PythontestPython回归测试包
注解
test
包只供 Python 内部使用。它的记录是为了让 Python 的核心开发者受益。我们不鼓励在 Python 标准库之外使用这个包,因为这里提到的代码在 Python 的不同版本之间可能会改变或被删除而不另行通知。
test
包包含了 Python 的所有回归测试,以及 test.support
和 test.regrtest
模块。 test.support
用于增强你的测试,而 test.regrtest
驱动测试套件。
test`包中每个名字以``test_`
开头的模块都是一个特定模块或功能的测试套件。所有新的测试应该使用 unittest
或 doctest
模块编写。一些旧的测试是使用“传统”的测试风格编写的,即比较打印出来的输出到``sys.stdout``;这种测试风格被认为是过时的。
参见
- 模块
unittest
编写 PyUnit 回归测试.
doctest
--- 文档测试模块Tests embedded in documentation strings.
Writing Unit Tests for the test
package¶
It is preferred that tests that use the unittest
module follow a few
guidelines. One is to name the test module by starting it with test_
and end
it with the name of the module being tested. The test methods in the test module
should start with test_
and end with a description of what the method is
testing. This is needed so that the methods are recognized by the test driver as
test methods. Also, no documentation string for the method should be included. A
comment (such as #TestsfunctionreturnsonlyTrueorFalse
) should be used
to provide documentation for test methods. This is done because documentation
strings get printed out if they exist and thus what test is being run is not
stated.
A basic boilerplate is often used:
importunittestfromtestimportsupport
classMyTestCase1(unittest.TestCase):
# Only use setUp() and tearDown() if necessary
defsetUp(self):
...codetoexecuteinpreparationfortests...
deftearDown(self):
...codetoexecutetocleanupaftertests...
deftest_feature_one(self):
# Test feature one.
...testingcode...
deftest_feature_two(self):
# Test feature two.
...testingcode...
...moretestmethods...
classMyTestCase2(unittest.TestCase):
...samestructureasMyTestCase1...
...moretestclasses...
if__name__=='__main__':
unittest.main()
This code pattern allows the testing suite to be run by test.regrtest
,
on its own as a script that supports the unittest
CLI, or via the
python-munittest
CLI.
The goal for regression testing is to try to break code. This leads to a few
guidelines to be followed:
The testing suite should exercise all classes, functions, and constants. This
includes not just the external API that is to be presented to the outside
world but also "private" code.
Whitebox testing (examining the code being tested when the tests are being
written) is preferred. Blackbox testing (testing only the published user
interface) is not complete enough to make sure all boundary and edge cases
are tested.
Make sure all possible values are tested including invalid ones. This makes
sure that not only all valid values are acceptable but also that improper
values are handled correctly.
Exhaust as many code paths as possible. Test where branching occurs and thus
tailor input to make sure as many different paths through the code are taken.
Add an explicit test for any bugs discovered for the tested code. This will
make sure that the error does not crop up again if the code is changed in the
future.
Make sure to clean up after your tests (such as close and remove all temporary
files).
If a test is dependent on a specific condition of the operating system then
verify the condition already exists before attempting the test.
Import as few modules as possible and do it as soon as possible. This
minimizes external dependencies of tests and also minimizes possible anomalous
behavior from side-effects of importing a module.
Try to maximize code reuse. On occasion, tests will vary by something as small
as what type of input is used. Minimize code duplication by subclassing a
basic test class with a class that specifies the input:
python3 notranslate">classTestFuncAcceptsSequencesMixin:
func=mySuperWhammyFunction
deftest_func(self):
self.func(self.arg)
classAcceptLists(TestFuncAcceptsSequencesMixin,unittest.TestCase):
arg=[1,2,3]
classAcceptStrings(TestFuncAcceptsSequencesMixin,unittest.TestCase):
arg='abc'
classAcceptTuples(TestFuncAcceptsSequencesMixin,unittest.TestCase):
arg=(1,2,3)
When using this pattern, remember that all classes that inherit from
unittest.TestCase
are run as tests. TheMixin
class in the example abovedoes not have any data and so can't be run by itself, thus it does not
inherit from
unittest.TestCase
.
参见
- Test Driven Development
A book by Kent Beck on writing tests before code.
Running tests using the command-line interface¶
The test
package can be run as a script to drive Python's regression
test suite, thanks to the -m
option: python -m test. Under
the hood, it uses test.regrtest
; the call python -m
test.regrtest used in previous Python versions still works. Running the
script by itself automatically starts running all regression tests in the
test
package. It does this by finding all modules in the package whose
name starts with test_
, importing them, and executing the function
test_main()
if present or loading the tests via
unittest.TestLoader.loadTestsFromModule if test_main
does not exist. The
names of tests to execute may also be passed to the script. Specifying a single
regression test (python -m test test_spam) will minimize output and
only print whether the test passed or failed.
Running test
directly allows what resources are available for
tests to use to be set. You do this by using the -u
command-line
option. Specifying all
as the value for the -u
option enables all
possible resources: python -m test -uall.
If all but one resource is desired (a more common case), a
comma-separated list of resources that are not desired may be listed after
all
. The command python -m test -uall,-audio,-largefile
will run test
with all resources except the audio
and
largefile
resources. For a list of all resources and more command-line
options, run python -m test -h.
Some other ways to execute the regression tests depend on what platform the
tests are being executed on. On Unix, you can run make test at the
top-level directory where Python was built. On Windows,
executing rt.bat from your PCbuild
directory will run all
regression tests.