使用装饰器动态添加测试方法 [英] Adding test methods dynamically using decorator

问题描述

我一直在使用 DDT 对我的测试进行参数设置，取得了巨大的成功过去的几个月。现在的问题是我似乎无法注入列表变量作为数据源。这样做似乎会使DDT混淆，导致DDT无法参数化我的测试。我开始创建自己的解决方案，但似乎无法弄清楚最后一部分。

I've been using DDT to parameterize my tests with great success for the past few months. My issue now is that I can't seem to inject a list variable as my data source. Doing so seems to confuse DDT causing it to not parameterize my tests. I started to create my own solution, but I can't seem to figure this last part out.

到目前为止，这是我作为装饰者所拥有的-

Here is what I have thus far as decorators -

def data(*values):
    def aaa(func):
        def wrapper(self, *args, **kwargs):
            pass
#             return func(self, *args, **kwargs)
        wrapper.func_name = func.__name__ + 't'
        wrapper.values = values
        return wrapper
    return aaa


def c(cls):
    for name, method in list(cls.__dict__.items()):
        if hasattr(method, 'values'):
            for ticket in method.values[0]:
                test_name = mk_test_name(method.func_name, ticket)
                print(test_name)
                setattr(cls, test_name, method(cls, ticket))
    return cls

然后我就这样使用它-

@c
class IntegrationTests(APITestCase):
    tickets = [1, 2, 3, 4]

    @data(tickets)
    def tes(self, t):
        print(t)

如何使Python测试框架能够识别通过装饰器添加的内容？我知道已经添加了这些方法，因为在PDB中发出 dir 命令会显示它们。这样做的目的是，我将为列表中的每个项目重复装饰的测试。对于那些想知道为什么 wrapper（）没有代码的人，我这样做是因为取消注释该行的return调用会导致我装饰的方法在没有参数的情况下执行，从而导致错误。

How can I make the Python testing framework recognize that I've added via decorator? I know the methods have been added because issuing the dir command in PDB displays them. The goal for this is that I would duplicate the test(s) I decorate for each item in a list. For those wondering why wrapper() has no code, I did this because uncommenting the line the return call causes the method I decorate to be executed without parameters, thus causing an error.

在我的示例中，我希望执行4个名称不同的测试。

In my example, I would expect 4 tests with different names to be executed.

推荐答案

最好的解决方案是在python 3.4中使用unittest的子测试功能。在此处找到的文档，其使用方式如下：

The best solution is to use the sub tests feature of unittest in python 3.4. Documentation found here and used like:

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)

使用python 3.4，以下是一个穷人的替代品。

For those who cannot use python 3.4, the following is a poor man's replacement.

class sub_test_data(object):

    def __init__(self, *test_data):
        self.test_data = test_data

    def __call__(self, func):
        func.sub_test_data = self.test_data
        func.has_sub_tests = True
        return func

def create_test_driver(func, *args):
    def test_driver(self):
        try:
            func(self, *args)
        except AssertionError as e:
            e.args += ({"test_args": args},)
            raise
    return test_driver  

def create_sub_tests(cls):
    for attr_name, func in list(vars(cls).items()):
        if getattr(func, "has_sub_tests", False):
            for i, value in enumerate(func.sub_test_data):
                test_name = 'test_{}_subtest{}'.format(attr_name, i)
                setattr(cls, test_name, create_test_driver(func, value))
    return cls

@create_sub_tests
class NumbersTest(unittest.TestCase):
    tickets = [0, 1, 2, 3, 4, 5]

    @sub_test_data(*tickets)
    def even(self, t):
        self.assertEqual(t % 2, 0)

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