Just the tests and documentation for now. Leaves any code accommodations in place.
3.7 KiB
testtools: tasteful testing for Python
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))
Why use testtools?
Better assertion methods
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.
Matchers: better than assertion methods
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')))
More debugging info, when you need it
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.
Extend unittest, but stay compatible and re-usable
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.
Cross-Python compatibility
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.