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。

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()

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()

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。

我在一种非常特殊的参数化测试风格上遇到了麻烦。我们所有的Selenium测试都可以在本地运行，但它们也应该能够在SauceLabs上的多个平台上远程运行。基本上，我想要使用大量已经编写好的测试用例，并用尽可能少的代码更改参数化它们。此外，我需要能够将参数传递到setUp方法中，这是我在其他地方没有看到的任何解决方案。

以下是我想到的:

import inspect
import types

test_platforms = [
    {'browserName': "internet explorer", 'platform': "Windows 7", 'version': "10.0"},
    {'browserName': "internet explorer", 'platform': "Windows 7", 'version': "11.0"},
    {'browserName': "firefox", 'platform': "Linux", 'version': "43.0"},
]


def sauce_labs():
    def wrapper(cls):
        return test_on_platforms(cls)
    return wrapper


def test_on_platforms(base_class):
    for name, function in inspect.getmembers(base_class, inspect.isfunction):
        if name.startswith('test_'):
            for platform in test_platforms:
                new_name = '_'.join(list([name, ''.join(platform['browserName'].title().split()), platform['version']]))
                new_function = types.FunctionType(function.__code__, function.__globals__, new_name,
                                                  function.__defaults__, function.__closure__)
                setattr(new_function, 'platform', platform)
                setattr(base_class, new_name, new_function)
            delattr(base_class, name)

    return base_class

With this, all I had to do was add a simple decorator @sauce_labs() to each regular old TestCase, and now when running them, they're wrapped up and rewritten, so that all the test methods are parameterized and renamed. LoginTests.test_login(self) runs as LoginTests.test_login_internet_explorer_10.0(self), LoginTests.test_login_internet_explorer_11.0(self), and LoginTests.test_login_firefox_43.0(self), and each one has the parameter self.platform to decide what browser/platform to run against, even in LoginTests.setUp, which is crucial for my task since that's where the connection to SauceLabs is initialized.

无论如何，我希望这对那些希望对他们的测试进行类似的“全局”参数化的人有所帮助!

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