4

test_update_with_only_1_field基本上，我意识到我正在为多个模型的相似 URL编写相同的测试用例 ( )

from django.test import RequestFactory, TestCase
class BaseApiTest(TestCase):
def setUp(self):
    superuser = User.objects.create_superuser('test', 'test@api.com', 'testpassword')
    self.factory = RequestFactory()
    self.user = superuser
    self.client.login(username=superuser.username, password='testpassword')

class SomeModelApiTests(base_tests.BaseApiTest):
def test_update_with_only_1_field(self):
    """
    Tests for update only 1 field 

    GIVEN the following shape and related are valid
    WHEN we update only with just 1 field
    THEN we expect the update to be successful
    """
    shape_data = {
        'name': 'test shape',
        'name_en': 'test shape en',
        'name_zh_hans': 'test shape zh hans',
        'serial_number': 'test shape serial number',
        'model_name': {
            'some_field': '123'
        }
    }

    data = json.dumps(shape_data)
    response = self.client.post(reverse('shape-list-create'), data, 'application/json')
    self.assertEqual(response.status_code, status.HTTP_201_CREATED)

    some_model = response.data['some_model']
    new_some_field = '12345'

    data = json.dumps({'some_field': new_some_field, 'id': response.data['some_model']['id']})
    response = self.client.put(reverse('some-model', args=[some_model['id']]), data, 'application/json')
    self.assertEqual(response.status_code, status.HTTP_200_OK)
    self.assertEqual(new_some_field, response.data['some_field'])

我需要这样做超过 10 次。我已经这样做了。

每次唯一的区别是以下短语“some_model”、“some-model”和“some_field”

我想知道是否有更快的方法来做到这一点。

我可以抽象地思考两种方式：

  1. 在文本编辑器中创建一个模板，该模板可以生成最终的测试用例，然后我将其复制并粘贴。我正在使用 sublime text 3 虽然我可以切换到另一个文本编辑器

  2. 有一种方法可以让我编写更多代码，将这个测试用例转换为单个测试类可以调用的行为类。又名作曲。

哪个更有意义，或者有不同的方法可以做到这一点？

请注意，BaseApi 类也被其他没有该重复测试用例方法的测试类继承。

4

4 回答 4

5

我猜你想要的是“参数化测试”，标准可以用参数化包unittest做到这一点：

import unittest
from parameterized import parameterized

class SomeModelApiTests(unittest.TestCase):

    @parameterized.expand([
        ('case1', 'm1', 'f1', 'nf1'),
        ('case1', 'm2', 'f2', 'nf2'),
    ])
    def test_update_with_only_1_field(self, dummy_subtest_name, model_name, field_name, new_field_value):
        print(model_name, field_name, new_field_value)

将产生：

test_update_with_only_1_field_0_case1 (t.SomeModelApiTests) ... m1 f1 nf1
ok
test_update_with_only_1_field_1_case1 (t.SomeModelApiTests) ... m2 f2 nf2
ok

pytest测试框架对参数化测试有更好的支持，值得一看。

于 2017-11-13T17:31:16.727 回答
2

subtest您可以创建一个“ some_model”列表/字典进行测试，并为您的每个“ some_model”项目。

my_list_of_model = [FirstModel, SecondModel]

for my_model in my_list_of_model:
    with subTest(model=mymodel):
        # Testing model here

如果您希望TestCase每个模型都不同，我认为多重继承是要走的路：

class BaseApiTestCase(TestCase):
    def setUp():
        # Setup stuff

class RepetitiveTestCaseMixin:
    # Class to do the repetitive stuff
    def test_update_should_work(self):
        # Do some thing with self.model and self.field here

class ModelTestCase(BaseApiTestCase, RepetitiveTestCaseMixin):
    @classmethod
    def setUpClass(cls):
       super().setUpClass()

       cls.model = MyModel
       cls.field = 'some_field'
于 2017-11-13T12:40:36.760 回答
2

当需要重复测试时，我从事的项目有时会使用 mixin +“自定义挂钩”。（并且像“shape-list-create”这样的端点可能会发生变化/重构）

问题示例：

class TestUpdateWithOnly1FieldMixin(object):
    some_model = None
    some_field = None
    some_model2 = None

    def get_some_model(self):
        return self.some_model

    def get_some_field(self):
        return self.some_field

    def get_some_model2(self):
        return self.some_model2

    def test_update_with_only_1_field(self):
        some_model = self.get_some_model()
        # represents some-model in example
        some_model2 = self.get_some_model2()
        some_field = self.get_some_field()

        shape_data = {
            'name': 'test shape',
            'name_en': 'test shape en',
            'name_zh_hans': 'test shape zh hans',
            'serial_number': 'test shape serial number',
            'model_name': {
                some_field: '123'
            }
        }

      data = json.dumps(shape_data)
      response = self.client.post(reverse('shape-list-create'), data, 'application/json')
      self.assertEqual(response.status_code, status.HTTP_201_CREATED)

      some_model_data = response.data[some_model]



class SomeModelApiTests(base_tests.BaseApiTest, TestUpdateWithOnly1FieldMixin):
    some_model = 'choose your model'
    some_field = 'some_field'
    some_model2 = 'some-model'

    def get_some_field(self):
        # Do customization
        return 'some-field after customize'

如何拆分自定义钩子以及在mixin中放入什么等是根据情况而定的。在我看来，目标是让实际的测试用例易于理解。（也许将“post shape-list-create”移动到一个单独的函数中，因为它可能与该测试用例并不相关）

另一个例子，在自定义方面有点过火，但只是为了给出一个想法。

class TestWithGoodNameMixin(object):
    some_model = None
    some_field = None

    # "Customization hooks"

    def get_shape_data(self):
        return {self.some_field: 'x'}

    def create_model(self, shape_data):
        response = self.client.post(reverse('shape-list-create'), shape_data,
                                    'application/json')
        self.assertEqual(response.status_code, status.HTTP_201_CREATED)
        return response[self.some_model]

    def create_put_data(self, some_model_data):
        # Add default implementation
        pass

    # .....

    def test_update_with_only_1_field(self):
        shape_data = self.get_shape_data()
        some_model_data = self.create_model(shape_data)

        data = self.create_put_data(some_model_data)
        response = self.put_data(data)

        self.assert_put_response(response)
于 2017-11-14T05:42:13.203 回答
0

您可以使用pytest包进行单元测试。它非常简单易用。

@pytest.mark.parametrize()装饰器可用于实现该功能。

参数化测试用例的示例如下：

import pytest
class SampleTesting(object):
    data_for_test = [
                      ('{inputdata1:value1}','output1'),
                      ('{inputdata1:value2}','output2')
                     ]
   @pytest.mark.parametrized('input_data, expected_output', data_for_test)
   def test_sample_function(self, input_data, expected_output):
       response = function_to_be_tested(input_data)
       assert response == expected_output

您可以在docs中阅读有关此装饰器的更多信息

您还可以使用@pytest.fixture()装饰器来设置测试功能。

于 2017-11-16T21:13:58.067 回答