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Unit, Integration, and Functional Testing

Unit testing is, not surprisingly, the act of testing a "unit" in your application. In this context, a "unit" is often a function or a method of a class instance. The unit is also referred to as a "unit under test".

The goal of a single unit test is to test only some permutation of the "unit under test". If you write a unit test that aims to verify the result of a particular codepath through a Python function, you need only be concerned about testing the code that lives in the function body itself. If the function accepts a parameter that represents a complex application "domain object" (such as a resource, a database connection, or an SMTP server), the argument provided to this function during a unit test need not be and likely should not be a "real" implementation object. For example, although a particular function implementation may accept an argument that represents an SMTP server object, and the function may call a method of this object when the system is operating normally that would result in an email being sent, a unit test of this codepath of the function does not need to test that an email is actually sent. It just needs to make sure that the function calls the method of the object provided as an argument that would send an email if the argument happened to be the "real" implementation of an SMTP server object.

An integration test, on the other hand, is a different form of testing in which the interaction between two or more "units" is explicitly tested. Integration tests verify that the components of your application work together. You might make sure that an email was actually sent in an integration test.

A functional test is a form of integration test in which the application is run "literally". You would have to make sure that an email was actually sent in a functional test, because it tests your code end to end.

It is often considered best practice to write each type of tests for any given codebase. Unit testing often provides the opportunity to obtain better "coverage": it's usually possible to supply a unit under test with arguments and/or an environment which causes all of its potential codepaths to be executed. This is usually not as easy to do with a set of integration or functional tests, but integration and functional testing provides a measure of assurance that your "units" work together, as they will be expected to when your application is run in production.

The suggested mechanism for unit and integration testing of a :app:`Pyramid` application is the Python :mod:`unittest` module. Although this module is named :mod:`unittest`, it is actually capable of driving both unit and integration tests. A good :mod:`unittest` tutorial is available within Dive Into Python by Mark Pilgrim.

:app:`Pyramid` provides a number of facilities that make unit, integration, and functional tests easier to write. The facilities become particularly useful when your code calls into :app:`Pyramid` -related framework functions.

Test Set Up and Tear Down

:app:`Pyramid` uses a "global" (actually :term:`thread local`) data structure to hold on to two items: the current :term:`request` and the current :term:`application registry`. These data structures are available via the :func:`pyramid.threadlocal.get_current_request` and :func:`pyramid.threadlocal.get_current_registry` functions, respectively. See :ref:`threadlocals_chapter` for information about these functions and the data structures they return.

If your code uses these get_current_* functions or calls :app:`Pyramid` code which uses get_current_* functions, you will need to construct a :term:`Configurator` and call its begin method within the setUp method of your unit test and call the same Configurator's end method within the tearDown method of your unit test.

We'll also instruct the Configurator we use during testing to autocommit. Normally when a Configurator is used by an application, it defers performing any "real work" until its .commit method is called (often implicitly by the :meth:`pyramid.config.Configurator.make_wsgi_app` method). Passing autocommit=True to the Configurator constructor causes the Configurator to perform all actions implied by methods called on it immediately, which is more convenient for unit-testing purposes than needing to call :meth:`pyramid.config.Configurator.commit` in each test.

The use of a Configurator and its begin and end methods allows you to supply each unit test method in a test case with an environment that has an isolated registry and an isolated request for the duration of a single test. Here's an example of using this feature:

The above will make sure that :func:`pyramid.threadlocal.get_current_registry` will return the :term:`application registry` associated with the config Configurator instance when :func:`pyramid.threadlocal.get_current_registry` is called in a test case method attached to MyTest. Each test case method attached to MyTest will use an isolated registry.

The :meth:`pyramid.config.Configurator.begin` method accepts various arguments that influence the code run during the test. See the :ref:`configuration_module` chapter for information about the API of a :term:`Configurator`, including its begin and end methods.

If you also want to make :func:`pyramid.get_current_request` return something other than None during the course of a single test, you can pass a :term:`request` object into the :meth:`pyramid.config.Configurator.begin` method of the Configurator within the setUp method of your test:

If you pass a :term:`request` object into the begin method of the configurator within your test case's setUp, any test method attached to the MyTest test case that directly or indirectly calls :func:`pyramid.threadlocal.get_current_request` will receive the request you passed into the begin method. Otherwise, during testing, :func:`pyramid.threadlocal.get_current_request` will return None. We use a "dummy" request implementation supplied by :class:`pyramid.testing.DummyRequest` because it's easier to construct than a "real" :app:`Pyramid` request object.

What?

Thread local data structures are always a bit confusing, especially when they're used by frameworks. Sorry. So here's a rule of thumb: if you don't know whether you're calling code that uses the :func:`pyramid.threadlocal.get_current_registry` or :func:`pyramid.threadlocal.get_current_request` functions, or you don't care about any of this, but you still want to write test code, just always create an autocommitting Configurator instance and call its begin method within the setUp of a unit test, then subsequently call its end method in the test's tearDown. This won't really hurt anything if the application you're testing does not call any get_current* function.

Using the Configurator and pyramid.testing APIs in Unit Tests

The Configurator API and the pyramid.testing module provide a number of functions which can be used during unit testing. These functions make :term:`configuration declaration` calls to the current :term:`application registry`, but typically register a "stub" or "dummy" feature in place of the "real" feature that the code would call if it was being run normally.

