.. _topics-testing: =========================== Testing Django applications =========================== .. module:: django.test :synopsis: Testing tools for Django applications. Automated testing is an extremely useful bug-killing tool for the modern Web developer. You can use a collection of tests -- a **test suite** -- to solve, or avoid, a number of problems: * When you're writing new code, you can use tests to validate your code works as expected. * When you're refactoring or modifying old code, you can use tests to ensure your changes haven't affected your application's behavior unexpectedly. Testing a Web application is a complex task, because a Web application is made of several layers of logic -- from HTTP-level request handling, to form validation and processing, to template rendering. With Django's test-execution framework and assorted utilities, you can simulate requests, insert test data, inspect your application's output and generally verify your code is doing what it should be doing. The best part is, it's really easy. This document is split into two primary sections. First, we explain how to write tests with Django. Then, we explain how to run them. Writing tests ============= There are two primary ways to write tests with Django, corresponding to the two test frameworks that ship in the Python standard library. The two frameworks are: * **Doctests** -- tests that are embedded in your functions' docstrings and are written in a way that emulates a session of the Python interactive interpreter. For example:: def my_func(a_list, idx): """ >>> a = ['larry', 'curly', 'moe'] >>> my_func(a, 0) 'larry' >>> my_func(a, 1) 'curly' """ return a_list[idx] * **Unit tests** -- tests that are expressed as methods on a Python class that subclasses ``unittest.TestCase``. For example:: import unittest class MyFuncTestCase(unittest.TestCase): def testBasic(self): a = ['larry', 'curly', 'moe'] self.assertEquals(my_func(a, 0), 'larry') self.assertEquals(my_func(a, 1), 'curly') You can choose the test framework you like, depending on which syntax you prefer, or you can mix and match, using one framework for some of your code and the other framework for other code. You can also use any *other* Python test frameworks, as we'll explain in a bit. Writing doctests ---------------- Doctests use Python's standard doctest_ module, which searches your docstrings for statements that resemble a session of the Python interactive interpreter. A full explanation of how doctest works is out of the scope of this document; read Python's official documentation for the details. .. admonition:: What's a **docstring**? A good explanation of docstrings (and some guidelines for using them effectively) can be found in :pep:`257`: A docstring is a string literal that occurs as the first statement in a module, function, class, or method definition. Such a docstring becomes the ``__doc__`` special attribute of that object. For example, this function has a docstring that describes what it does:: def add_two(num): "Return the result of adding two to the provided number." return num + 2 Because tests often make great documentation, putting tests directly in your docstrings is an effective way to document *and* test your code. For a given Django application, the test runner looks for doctests in two places: * The ``models.py`` file. You can define module-level doctests and/or a doctest for individual models. It's common practice to put application-level doctests in the module docstring and model-level doctests in the model docstrings. * A file called ``tests.py`` in the application directory -- i.e., the directory that holds ``models.py``. This file is a hook for any and all doctests you want to write that aren't necessarily related to models. Here is an example model doctest:: # models.py from django.db import models class Animal(models.Model): """ An animal that knows how to make noise # Create some animals >>> lion = Animal.objects.create(name="lion", sound="roar") >>> cat = Animal.objects.create(name="cat", sound="meow") # Make 'em speak >>> lion.speak() 'The lion says "roar"' >>> cat.speak() 'The cat says "meow"' """ name = models.CharField(max_length=20) sound = models.CharField(max_length=20) def speak(self): return 'The %s says "%s"' % (self.name, self.sound) When you :ref:`run your tests `, 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.) Note that to use this feature, the database user Django is connecting as must have ``CREATE DATABASE`` rights. For more details about how doctest works, see the `standard library documentation for doctest`_. .. _doctest: http://docs.python.org/lib/module-doctest.html .. _standard library documentation for doctest: doctest_ Writing unit tests ------------------ Like doctests, Django's unit tests use a standard library module: unittest_. This module uses a different way of defining tests, taking a class-based approach. As with doctests, for a given Django application, the test runner looks for unit tests in two places: * The ``models.py`` file. The test runner looks for any subclass of ``unittest.TestCase`` in this module. * A file called ``tests.py`` in the application directory -- i.e., the directory that holds ``models.py``. Again, the test runner looks for any subclass of ``unittest.TestCase`` in this module. This example ``unittest.TestCase`` subclass is equivalent to the example given in the doctest section above:: import unittest from myapp.models import Animal class AnimalTestCase(unittest.TestCase): def setUp(self): self.lion = Animal.objects.create(name="lion", sound="roar") self.cat = Animal.objects.create(name="cat", sound="meow") def testSpeaking(self): self.assertEquals(self.lion.speak(), 'The lion says "roar"') self.assertEquals(self.cat.speak(), 'The cat says "meow"') When you :ref:`run your tests `, 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. 