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
我发现这很适合我的目的，特别是当我需要生成在数据集合上执行稍微不同的过程的测试时。
import unittest
def rename(newName):
def renamingFunc(func):
func.__name__ == newName
return func
return renamingFunc
class TestGenerator(unittest.TestCase):
TEST_DATA = {}
@classmethod
def generateTests(cls):
for dataName, dataValue in TestGenerator.TEST_DATA:
for func in cls.getTests(dataName, dataValue):
setattr(cls, "test_{:s}_{:s}".format(func.__name__, dataName), func)
@classmethod
def getTests(cls):
raise(NotImplementedError("This must be implemented"))
class TestCluster(TestGenerator):
TEST_CASES = []
@staticmethod
def getTests(dataName, dataValue):
def makeTest(case):
@rename("{:s}".format(case["name"]))
def test(self):
# Do things with self, case, data
pass
return test
return [makeTest(c) for c in TestCluster.TEST_CASES]
TestCluster.generateTests()
TestGenerator类可以用来生成不同的测试用例集，比如TestCluster。
TestCluster可以被认为是TestGenerator接口的实现。
其他回答
import unittest
def generator(test_class, a, b,c,d,name):
def test(self):
print('Testexecution=',name)
print('a=',a)
print('b=',b)
print('c=',c)
print('d=',d)
return test
def add_test_methods(test_class):
test_list = [[3,3,5,6, 'one'], [5,5,8,9, 'two'], [0,0,5,6, 'three'],[0,0,2,3,'Four']]
for case in test_list:
print('case=',case[0], case[1],case[2],case[3],case[4])
test = generator(test_class, case[0], case[1],case[2],case[3],case[4])
setattr(test_class, "test_%s" % case[4], test)
class TestAuto(unittest.TestCase):
def setUp(self):
print ('Setup')
pass
def tearDown(self):
print ('TearDown')
pass
add_test_methods(TestAuto)
if __name__ == '__main__':
unittest.main(verbosity=1)
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()
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)。
基于元类的答案在Python 3中仍然有效，但必须使用元类参数，而不是__metaclass__属性，例如:
class ExampleTestCase(TestCase,metaclass=DocTestMeta):
pass
这个解决方案适用于Python 2和Python 3的unittest和nose:
#!/usr/bin/env python
import unittest
def make_function(description, a, b):
def ghost(self):
self.assertEqual(a, b, description)
print(description)
ghost.__name__ = 'test_{0}'.format(description)
return ghost
class TestsContainer(unittest.TestCase):
pass
testsmap = {
'foo': [1, 1],
'bar': [1, 2],
'baz': [5, 5]}
def generator():
for name, params in testsmap.iteritems():
test_func = make_function(name, params[0], params[1])
setattr(TestsContainer, 'test_{0}'.format(name), test_func)
generator()
if __name__ == '__main__':
unittest.main()
