Extensions to the Python standard library unit testing framework
testtools is a set of extensions to the Python standard library’s unit testing framework. These extensions have been derived from many years of experience with unit testing in Python and come from many different sources.
What better way to start than with a contrived code snippet?:
from testtools import TestCase from testtools.content import Content from testtools.content_type import UTF8_TEXT from testtools.matchers import Equals from myproject import SillySquareServer class TestSillySquareServer(TestCase): def setUp(self): super(TestSillySquareServer, self).setUp() self.server = self.useFixture(SillySquareServer()) self.addCleanup(self.attach_log_file) def attach_log_file(self): self.addDetail( 'log-file', Content(UTF8_TEXT, lambda: open(self.server.logfile, 'r').readlines())) def test_server_is_cool(self): self.assertThat(self.server.temperature, Equals("cool")) def test_square(self): self.assertThat(self.server.silly_square_of(7), Equals(49))
The standard assertion methods that come with unittest aren’t as helpful as they could be, and there aren’t quite enough of them. testtools adds assertIn, assertIs, assertIsInstance and their negatives.
Of course, in any serious project you want to be able to have assertions that are specific to that project and the particular problem that it is addressing. Rather than forcing you to define your own assertion methods and maintain your own inheritance hierarchy of TestCase classes, testtools lets you write your own “matchers”, custom predicates that can be plugged into a unit test:
def test_response_has_bold(self): # The response has bold text. response = self.server.getResponse() self.assertThat(response, HTMLContains(Tag('bold', 'b')))
testtools makes it easy to add arbitrary data to your test result. If you want to know what’s in a log file when a test fails, or what the load was on the computer when a test started, or what files were open, you can add that information with TestCase.addDetail, and it will appear in the test results if that test fails.
testtools goes to great lengths to allow serious test authors and test framework authors to do whatever they like with their tests and their extensions while staying compatible with the standard library’s unittest.
testtools has completely parametrized how exceptions raised in tests are mapped to TestResult methods and how tests are actually executed (ever wanted tearDown to be called regardless of whether setUp succeeds?)
It also provides many simple but handy utilities, like the ability to clone a test, a MultiTestResult object that lets many result objects get the results from one test suite, adapters to bring legacy TestResult objects into our new golden age.
testtools gives you the very latest in unit testing technology in a way that will work with Python 2.7, 3.3, 3.4, 3.5, and pypy.
If you wish to use testtools with Python 2.4 or 2.5, then please use testtools 0.9.15.
If you wish to use testtools with Python 2.6 or 3.2, then please use testtools 1.9.0.
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