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`_. .. _unittest: http://docs.python.org/lib/module-unittest.html .. _standard library unittest documentation: unittest_ .. _suggested organization: http://docs.python.org/lib/organizing-tests.html Which should I use? ------------------- Because Django supports both of the standard Python test frameworks, it's up to you and your tastes to decide which one to use. You can even decide to use *both*. For developers new to testing, however, this choice can seem confusing. Here, then, are a few key differences to help you decide which approach is right for you: * If you've been using Python for a while, ``doctest`` will probably feel more "pythonic". It's designed to make writing tests as easy as possible, so it requires no overhead of writing classes or methods. You simply put tests in docstrings. This has the added advantage of serving as documentation (and correct documentation, at that!). If you're just getting started with testing, using doctests will probably get you started faster. * The ``unittest`` framework will probably feel very familiar to developers coming from Java. ``unittest`` is inspired by Java's JUnit, so you'll feel at home with this method if you've used JUnit or any test framework inspired by JUnit. * If you need to write a bunch of tests that share similar code, then you'll appreciate the ``unittest`` framework's organization around classes and methods. This makes it easy to abstract common tasks into common methods. The framework also supports explicit setup and/or cleanup routines, which give you a high level of control over the environment in which your test cases are run. Again, remember that you can use both systems side-by-side (even in the same app). In the end, most projects will eventually end up using both. Each shines in different circumstances. .. _running-tests: Running tests ============= Once you've written tests, run them using your project's ``manage.py`` utility:: $ ./manage.py test By default, this will run every test in every application in :setting:`INSTALLED_APPS`. If you only want to run tests for a particular application, add the application name to the command line. For example, if your :setting:`INSTALLED_APPS` contains ``'myproject.polls'`` and ``'myproject.animals'``, you can run the ``myproject.animals`` unit tests alone with this command:: # ./manage.py test animals Note that we used ``animals``, not ``myproject.animals``. **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 The test database ----------------- Tests that require a database (namely, model tests) will not use your "real" (production) database. A separate, blank database is created for the tests. Regardless of whether the tests pass or fail, the test database is destroyed when all the tests have been executed. By default this test database gets its name by prepending ``test_`` to the value of the :setting:`DATABASE_NAME` setting. When using the SQLite database engine the tests will by default use an in-memory database (i.e., the database will be created in memory, bypassing the filesystem entirely!). If you want to use a different database name, specify the :setting:`TEST_DATABASE_NAME` setting. Aside from using a separate database, the test runner will otherwise use all of the same database settings you have in your settings file: :setting:`DATABASE_ENGINE`, :setting:`DATABASE_USER`, :setting:`DATABASE_HOST`, etc. The test database is created by the user specified by :setting:`DATABASE_USER`, so you'll need to make sure that the given user account has sufficient privileges to create a new database on the system. **New in Django development version:** For fine-grained control over the character encoding of your test database, use the :setting:`TEST_DATABASE_CHARSET` setting. If you're using MySQL, you can also use the :setting:`TEST_DATABASE_COLLATION` setting to control the particular collation used by the test database. See the :ref:`settings documentation ` for details of these advanced settings. Other test conditions --------------------- Regardless of the value of the :setting:`DEBUG` setting in your configuration file, all Django tests run with :setting:`DEBUG=False`. This is to ensure that the observed output of your code matches what will be seen in a production setting. Understanding the test output ----------------------------- When you run your tests, you'll see a number of messages