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
从Python 3.4开始，已经为此目的向unittest引入了子测试。详细信息请参见文档。TestCase。subTest是一个上下文管理器，它允许在测试中隔离断言，以便用参数信息报告失败，但它不会停止测试执行。下面是文档中的例子:
class NumbersTest(unittest.TestCase):
def test_even(self):
"""
Test that numbers between 0 and 5 are all even.
"""
for i in range(0, 6):
with self.subTest(i=i):
self.assertEqual(i % 2, 0)
测试运行的输出是:
======================================================================
FAIL: test_even (__main__.NumbersTest) (i=1)
----------------------------------------------------------------------
Traceback (most recent call last):
File "subtests.py", line 32, in test_even
self.assertEqual(i % 2, 0)
AssertionError: 1 != 0
======================================================================
FAIL: test_even (__main__.NumbersTest) (i=3)
----------------------------------------------------------------------
Traceback (most recent call last):
File "subtests.py", line 32, in test_even
self.assertEqual(i % 2, 0)
AssertionError: 1 != 0
======================================================================
FAIL: test_even (__main__.NumbersTest) (i=5)
----------------------------------------------------------------------
Traceback (most recent call last):
File "subtests.py", line 32, in test_even
self.assertEqual(i % 2, 0)
AssertionError: 1 != 0
这也是unittest2的一部分，因此可用于早期版本的Python。
其他回答
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
我有麻烦使这些工作为setUpClass。
下面是Javier回答的一个版本，它允许setUpClass访问动态分配的属性。
import unittest
class GeneralTestCase(unittest.TestCase):
@classmethod
def setUpClass(cls):
print ''
print cls.p1
print cls.p2
def runTest1(self):
self.assertTrue((self.p2 - self.p1) == 1)
def runTest2(self):
self.assertFalse((self.p2 - self.p1) == 2)
def load_tests(loader, tests, pattern):
test_cases = unittest.TestSuite()
for p1, p2 in [(1, 2), (3, 4)]:
clsname = 'TestCase_{}_{}'.format(p1, p2)
dct = {
'p1': p1,
'p2': p2,
}
cls = type(clsname, (GeneralTestCase,), dct)
test_cases.addTest(cls('runTest1'))
test_cases.addTest(cls('runTest2'))
return test_cases
输出
1
2
..
3
4
..
----------------------------------------------------------------------
Ran 4 tests in 0.000s
OK
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。
使用ddt库。它为测试方法添加了简单的装饰器:
import unittest
from ddt import ddt, data
from mycode import larger_than_two
@ddt
class FooTestCase(unittest.TestCase):
@data(3, 4, 12, 23)
def test_larger_than_two(self, value):
self.assertTrue(larger_than_two(value))
@data(1, -3, 2, 0)
def test_not_larger_than_two(self, value):
self.assertFalse(larger_than_two(value))
这个库可以用pip安装。它不需要nose，并且与标准库unittest模块一起出色地工作。
我使用元类和装饰器来生成测试。您可以检查我的实现python_wrap_cases。这个库不需要任何测试框架。
你的例子:
import unittest
from python_wrap_cases import wrap_case
@wrap_case
class TestSequence(unittest.TestCase):
@wrap_case("foo", "a", "a")
@wrap_case("bar", "a", "b")
@wrap_case("lee", "b", "b")
def testsample(self, name, a, b):
print "test", name
self.assertEqual(a, b)
控制台输出:
testsample_u'bar'_u'a'_u'b' (tests.example.test_stackoverflow.TestSequence) ... test bar
FAIL
testsample_u'foo'_u'a'_u'a' (tests.example.test_stackoverflow.TestSequence) ... test foo
ok
testsample_u'lee'_u'b'_u'b' (tests.example.test_stackoverflow.TestSequence) ... test lee
ok
你也可以使用发电机。例如，这段代码用参数a__list和b__list生成所有可能的测试组合
import unittest
from python_wrap_cases import wrap_case
@wrap_case
class TestSequence(unittest.TestCase):
@wrap_case(a__list=["a", "b"], b__list=["a", "b"])
def testsample(self, a, b):
self.assertEqual(a, b)
控制台输出:
testsample_a(u'a')_b(u'a') (tests.example.test_stackoverflow.TestSequence) ... ok
testsample_a(u'a')_b(u'b') (tests.example.test_stackoverflow.TestSequence) ... FAIL
testsample_a(u'b')_b(u'a') (tests.example.test_stackoverflow.TestSequence) ... FAIL
testsample_a(u'b')_b(u'b') (tests.example.test_stackoverflow.TestSequence) ... ok
