graceful exit the test runner will output details of any test failures, report on how many tests were run and how many errors and failures were encountered, and destroy any test databases as usual. Thus pressing ``Ctrl-C`` can be very useful if you forget to pass the :djadminopt:`--failfast` option, notice that some tests are unexpectedly failing, and want to get details on the failures without waiting for the full test run to complete. If you do not want to wait for the currently running test to finish, you can press ``Ctrl-C`` a second time and the test run will halt immediately, but not gracefully. No details of the tests run before the interruption will be reported, and any test databases created by the run will not be destroyed. .. admonition:: Test with warnings enabled It's a good idea to run your tests with Python warnings enabled: ``python -Wall manage.py test``. The ``-Wall`` flag tells Python to display deprecation warnings. Django, like many other Python libraries, uses these warnings to flag when features are going away. It also might flag areas in your code that aren't strictly wrong but could benefit from a better implementation. Running tests outside the test runner ------------------------------------- If you want to run tests outside of ``./manage.py test`` -- for example, from a shell prompt -- you will need to set up the test environment first. Django provides a convenience method to do this:: >>> from django.test.utils import setup_test_environment >>> setup_test_environment() This convenience method sets up the test database, and puts other Django features into modes that allow for repeatable testing. The call to :meth:`~django.test.utils.setup_test_environment` is made automatically as part of the setup of `./manage.py test`. You only need to manually invoke this method if you're not using running your tests via Django's test runner. The test database ----------------- Tests that require a database (namely, model tests) will not use your "real" (production) database. Separate, blank databases are created for the tests. Regardless of whether the tests pass or fail, the test databases are destroyed when all the tests have been executed. By default the test databases get their names by prepending ``test_`` to the value of the :setting:`NAME` settings for the databases defined in :setting:`DATABASES`. When using the SQLite database engine the tests will by default use an in-memory database (i.e., the database will be created in memory, bypassing the filesystem entirely!). If you want to use a different database name, specify :setting:`TEST_NAME` in the dictionary for any given database in :setting:`DATABASES`. Aside from using a separate database, the test runner will otherwise use all of the same database settings you have in your settings file: :setting:`ENGINE`, :setting:`USER`, :setting:`HOST`, etc. The test database is created by the user specified by ``USER``, so you'll need to make sure that the given user account has sufficient privileges to create a new database on the system. For fine-grained control over the character encoding of your test database, use the :setting:`TEST_CHARSET` option. If you're using MySQL, you can also use the :setting:`TEST_COLLATION` option to control the particular collation used by the test database. See the :doc:`settings documentation ` for details of these advanced settings. .. _topics-testing-masterslave: Testing master/slave configurations ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. versionadded:: 1.2 If you're testing a multiple database configuration with master/slave replication, this strategy of creating test databases poses a problem. When the test databases are created, there won't be any replication, and as a result, data created on the master won't be seen on the slave. To compensate for this, Django allows you to define that a database is a *test mirror*. Consider the following (simplified) example database configuration:: DATABASES = { 'default': { 'ENGINE': 'django.db.backends.mysql', 'NAME': 'myproject', 'HOST': 'dbmaster', # ... plus some other settings }, 'slave': { 'ENGINE': 'django.db.backends.mysql', 'NAME': 'myproject', 'HOST': 'dbslave', 'TEST_MIRROR': 'default' # ... plus some other settings } } In this setup, we have two database servers: ``dbmaster``, described by the database alias ``default``, and ``dbslave`` described by the alias ``slave``. As you might expect, ``dbslave`` has been configured by the database administrator as a read slave of ``dbmaster``, so in normal activity, any write to ``default`` will appear on ``slave``. If Django created two independent test databases, this would break any tests that expected replication to occur. However, the ``slave`` database has been configured as a test mirror (using the :setting:`TEST_MIRROR` setting), indicating that under testing, ``slave`` should be treated as a mirror of ``default``. When the test environment is configured, a test version of ``slave`` will *not* be created. Instead the connection to ``slave`` will be redirected to point at ``default``. As a result, writes to ``default`` will appear on ``slave`` -- but because they are actually the same database, not because there is data replication between the two databases. .. _topics-testing-creation-dependencies: Controlling creation order for test databases ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. versionadded:: 1.3 By default, Django will always create the ``default`` database first. However, no guarantees are made on the creation order of any other databases in your test setup. If your database configuration requires a specific creation order, you can specify the dependencies that exist using the :setting:`TEST_DEPENDENCIES` setting. Consider the following (simplified) example database configuration:: DATABASES = { 'default': { # ... db settings 'TEST_DEPENDENCIES': ['diamonds'] }, 'diamonds': { # ... db settings }, 'clubs': { # ... db settings 'TEST_DEPENDENCIES': ['diamonds'] }, 'spades': { # ... db settings 'TEST_DEPENDENCIES': ['diamonds','hearts'] }, 'hearts': { # ... db settings 'TEST_DEPENDENCIES': ['diamonds','clubs'] } } Under this configuration, the ``diamonds`` database will be created first, as it is the only database alias without dependencies. The ``default`` and ``clubs`` alias will be created next (although the order of creation of this pair is not guaranteed); then ``hearts``; and finally ``spades``. If there are any circular dependencies in the :setting:`TEST_DEPENDENCIES` definition, an ``ImproperlyConfigured`` exception will be raised. Other test conditions --------------------- Regardless of the value of the :setting:`DEBUG` setting in your configuration file, all Django tests run with :setting:`DEBUG`\=False. This is to ensure that the observed output of your code matches what will be seen in a production setting. Understanding the test output ----------------------------- When you run your tests, you'll see a number of messages as the test runner prepares itself. You can control the level of detail of these messages with the ``verbosity`` option on the command line:: Creating test database... Creating table myapp_animal Creating table myapp_mineral Loading 'initial_data' fixtures... No fixtures found. This tells you that the test runner is creating a test database, as described in the previous section. Once the test database has been created, Django will run your tests. If everything goes well, you'll see something like this:: ---------------------------------------------------------------------- Ran 22 tests in 0.221s OK If there are test failures, however, you'll see full details about which tests failed:: ====================================================================== FAIL: Doctest: ellington.core.throttle.models ---------------------------------------------------------------------- Traceback (most recent call last): File "/dev/django/test/doctest.py", line 2153, in runTest raise self.failureException(self.format_failure(new.getvalue())) AssertionError: Failed doctest test for myapp.models File "/dev/myapp/models.py", line 0, in models ---------------------------------------------------------------------- File "/dev/myapp/models.py", line 14, in myapp.models Failed example: throttle.check("actor A", "action one", limit=2, hours=1) Expected: True Got: False ---------------------------------------------------------------------- Ran 2 tests in 0.048s FAILED (failures=1) A full explanation of this error output is beyond the scope of this document, but it's pretty intuitive. You can consult the documentation of Python's ``unittest`` library for details. Note that the return code for the test-runner script is the total number of failed and erroneous tests. If all the tests pass, the return code is 0. This feature is useful if you're using the test-runner script in a shell script and need to test for success or failure at that level. Testing tools ============= Django provides a small set of tools that come in handy when writing tests. .. _test-client: The test client --------------- .. module:: django.test.client :synopsis: Django's test client. The test client is a Python class that acts as a dummy Web browser, allowing you to test your views and interact with your Django-powered application programmatically. Some of the things you can do with the test client are: * Simulate GET and POST requests on a URL and observe the response -- everything from low-level HTTP (result headers and status codes) to page content. * Test that the correct view is executed for a given URL. * Test that a given request is rendered by a given Django template, with a template context that contains certain values. Note that the test client is not intended to be a replacement for Twill_, Selenium_, or other "in-browser" frameworks. Django's test client has a different focus. In short: * Use Django's test client to establish that the correct view is being called and that the view is collecting the correct context data. * Use in-browser frameworks such as Twill and Selenium