IUNIT TESTING PYTHON PATCH
IUNIT TESTING PYTHON PORTABLE
IUNIT TESTING PYTHON SOFTWARE
IUNIT TESTING PYTHON CODE

Note that patch is still useful, for example, to patch calls to time.time() or other side-effect-free library calls.Дependency injection is useful, but what should we do when our class needs a large number of clients? We can add more parameters and inject them all separately:Дef _init_(self, network_client=None: NetworkClient, authz_client=None: AuthzClient, accts_client=None:Д«y adding default values, it's possible to selectively initialize clients, which makes unit testing easier (more on this later). As I noted earlier, if you're patching more than a few calls, it's a sign that you should refactor. In this simple example, patch allowed us to paper over an inflexible design by creating an even more inflexible unit test. We create a mock network client for unit testing, using the autospec argument of MagicMock to create a mock object that adheres to the NetworkClient interface. Self.cloud_creator = CloudCreator(self.mock_network_client) Self.mock_network_client = MagicMock(autospec=NetworkClient) Now we can set up our tests like this:Д¬lass TestCloudCreator (unittest.TestCase) : One of the primary advantages of dependency injection is that it allows the developer to easily pass in mock objects when unit testing. This is a great simplification of the process, and astute observers will note that the specification of the client interface becomes of paramount importance, but that's another blog post. This encapsulation allows the class to be used with an HTTP client, a TCP/IP client, a ZMQ client, or an SQS/SNS client, so long as the network I/O conforms to a pre-specified interface defined in NetworkClient, such as NetworkClient.recv() and nd(data).

IUNIT TESTING PYTHON CODE

Therefore, it's logical to write the class in such a way that network I/O is handled by a client that is injected at runtime, rather than hard-coded (this code uses Python's type-hinting syntax):Дef _init_(self, network_client: NetworkClient) : In our example, CloudCreator's core functionality of creating cloud infrastructure is not dependent on any particular means of sending and receiving messages. This allows code to operate in multiple contexts, depending on what clients it is given.

IUNIT TESTING PYTHON SOFTWARE

Dependency Inversion and InjectionДependency inversion, and specifically dependency injection in this case, are well-worn subjects in software engineering circles for the uninitiated, dependency injection is the idea that a class or function should be given any external clients it depends on, rather than creating them itself. Experienced software engineers will see that this example is a prime opportunity for dependency inversion. In general, if testing a class requires a lot of patching of external clients, it's a sign that a refactor is needed.

A refactor of the structure would be required to properly unit test such a class in another language. Statically typed languages with compilers don't allow monkey patching (without some serious work).

IUNIT TESTING PYTHON PORTABLE

Code that is written that depends on patch to unit test is not portable to other languages.Using patch is a code smell because it means that the class under test has been coupled to one or more other concrete classes.When refactoring underlying implementations, using patch will require updating multiple unrelated unit tests, and it is not always clear which unit tests will require changes due to patch's use of hard-coded strings rather than more strongly 'typed' references (which can be caught by linters/IDEs).Constructor args make dependencies explicit. Using it means there are implicit dependencies somewhere in the class - another developer wouldn't ever know this.Furthermore, CloudCreator and its unit tests are strongly dependent on HTTPClient, which makes changing the network client difficult.ДЇugue engineer Josh Einhorn notes some other disadvantages of patch: If CloudCreator uses a lot of external clients, we need to stack a lot of patch calls. Patch has given us the ability to test our CloudCreator class without creating any network side effects. Mock_http_client_call.return_value = self.mock_http_client # Recall that patch patches the _initialization_ call of classes Self.mock_http_client = MagicMock(autospec=http_client.HTTPClient) work_client = http_client.HTTPClient()Д¬lass TestCloudCreator (unittest.TestCase) setUp (self, mock_http_client_call) : Consider a class, CloudCreator, that receives messages over HTTP, generates some side effects by creating cloud infrastructure, and sends messages over HTTP in response:

In particular, I want to revisit the idea of patching mock objects in unit tests.Д¬lients in this post refer to any objects that create side effects, such as disk or network I/O. This post covers some higher-level software engineering principles demonstrated in my experience with Python testing over the past year and half. My previous blog post, Python Mocking 101: Fake It Before You Make It, discussed the basic mechanics of mocking and unit testing in Python.

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