How to use unittest-based tests with pytest ​
pytest
supports running Python unittest
-based tests out of the box. It’s meant for leveraging existing unittest
-based test suites to use pytest as a test runner and also allow to incrementally adapt the test suite to take full advantage of pytest’s features.
To run an existing unittest
-style test suite using pytest
, type:
pytest tests
pytest tests
pytest will automatically collect unittest.TestCase
subclasses and their test
methods in test_*.py
or *_test.py
files.
Almost all unittest
features are supported:
@unittest.skip
style decorators;setUp/tearDown
;setUpClass/tearDownClass
;setUpModule/tearDownModule
;
Additionally, subtests are supported by the pytest-subtests plugin.
Up to this point pytest does not have support for the following features:
Benefits out of the box ​
By running your test suite with pytest you can make use of several features, in most cases without having to modify existing code:
Obtain more informative tracebacks;
stdout and stderr capturing;
Test selection options using
-k
and-m
flags;Stopping after the first (or N) failures;
–pdb
command-line option for debugging on test failures (see note below);Distribute tests to multiple CPUs using the pytest-xdist plugin;
Use plain assert-statements instead of
self.assert*
functions (unittest2pytest is immensely helpful in this);
pytest features in unittest.TestCase
subclasses ​
The following pytest features work in unittest.TestCase
subclasses:
Marks:
skip
,skipif
,xfail
;
The following pytest features do not work, and probably never will due to different design philosophies:
Third party plugins may or may not work well, depending on the plugin and the test suite.
Mixing pytest fixtures into unittest.TestCase subclasses using marks ​
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()
# 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
# 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:
$ pytest test_unittest_db.py
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-7.x.y, pluggy-1.x.y
rootdir: /home/sweet/project
collected 2 items
test_unittest_db.py FF [100%]
================================= 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.db_class.<locals>.DummyDB object at 0xdeadbeef0001>
E assert 0
test_unittest_db.py:11: 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.db_class.<locals>.DummyDB object at 0xdeadbeef0001>
E assert 0
test_unittest_db.py:14: AssertionError
========================= short test summary info ==========================
FAILED test_unittest_db.py::MyTest::test_method1 - AssertionError: <conft...
FAILED test_unittest_db.py::MyTest::test_method2 - AssertionError: <conft...
============================ 2 failed in 0.12s =============================
$ pytest test_unittest_db.py
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-7.x.y, pluggy-1.x.y
rootdir: /home/sweet/project
collected 2 items
test_unittest_db.py FF [100%]
================================= 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.db_class.<locals>.DummyDB object at 0xdeadbeef0001>
E assert 0
test_unittest_db.py:11: 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.db_class.<locals>.DummyDB object at 0xdeadbeef0001>
E assert 0
test_unittest_db.py:14: AssertionError
========================= short test summary info ==========================
FAILED test_unittest_db.py::MyTest::test_method1 - AssertionError: <conft...
FAILED test_unittest_db.py::MyTest::test_method2 - AssertionError: <conft...
============================ 2 failed in 0.12s =============================
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.
Using autouse fixtures and accessing other fixtures ​
Although it’s usually better to explicitly 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 tmp_path
fixture to delegate the creation of a per-test temporary directory:
# content of test_unittest_cleandir.py
import unittest
import pytest
class MyTest(unittest.TestCase):
@pytest.fixture(autouse=True)
def initdir(self, tmp_path, monkeypatch):
monkeypatch.chdir(tmp_path) # change to pytest-provided temporary directory
tmp_path.joinpath("samplefile.ini").write_text("# testdata", encoding="utf-8")
def test_method(self):
with open("samplefile.ini", encoding="utf-8") as f:
s = f.read()
assert "testdata" in s
# content of test_unittest_cleandir.py
import unittest
import pytest
class MyTest(unittest.TestCase):
@pytest.fixture(autouse=True)
def initdir(self, tmp_path, monkeypatch):
monkeypatch.chdir(tmp_path) # change to pytest-provided temporary directory
tmp_path.joinpath("samplefile.ini").write_text("# testdata", encoding="utf-8")
def test_method(self):
with open("samplefile.ini", encoding="utf-8") as f:
s = f.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 …:
$ pytest -q test_unittest_cleandir.py
. [100%]
1 passed in 0.12s
$ pytest -q test_unittest_cleandir.py
. [100%]
1 passed in 0.12s
… gives us one passed test because the initdir
fixture function was executed ahead of the test_method
.
Note
unittest.TestCase
methods cannot directly receive fixture arguments as implementing that is likely to inflict on the ability to run general unittest.TestCase
test suites.
The above usefixtures
and autouse
examples should help to mix in pytest fixtures into unittest suites.
You can also gradually move away from subclassing from unittest.TestCase
to plain asserts and then start to benefit from the full pytest feature set step by step.
Note
Due to architectural differences between the two frameworks, setup and teardown for unittest
-based tests is performed during the call
phase of testing instead of in pytest
’s standard setup
and teardown
stages. This can be important to understand in some situations, particularly when reasoning about errors. For example, if a unittest
-based suite exhibits errors during setup, pytest
will report no errors during its setup
phase and will instead raise the error during call
.