pytest has support for running Python unittest.py style tests. It’s meant for leveraging existing unittest-style projects to use pytest features. Concretely, pytest will automatically collect unittest.TestCase subclasses and their test methods in test files. It will invoke typical setup/teardown methods and generally try to make test suites written to run on unittest, to also run using pytest. We assume here that you are familiar with writing unittest.TestCase style tests and rather focus on integration aspects.
After Installation type:
and you should be able to run your unittest-style tests if they are contained in test_* modules. If that works for you then you can make use of most pytest features, for example --pdb debugging in failures, using plain assert-statements, more informative tracebacks, stdout-capturing or distributing tests to multiple CPUs via the -nNUM option if you installed the pytest-xdist plugin. Please refer to the general pytest documentation for many more examples.
Running your unittest with pytest allows you to use its fixture mechanism with unittest.TestCase style tests. Assuming you have at least skimmed the pytest fixture features, let’s jump-start into an example that integrates a pytest db_class fixture, setting up a class-cached database object, and then reference it from a unittest-style test:
# content of conftest.py # we define a fixture function below and it will be "used" by # referencing its name from tests import pytest @pytest.fixture(scope="class") def db_class(request): class DummyDB: pass # set a class attribute on the invoking test context request.cls.db = DummyDB()
This defines a fixture function db_class which - if used - is called once for each test class and which sets the class-level db attribute to a DummyDB instance. The fixture function achieves this by receiving a special request object which gives access to the requesting test context such as the cls attribute, denoting the class from which the fixture is used. This architecture de-couples fixture writing from actual test code and allows re-use of the fixture by a minimal reference, the fixture name. So let’s write an actual unittest.TestCase class using our fixture definition:
# content of test_unittest_db.py import unittest import pytest @pytest.mark.usefixtures("db_class") class MyTest(unittest.TestCase): def test_method1(self): assert hasattr(self, "db") assert 0, self.db # fail for demo purposes def test_method2(self): assert 0, self.db # fail for demo purposes
The @pytest.mark.usefixtures("db_class") class-decorator makes sure that the pytest fixture function db_class is called once per class. Due to the deliberately failing assert statements, we can take a look at the self.db values in the traceback:
$ py.test test_unittest_db.py =========================== test session starts ============================ platform linux2 -- Python 2.7.6 -- py-1.4.22 -- pytest-2.6.0 collected 2 items test_unittest_db.py FF ================================= FAILURES ================================= ___________________________ MyTest.test_method1 ____________________________ self = <test_unittest_db.MyTest testMethod=test_method1> def test_method1(self): assert hasattr(self, "db") > assert 0, self.db # fail for demo purposes E AssertionError: <conftest.DummyDB instance at 0x2ba71cccb128> test_unittest_db.py:9: AssertionError ___________________________ MyTest.test_method2 ____________________________ self = <test_unittest_db.MyTest testMethod=test_method2> def test_method2(self): > assert 0, self.db # fail for demo purposes E AssertionError: <conftest.DummyDB instance at 0x2ba71cccb128> test_unittest_db.py:12: AssertionError ========================= 2 failed in 0.04 seconds =========================
This default pytest traceback shows that the two test methods share the same self.db instance which was our intention when writing the class-scoped fixture function above.
Although it’s usually better to explicitely declare use of fixtures you need for a given test, you may sometimes want to have fixtures that are automatically used in a given context. After all, the traditional style of unittest-setup mandates the use of this implicit fixture writing and chances are, you are used to it or like it.
You can flag fixture functions with @pytest.fixture(autouse=True) and define the fixture function in the context where you want it used. Let’s look at an initdir fixture which makes all test methods of a TestCase class execute in a temporary directory with a pre-initialized samplefile.ini. Our initdir fixture itself uses the pytest builtin tmpdir fixture to delegate the creation of a per-test temporary directory:
# content of test_unittest_cleandir.py import pytest import unittest class MyTest(unittest.TestCase): @pytest.fixture(autouse=True) def initdir(self, tmpdir): tmpdir.chdir() # change to pytest-provided temporary directory tmpdir.join("samplefile.ini").write("# testdata") def test_method(self): s = open("samplefile.ini").read() assert "testdata" in s
Due to the autouse flag the initdir fixture function will be used for all methods of the class where it is defined. This is a shortcut for using a @pytest.mark.usefixtures("initdir") marker on the class like in the previous example.
Running this test module ...:
$ py.test -q test_unittest_cleandir.py . 1 passed in 0.03 seconds
... gives us one passed test because the initdir fixture function was executed ahead of the test_method.
While pytest supports receiving fixtures via test function arguments for non-unittest test methods, unittest.TestCase methods cannot directly receive fixture function arguments as implementing that is likely to inflict on the ability to run general unittest.TestCase test suites. Maybe optional support would be possible, though. If unittest finally grows a plugin system that should help as well. In the meanwhile, the above usefixtures and autouse examples should help to mix in pytest fixtures into unittest suites. And of course you can also start to selectively leave away the unittest.TestCase subclassing, use plain asserts and get the unlimited pytest feature set.