我有一些测试数据，想为每个项目创建一个单元测试。我的第一个想法是这样做的:
import unittest
l = [["foo", "a", "a",], ["bar", "a", "b"], ["lee", "b", "b"]]
class TestSequence(unittest.TestCase):
def testsample(self):
for name, a,b in l:
print "test", name
self.assertEqual(a,b)
if __name__ == '__main__':
unittest.main()
这样做的缺点是它在一个测试中处理所有数据。我想在飞行中为每个项目生成一个测试。有什么建议吗?
当前回答
您将从尝试testscenario库中受益。
testscenes为python unittest风格的测试提供了干净的依赖注入。这可以用于接口测试(通过单个测试套件测试许多实现)或经典的依赖项注入(在测试代码本身的外部提供依赖项测试，允许在不同情况下轻松测试)。
其他回答
这被称为“参数化”。
有几个工具支持这种方法。例如:
pytest的装饰 参数化
结果代码如下所示:
from parameterized import parameterized
class TestSequence(unittest.TestCase):
@parameterized.expand([
["foo", "a", "a",],
["bar", "a", "b"],
["lee", "b", "b"],
])
def test_sequence(self, name, a, b):
self.assertEqual(a,b)
这将生成测试:
test_sequence_0_foo (__main__.TestSequence) ... ok
test_sequence_1_bar (__main__.TestSequence) ... FAIL
test_sequence_2_lee (__main__.TestSequence) ... ok
======================================================================
FAIL: test_sequence_1_bar (__main__.TestSequence)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/local/lib/python2.7/site-packages/parameterized/parameterized.py", line 233, in <lambda>
standalone_func = lambda *a: func(*(a + p.args), **p.kwargs)
File "x.py", line 12, in test_sequence
self.assertEqual(a,b)
AssertionError: 'a' != 'b'
由于历史原因，我将保留大约2008年的原始答案):
我使用的方法是这样的:
import unittest
l = [["foo", "a", "a",], ["bar", "a", "b"], ["lee", "b", "b"]]
class TestSequense(unittest.TestCase):
pass
def test_generator(a, b):
def test(self):
self.assertEqual(a,b)
return test
if __name__ == '__main__':
for t in l:
test_name = 'test_%s' % t[0]
test = test_generator(t[1], t[2])
setattr(TestSequense, test_name, test)
unittest.main()
以下是我的解决方案。我发现这个方法很有用:
Should work for unittest.Testcase and unittest discover Have a set of tests to be run for different parameter settings. Very simple and no dependency on other packages import unittest class BaseClass(unittest.TestCase): def setUp(self): self.param = 2 self.base = 2 def test_me(self): self.assertGreaterEqual(5, self.param+self.base) def test_me_too(self): self.assertLessEqual(3, self.param+self.base) class Child_One(BaseClass): def setUp(self): BaseClass.setUp(self) self.param = 4 class Child_Two(BaseClass): def setUp(self): BaseClass.setUp(self) self.param = 1
除了使用setattr，我们还可以在Python 3.2及更高版本中使用load_tests。
class Test(unittest.TestCase):
pass
def _test(self, file_name):
open(file_name, 'r') as f:
self.assertEqual('test result',f.read())
def _generate_test(file_name):
def test(self):
_test(self, file_name)
return test
def _generate_tests():
for file in files:
file_name = os.path.splitext(os.path.basename(file))[0]
setattr(Test, 'test_%s' % file_name, _generate_test(file))
test_cases = (Test,)
def load_tests(loader, tests, pattern):
_generate_tests()
suite = TestSuite()
for test_class in test_cases:
tests = loader.loadTestsFromTestCase(test_class)
suite.addTests(tests)
return suite
if __name__ == '__main__':
_generate_tests()
unittest.main()
您将从尝试testscenario库中受益。
testscenes为python unittest风格的测试提供了干净的依赖注入。这可以用于接口测试(通过单个测试套件测试许多实现)或经典的依赖项注入(在测试代码本身的外部提供依赖项测试，允许在不同情况下轻松测试)。
只使用元类，如这里所示;
class DocTestMeta(type):
"""
Test functions are generated in metaclass due to the way some
test loaders work. For example, setupClass() won't get called
unless there are other existing test methods, and will also
prevent unit test loader logic being called before the test
methods have been defined.
"""
def __init__(self, name, bases, attrs):
super(DocTestMeta, self).__init__(name, bases, attrs)
def __new__(cls, name, bases, attrs):
def func(self):
"""Inner test method goes here"""
self.assertTrue(1)
func.__name__ = 'test_sample'
attrs[func.__name__] = func
return super(DocTestMeta, cls).__new__(cls, name, bases, attrs)
class ExampleTestCase(TestCase):
"""Our example test case, with no methods defined"""
__metaclass__ = DocTestMeta
输出:
test_sample (ExampleTestCase) ... OK