For example, let's imagine you want to unit test a :app:`Pyramid` view function.

Without invoking any startup code or using the testing API, an attempt to run this view function in a unit test will result in an error. When a :app:`Pyramid` application starts normally, it will populate a :term:`application registry` using :term:`configuration declaration` calls made against a :term:`Configurator` (sometimes deferring to the application's configure.zcml :term:`ZCML` file via load_zcml). But if this application registry is not created and populated (e.g. with an :meth:`pyramid.config.Configurator.add_view` :term:`configuration declaration` or view declarations in :term:`ZCML`), like when you invoke application code via a unit test, :app:`Pyramid` API functions will tend to fail.

The testing API provided by :app:`Pyramid` allows you to simulate various application registry registrations for use under a unit testing framework without needing to invoke the actual application configuration implied by its run.py. For example, if you wanted to test the above view_fn (assuming it lived in the package named my.package), you could write a :class:`unittest.TestCase` that used the testing API.

In the above example, we create a MyTest test case that inherits from :mod:`unittest.TestCase`. If it's in our :app:`Pyramid` application, it will be found when setup.py test is run. It has two test methods.

The first test method, test_view_fn_not_submitted tests the view_fn function in the case that no "form" values (represented by request.params) have been submitted. Its first line registers a "dummy template renderer" named templates/show.pt via the :meth:`pyramid.config.Configurator.testing_add_renderer` method; this method returns a :class:`pyramid.testing.DummyTemplateRenderer` instance which we hang on to for later.

We then create a :class:`pyramid.testing.DummyRequest` object which simulates a WebOb request object API. A :class:`pyramid.testing.DummyRequest` is a request object that requires less setup than a "real" :app:`Pyramid` request. We call the function being tested with the manufactured request. When the function is called, :func:`pyramid.chameleon_zpt.render_template_to_response` will call the "dummy" template renderer object instead of the real template renderer object. When the dummy renderer is called, it will set attributes on itself corresponding to the non-path keyword arguments provided to the :func:`pyramid.chameleon_zpt.render_template_to_response` function. We check that the say parameter sent into the template rendering function was Hello in this specific example. The assert_ method of the renderer we've created will raise an :exc:`AssertionError` if the value passed to the renderer as say does not equal Hello (any number of keyword arguments are supported).

The second test method, named test_view_fn_submitted tests the alternate case, where the say form value has already been set in the request and performs a similar template registration and assertion. We assert at the end of this that the renderer's say attribute is Yo, as this is what is expected of the view function in the branch it's testing.

Note that the test calls the :meth:`pyramid.config.Configurator.begin` method in its setUp method and the end method of the same in its tearDown method. If you use any of the :class:`pyramid.config.Configurator` APIs during testing, be sure to use this pattern in your test case's setUp and tearDown; these methods make sure you're using a "fresh" :term:`application registry` per test run.

See the :ref:`testing_module` chapter for the entire :app:`Pyramid` -specific testing API. This chapter describes APIs for registering a security policy, registering resources at paths, registering event listeners, registering views and view permissions, and classes representing "dummy" implementations of a request and a resource.

See also the various methods of the :term:`Configurator` documented in :ref:`configuration_module` that begin with the testing_ prefix.

Creating Integration Tests

In :app:`Pyramid`, a unit test typically relies on "mock" or "dummy" implementations to give the code under test only enough context to run.

"Integration testing" implies another sort of testing. In the context of a :app:`Pyramid`, integration test, the test logic tests the functionality of some code and its integration with the rest of the :app:`Pyramid` framework.

In :app:`Pyramid` applications that use :term:`ZCML`, you can create an integration test by loading its ZCML in the test's setup code. This causes the entire :app:`Pyramid` environment to be set up and torn down as if your application was running "for real". This is a heavy-hammer way of making sure that your tests have enough context to run properly, and it tests your code's integration with the rest of :app:`Pyramid`.

Let's demonstrate this by showing an integration test for a view. The below test assumes that your application's package name is myapp, and that there is a views module in the app with a function with the name my_view in it that returns the response 'Welcome to this application' after accessing some values that require a fully set up environment.

Unless you cannot avoid it, you should prefer writing unit tests that use the :class:`pyramid.config.Configurator` API to set up the right "mock" registrations rather than creating an integration test. Unit tests will run faster (because they do less for each test) and the result of a unit test is usually easier to make assertions about.

Creating Functional Tests

Functional tests test your literal application.

The below test assumes that your application's package name is myapp, and that there is view that returns an HTML body when the root URL is invoked. It further assumes that you've added a tests_require dependency on the WebTest package within your setup.py file. :term:`WebTest` is a functional testing package written by Ian Bicking.

When this test is run, each test creates a "real" WSGI application using the main function in your myapp.__init__ module and uses :term:`WebTest` to wrap that WSGI application. It assigns the result to self.testapp. In the test named test_root, we use the testapp's get method to invoke the root URL. We then assert that the returned HTML has the string Pyramid in it.

See the :term:`WebTest` documentation for further information about the methods available to a :class:`webtest.TestApp` instance.

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