Writing and running tests¶
This document is split into two primary sections. First, we explain how to write tests with Django. Then, we explain how to run them.
Django’s unit tests use a Python standard library module: unittest. This module defines tests using a class-based approach.
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 Python 2.7’s unittest, backported for Python 2.6 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 it. Otherwise, Django will use its own bundled version of unittest2.
To use this alias, simply use:
from django.utils import unittest
wherever you would have historically used:
If you want to continue to use the legacy unittest library, you can – you just won’t get any of the nice new unittest2 features.
from django.test import TestCase from myapp.models import Animal class AnimalTestCase(TestCase): def setUp(self): Animal.objects.create(name="lion", sound="roar") Animal.objects.create(name="cat", sound="meow") def test_animals_can_speak(self): """Animals that can speak are correctly identified""" lion = Animal.objects.get(name="lion") cat = Animal.objects.get(name="cat") self.assertEqual(lion.speak(), 'The lion says "roar"') self.assertEqual(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 any file whose name begins with test, automatically build a test suite out of those test cases, and run that suite.
Previously, Django’s default test runner only discovered tests in tests.py and models.py files within a Python package listed in INSTALLED_APPS.
For more details about unittest, see the Python documentation.
Using unittest.TestCase avoids the cost of running each test in a transaction and flushing the database, but if your tests interact with the database their behavior will vary based on the order that the test runner executes them. This can lead to unit tests that pass when run in isolation but fail when run in a suite.
Once you’ve written tests, run them using the test command of your project’s manage.py utility:
$ ./manage.py test
Test discovery is based on the unittest module’s built-in test discovery. By default, this will discover tests in any file named “test*.py” under the current working directory.
You can specify particular tests to run by supplying any number of “test labels” to ./manage.py test. Each test label can be a full Python dotted path to a package, module, TestCase subclass, or test method. For instance:
# Run all the tests in the animals.tests module $ ./manage.py test animals.tests # Run all the tests found within the 'animals' package $ ./manage.py test animals # Run just one test case $ ./manage.py test animals.tests.AnimalTestCase # Run just one test method $ ./manage.py test animals.tests.AnimalTestCase.test_animals_can_speak
You can also provide a path to a directory to discover tests below that directory:
$ ./manage.py test animals/
You can specify a custom filename pattern match using the -p (or --pattern) option, if your test files are named differently from the test*.py pattern:
$ ./manage.py test --pattern="tests_*.py"
Previously, test labels were in the form applabel, applabel.TestCase, or applabel.TestCase.test_method, rather than being true Python dotted paths, and tests could only be found within tests.py or models.py files within a Python package listed in INSTALLED_APPS. The --pattern option and file paths as test labels are new in 1.6.
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.
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.
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 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.
Finding data from your production database when running tests?
If your code attempts to access the database when its modules are compiled, this will occur before the test database is set up, with potentially unexpected results. For example, if you have a database query in module-level code and a real database exists, production data could pollute your tests. It is a bad idea to have such import-time database queries in your code anyway - rewrite your code so that it doesn’t do this.
Order in which tests are executed¶
In order to guarantee that all TestCase code starts with a clean database, the Django test runner reorders tests in the following way:
- All TestCase subclasses are run first.
- Then, all other unittests (including unittest.TestCase, SimpleTestCase and TransactionTestCase) are run with no particular ordering guaranteed nor enforced among them.
- Then any other tests (e.g. doctests) that may alter the database without restoring it to its original state are run.
Before Django 1.5, the only guarantee was that TestCase tests were always ran first, before any other tests.
The new ordering of tests may reveal unexpected dependencies on test case ordering. This is the case with doctests that relied on state left in the database by a given TransactionTestCase test, they must be updated to be able to run independently.
Other test conditions¶
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.
Caches are not cleared after each test, and running “manage.py test fooapp” can insert data from the tests into the cache of a live system if you run your tests in production because, unlike databases, a separate “test cache” is not used. This behavior may change in the future.
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: test_was_published_recently_with_future_poll (polls.tests.PollMethodTests) ---------------------------------------------------------------------- Traceback (most recent call last): File "/dev/mysite/polls/tests.py", line 16, in test_was_published_recently_with_future_poll self.assertEqual(future_poll.was_published_recently(), False) AssertionError: True != False ---------------------------------------------------------------------- Ran 1 test in 0.003s 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 1 for any 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.
Speeding up the tests¶
In recent versions of Django, the default password hasher is rather slow by design. If during your tests you are authenticating many users, you may want to use a custom settings file and set the PASSWORD_HASHERS setting to a faster hashing algorithm:
PASSWORD_HASHERS = ( 'django.contrib.auth.hashers.MD5PasswordHasher', )
Don’t forget to also include in PASSWORD_HASHERS any hashing algorithm used in fixtures, if any.