to test *rendered* HTML and the *behavior* of Web pages, namely JavaScript functionality. A comprehensive test suite should use a combination of both test types. .. _Twill: http://twill.idyll.org/ .. _Selenium: http://seleniumhq.org/ Overview and a quick example ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ To use the test client, instantiate ``django.test.client.Client`` and retrieve Web pages:: >>> from django.test.client import Client >>> c = Client() >>> response = c.post('/login/', {'username': 'john', 'password': 'smith'}) >>> response.status_code 200 >>> response = c.get('/customer/details/') >>> response.content '>> c.get('/login/') This is incorrect:: >>> c.get('http://www.example.com/login/') The test client is not capable of retrieving Web pages that are not powered by your Django project. If you need to retrieve other Web pages, use a Python standard library module such as urllib_ or urllib2_. * To resolve URLs, the test client uses whatever URLconf is pointed-to by your :setting:`ROOT_URLCONF` setting. * Although the above example would work in the Python interactive interpreter, some of the test client's functionality, notably the template-related functionality, is only available *while tests are running*. The reason for this is that Django's test runner performs a bit of black magic in order to determine which template was loaded by a given view. This black magic (essentially a patching of Django's template system in memory) only happens during test running. * By default, the test client will disable any CSRF checks performed by your site. .. versionadded:: 1.2.2 If, for some reason, you *want* the test client to perform CSRF checks, you can create an instance of the test client that enforces CSRF checks. To do this, pass in the ``enforce_csrf_checks`` argument when you construct your client:: >>> from django.test import Client >>> csrf_client = Client(enforce_csrf_checks=True) .. _urllib: http://docs.python.org/library/urllib.html .. _urllib2: http://docs.python.org/library/urllib2.html Making requests ~~~~~~~~~~~~~~~ Use the ``django.test.client.Client`` class to make requests. It requires no arguments at time of construction: .. class:: Client() Once you have a ``Client`` instance, you can call any of the following methods: .. method:: Client.get(path, data={}, follow=False, **extra) Makes a GET request on the provided ``path`` and returns a ``Response`` object, which is documented below. The key-value pairs in the ``data`` dictionary are used to create a GET data payload. For example:: >>> c = Client() >>> c.get('/customers/details/', {'name': 'fred', 'age': 7}) ...will result in the evaluation of a GET request equivalent to:: /customers/details/?name=fred&age=7 The ``extra`` keyword arguments parameter can be used to specify headers to be sent in the request. For example:: >>> c = Client() >>> c.get('/customers/details/', {'name': 'fred', 'age': 7}, ... HTTP_X_REQUESTED_WITH='XMLHttpRequest') ...will send the HTTP header ``HTTP_X_REQUESTED_WITH`` to the details view, which is a good way to test code paths that use the :meth:`django.http.HttpRequest.is_ajax()` method. If you already have the GET arguments in URL-encoded form, you can use that encoding instead of using the data argument. For example, the previous GET request could also be posed as:: >>> c = Client() >>> c.get('/customers/details/?name=fred&age=7') If you provide a URL with both an encoded GET data and a data argument, the data argument will take precedence. If you set ``follow`` to ``True`` the client will follow any redirects and a ``redirect_chain`` attribute will be set in the response object containing tuples of the intermediate urls and status codes. If you had an url ``/redirect_me/`` that redirected to ``/next/``, that redirected to ``/final/``, this is what you'd see:: >>> response = c.get('/redirect_me/', follow=True) >>> response.redirect_chain [(u'http://testserver/next/', 302), (u'http://testserver/final/', 302)] .. method:: Client.post(path, data={}, content_type=MULTIPART_CONTENT, follow=False, **extra) Makes a POST request on the provided ``path`` and returns a ``Response`` object, which is documented below. The key-value pairs in the ``data`` dictionary are used to submit POST data. For example:: >>> c = Client() >>> c.post('/login/', {'name': 'fred', 'passwd': 'secret'}) ...will result in the evaluation of a POST request to this URL:: /login/ ...with this POST data:: name=fred&passwd=secret If you provide ``content_type`` (e.g., ``text/xml`` for an XML payload), the contents of ``data`` will be sent as-is in the POST request, using ``content_type`` in the HTTP ``Content-Type`` header. If you don't provide a value for ``content_type``, the values in ``data`` will be transmitted with a content type of ``multipart/form-data``. In this case, the key-value pairs in ``data`` will be encoded as a multipart message and used to create the POST data payload. To submit multiple values for a given key -- for example, to specify the selections for a ``