222 lines
7.6 KiB
Plaintext
222 lines
7.6 KiB
Plaintext
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.. _`test generators`:
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.. _`parametrizing-tests`:
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.. _`parametrized test functions`:
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.. _`parametrize`:
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.. _`parametrize-basics`:
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Parametrizing fixtures and test functions
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==========================================================================
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pytest supports test parametrization in several well-integrated ways:
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- :py:func:`pytest.fixture` allows to define :ref:`parametrization
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at the level of fixture functions <fixture-parametrize>`.
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* `@pytest.mark.parametrize`_ allows to define parametrization at the
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function or class level, provides multiple argument/fixture sets
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for a particular test function or class.
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* `pytest_generate_tests`_ enables implementing your own custom
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dynamic parametrization scheme or extensions.
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.. _parametrizemark:
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.. _`@pytest.mark.parametrize`:
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``@pytest.mark.parametrize``: parametrizing test functions
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---------------------------------------------------------------------
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.. regendoc: wipe
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.. versionadded:: 2.2, improved in 2.4
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The builtin ``pytest.mark.parametrize`` decorator enables
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parametrization of arguments for a test function. Here is a typical example
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of a test function that implements checking that a certain input leads
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to an expected output::
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# content of test_expectation.py
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import pytest
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@pytest.mark.parametrize("input,expected", [
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("3+5", 8),
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("2+4", 6),
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("6*9", 42),
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])
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def test_eval(input, expected):
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assert eval(input) == expected
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Here, the ``@parametrize`` decorator defines three different ``(input,expected)``
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tuples so that the ``test_eval`` function will run three times using
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them in turn::
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$ py.test
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=========================== test session starts ============================
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platform linux -- Python 3.4.0 -- py-1.4.25 -- pytest-2.6.3
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collected 3 items
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test_expectation.py ..F
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================================= FAILURES =================================
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____________________________ test_eval[6*9-42] _____________________________
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input = '6*9', expected = 42
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@pytest.mark.parametrize("input,expected", [
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("3+5", 8),
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("2+4", 6),
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("6*9", 42),
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])
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def test_eval(input, expected):
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> assert eval(input) == expected
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E assert 54 == 42
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E + where 54 = eval('6*9')
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test_expectation.py:8: AssertionError
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==================== 1 failed, 2 passed in 0.01 seconds ====================
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As designed in this example, only one pair of input/output values fails
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the simple test function. And as usual with test function arguments,
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you can see the ``input`` and ``output`` values in the traceback.
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Note that you could also use the parametrize marker on a class or a module
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(see :ref:`mark`) which would invoke several functions with the argument sets.
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It is also possible to mark individual test instances within parametrize,
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for example with the builtin ``mark.xfail``::
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# content of test_expectation.py
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import pytest
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@pytest.mark.parametrize("input,expected", [
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("3+5", 8),
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("2+4", 6),
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pytest.mark.xfail(("6*9", 42)),
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])
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def test_eval(input, expected):
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assert eval(input) == expected
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Let's run this::
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$ py.test
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=========================== test session starts ============================
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platform linux -- Python 3.4.0 -- py-1.4.25 -- pytest-2.6.3
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collected 3 items
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test_expectation.py ..x
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=================== 2 passed, 1 xfailed in 0.02 seconds ====================
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The one parameter set which caused a failure previously now
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shows up as an "xfailed (expected to fail)" test.
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.. note::
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In versions prior to 2.4 one needed to specify the argument
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names as a tuple. This remains valid but the simpler ``"name1,name2,..."``
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comma-separated-string syntax is now advertised first because
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it's easier to write and produces less line noise.
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.. _`pytest_generate_tests`:
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Basic ``pytest_generate_tests`` example
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---------------------------------------------
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Sometimes you may want to implement your own parametrization scheme
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or implement some dynamism for determining the parameters or scope
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of a fixture. For this, you can use the ``pytest_generate_tests`` hook
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which is called when collecting a test function. Through the passed in
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`metafunc` object you can inspect the requesting test context and, most
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importantly, you can call ``metafunc.parametrize()`` to cause
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parametrization.
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For example, let's say we want to run a test taking string inputs which
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we want to set via a new ``pytest`` command line option. Let's first write
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a simple test accepting a ``stringinput`` fixture function argument::
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# content of test_strings.py
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def test_valid_string(stringinput):
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assert stringinput.isalpha()
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Now we add a ``conftest.py`` file containing the addition of a
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command line option and the parametrization of our test function::
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# content of conftest.py
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def pytest_addoption(parser):
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parser.addoption("--stringinput", action="append", default=[],
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help="list of stringinputs to pass to test functions")
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def pytest_generate_tests(metafunc):
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if 'stringinput' in metafunc.fixturenames:
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metafunc.parametrize("stringinput",
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metafunc.config.option.stringinput)
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If we now pass two stringinput values, our test will run twice::
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$ py.test -q --stringinput="hello" --stringinput="world" test_strings.py
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..
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2 passed in 0.01 seconds
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Let's also run with a stringinput that will lead to a failing test::
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$ py.test -q --stringinput="!" test_strings.py
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F
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================================= FAILURES =================================
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___________________________ test_valid_string[!] ___________________________
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stringinput = '!'
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def test_valid_string(stringinput):
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> assert stringinput.isalpha()
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E assert <built-in method isalpha of str object at 0x2b1c6de5bb20>()
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E + where <built-in method isalpha of str object at 0x2b1c6de5bb20> = '!'.isalpha
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test_strings.py:3: AssertionError
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1 failed in 0.01 seconds
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As expected our test function fails.
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If you don't specify a stringinput it will be skipped because
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``metafunc.parametrize()`` will be called with an empty parameter
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listlist::
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$ py.test -q -rs test_strings.py
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s
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========================= short test summary info ==========================
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SKIP [1] /home/hpk/p/pytest/.tox/regen/lib/python3.4/site-packages/_pytest/python.py:1139: got empty parameter set, function test_valid_string at /tmp/doc-exec-180/test_strings.py:1
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1 skipped in 0.01 seconds
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For further examples, you might want to look at :ref:`more
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parametrization examples <paramexamples>`.
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.. _`metafunc object`:
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The **metafunc** object
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-------------------------------------------
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.. currentmodule:: _pytest.python
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metafunc objects are passed to the ``pytest_generate_tests`` hook.
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They help to inspect a testfunction and to generate tests
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according to test configuration or values specified
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in the class or module where a test function is defined:
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``metafunc.fixturenames``: set of required function arguments for given function
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``metafunc.function``: underlying python test function
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``metafunc.cls``: class object where the test function is defined in or None.
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``metafunc.module``: the module object where the test function is defined in.
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``metafunc.config``: access to command line opts and general config
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``metafunc.funcargnames``: alias for ``fixturenames``, for pre-2.3 compatibility
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.. automethod:: Metafunc.parametrize
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.. automethod:: Metafunc.addcall(funcargs=None,id=_notexists,param=_notexists)
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