as the test runner prepares itself. You can control the level of detail of these messages with the ``verbosity`` option on the command line:: Creating test database... Creating table myapp_animal Creating table myapp_mineral Loading 'initial_data' fixtures... No fixtures found. This tells you that the test runner is creating a test database, as described in the previous section. Once the test database has been created, Django will run your tests. If everything goes well, you'll see something like this:: ---------------------------------------------------------------------- Ran 22 tests in 0.221s OK If there are test failures, however, you'll see full details about which tests failed:: ====================================================================== FAIL: Doctest: ellington.core.throttle.models ---------------------------------------------------------------------- Traceback (most recent call last): File "/dev/django/test/doctest.py", line 2153, in runTest raise self.failureException(self.format_failure(new.getvalue())) AssertionError: Failed doctest test for myapp.models File "/dev/myapp/models.py", line 0, in models ---------------------------------------------------------------------- File "/dev/myapp/models.py", line 14, in myapp.models Failed example: throttle.check("actor A", "action one", limit=2, hours=1) Expected: True Got: False ---------------------------------------------------------------------- Ran 2 tests in 0.048s FAILED (failures=1) A full explanation of this error output is beyond the scope of this document, but it's pretty intuitive. You can consult the documentation of Python's ``unittest`` library for details. Note that the return code for the test-runner script is the total number of failed and erroneous tests. If all the tests pass, the return code is 0. This feature is useful if you're using the test-runner script in a shell script and need to test for success or failure at that level. Testing tools ============= Django provides a small set of tools that come in handy when writing tests. The test client --------------- .. module:: django.test.client :synopsis: Django's test client. The test client is a Python class that acts as a dummy Web browser, allowing you to test your views and interact with your Django-powered application programmatically. Some of the things you can do with the test client are: * Simulate GET and POST requests on a URL and observe the response -- everything from low-level HTTP (result headers and status codes) to page content. * Test that the correct view is executed for a given URL. * Test that a given request is rendered by a given Django template, with a template context that contains certain values. Note that the test client is not intended to be a replacement for Twill_, Selenium_, or other "in-browser" frameworks. Django's test client has a different focus. In short: * Use Django's test client to establish that the correct view is being called and that the view is collecting the correct context data. * Use in-browser frameworks such as Twill and Selenium to test *rendered* HTML and the *behavior* of Web pages, namely JavaScript functionality. A comprehensive test suite should use a combination of both test types. .. _Twill: http://twill.idyll.org/ .. _Selenium: http://www.openqa.org/selenium/ Overview and a quick example ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ To use the test client, instantiate ``django.test.client.Client`` and retrieve Web pages:: >>> from django.test.client import Client >>> c = Client() >>> response = c.post('/login/', {'username': 'john', 'password': 'smith'}) >>> response.status_code 200 >>> response = c.get('/customer/details/') >>> response.content '>> c.get('/login/') This is incorrect:: >>> c.get('http://www.example.com/login/') The test client is not capable of retrieving Web pages that are not powered by your Django project. If you need to retrieve other Web pages, use a Python standard library module such as urllib_ or urllib2_. * To resolve URLs, the test client uses whatever URLconf is pointed-to by your :setting:`ROOT_URLCONF` setting. * Although the above example would work in the Python interactive interpreter, some of the test client's functionality, notably the template-related functionality, is only available *while tests are running*. The reason for this is that Django's test runner performs a bit of black magic in order to determine which template was loaded by a given view. This black magic (essentially a patching of Django's template system in memory) only happens during test running. .. _urllib: http://docs.python.org/lib/module-urllib.html .. _urllib2: http://docs.python.org/lib/module-urllib2.html Making requests ~~~~~~~~~~~~~~~ Use the ``django.test.client.Client`` class to make requests. It requires no arguments at time of construction: .. class:: Client() Once you have a ``Client`` instance, you can call any of the following methods: .. method:: Client.get(path, data={}) 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 .. method:: Client.post(path, data={}, content_type=MULTIPART_CONTENT) 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 ``