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))
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 3.7+ and PyPy3.
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.
If you wish to use testtools with Python 3.3 or 3.4, then please use testtools 2.3.0.
If you wish to use testtools with Python 2.7 or 3.5, then please use testtools 2.4.0.