How to parametrize fixtures and test functions¶
pytest enables test parametrization at several levels:
pytest.fixture()
allows one to parametrize fixture functions.
@pytest.mark.parametrize allows one to define multiple sets of arguments and fixtures at the test function or class.
pytest_generate_tests allows one to define custom parametrization schemes or extensions.
@pytest.mark.parametrize
: parametrizing test functions¶
The builtin pytest.mark.parametrize decorator enables parametrization of arguments for a test function. Here is a typical example of a test function that implements checking that a certain input leads to an expected output:
# content of test_expectation.py
import pytest
@pytest.mark.parametrize("test_input,expected", [("3+5", 8), ("2+4", 6), ("6*9", 42)])
def test_eval(test_input, expected):
assert eval(test_input) == expected
Here, the @parametrize
decorator defines three different (test_input,expected)
tuples so that the test_eval
function will run three times using
them in turn:
$ pytest
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-7.x.y, pluggy-1.x.y
rootdir: /home/sweet/project
collected 3 items
test_expectation.py ..F [100%]
================================= FAILURES =================================
____________________________ test_eval[6*9-42] _____________________________
test_input = '6*9', expected = 42
@pytest.mark.parametrize("test_input,expected", [("3+5", 8), ("2+4", 6), ("6*9", 42)])
def test_eval(test_input, expected):
> assert eval(test_input) == expected
E AssertionError: assert 54 == 42
E + where 54 = eval('6*9')
test_expectation.py:6: AssertionError
========================= short test summary info ==========================
FAILED test_expectation.py::test_eval[6*9-42] - AssertionError: assert 54...
======================= 1 failed, 2 passed in 0.12s ========================
Note
Parameter values are passed as-is to tests (no copy whatsoever).
For example, if you pass a list or a dict as a parameter value, and the test case code mutates it, the mutations will be reflected in subsequent test case calls.
Note
pytest by default escapes any non-ascii characters used in unicode strings
for the parametrization because it has several downsides.
If however you would like to use unicode strings in parametrization
and see them in the terminal as is (non-escaped), use this option
in your pytest.ini
:
[pytest]
disable_test_id_escaping_and_forfeit_all_rights_to_community_support = True
Keep in mind however that this might cause unwanted side effects and even bugs depending on the OS used and plugins currently installed, so use it at your own risk.
As designed in this example, only one pair of input/output values fails
the simple test function. And as usual with test function arguments,
you can see the input
and output
values in the traceback.
Note that you could also use the parametrize marker on a class or a module (see How to mark test functions with attributes) which would invoke several functions with the argument sets, for instance:
import pytest
@pytest.mark.parametrize("n,expected", [(1, 2), (3, 4)])
class TestClass:
def test_simple_case(self, n, expected):
assert n + 1 == expected
def test_weird_simple_case(self, n, expected):
assert (n * 1) + 1 == expected
To parametrize all tests in a module, you can assign to the pytestmark
global variable:
import pytest
pytestmark = pytest.mark.parametrize("n,expected", [(1, 2), (3, 4)])
class TestClass:
def test_simple_case(self, n, expected):
assert n + 1 == expected
def test_weird_simple_case(self, n, expected):
assert (n * 1) + 1 == expected
It is also possible to mark individual test instances within parametrize,
for example with the builtin mark.xfail
:
# content of test_expectation.py
import pytest
@pytest.mark.parametrize(
"test_input,expected",
[("3+5", 8), ("2+4", 6), pytest.param("6*9", 42, marks=pytest.mark.xfail)],
)
def test_eval(test_input, expected):
assert eval(test_input) == expected
Let’s run this:
$ pytest
=========================== test session starts ============================
platform linux -- Python 3.x.y, pytest-7.x.y, pluggy-1.x.y
rootdir: /home/sweet/project
collected 3 items
test_expectation.py ..x [100%]
======================= 2 passed, 1 xfailed in 0.12s =======================
The one parameter set which caused a failure previously now shows up as an “xfailed” (expected to fail) test.
In case the values provided to parametrize
result in an empty list - for
example, if they’re dynamically generated by some function - the behaviour of
pytest is defined by the empty_parameter_set_mark
option.
To get all combinations of multiple parametrized arguments you can stack
parametrize
decorators:
import pytest
@pytest.mark.parametrize("x", [0, 1])
@pytest.mark.parametrize("y", [2, 3])
def test_foo(x, y):
pass
This will run the test with the arguments set to x=0/y=2
, x=1/y=2
,
x=0/y=3
, and x=1/y=3
exhausting parameters in the order of the decorators.
Basic pytest_generate_tests
example¶
Sometimes you may want to implement your own parametrization scheme
or implement some dynamism for determining the parameters or scope
of a fixture. For this, you can use the pytest_generate_tests
hook
which is called when collecting a test function. Through the passed in
metafunc
object you can inspect the requesting test context and, most
importantly, you can call metafunc.parametrize()
to cause
parametrization.
For example, let’s say we want to run a test taking string inputs which
we want to set via a new pytest
command line option. Let’s first write
a simple test accepting a stringinput
fixture function argument:
# content of test_strings.py
def test_valid_string(stringinput):
assert stringinput.isalpha()
Now we add a conftest.py
file containing the addition of a
command line option and the parametrization of our test function:
# content of conftest.py
def pytest_addoption(parser):
parser.addoption(
"--stringinput",
action="append",
default=[],
help="list of stringinputs to pass to test functions",
)
def pytest_generate_tests(metafunc):
if "stringinput" in metafunc.fixturenames:
metafunc.parametrize("stringinput", metafunc.config.getoption("stringinput"))
If we now pass two stringinput values, our test will run twice:
$ pytest -q --stringinput="hello" --stringinput="world" test_strings.py
.. [100%]
2 passed in 0.12s
Let’s also run with a stringinput that will lead to a failing test:
$ pytest -q --stringinput="!" test_strings.py
F [100%]
================================= FAILURES =================================
___________________________ test_valid_string[!] ___________________________
stringinput = '!'
def test_valid_string(stringinput):
> assert stringinput.isalpha()
E AssertionError: assert False
E + where False = <built-in method isalpha of str object at 0xdeadbeef0001>()
E + where <built-in method isalpha of str object at 0xdeadbeef0001> = '!'.isalpha
test_strings.py:4: AssertionError
========================= short test summary info ==========================
FAILED test_strings.py::test_valid_string[!] - AssertionError: assert False
1 failed in 0.12s
As expected our test function fails.
If you don’t specify a stringinput it will be skipped because
metafunc.parametrize()
will be called with an empty parameter
list:
$ pytest -q -rs test_strings.py
s [100%]
========================= short test summary info ==========================
SKIPPED [1] test_strings.py: got empty parameter set ['stringinput'], function test_valid_string at /home/sweet/project/test_strings.py:2
1 skipped in 0.12s
Note that when calling metafunc.parametrize
multiple times with different parameter sets, all parameter names across
those sets cannot be duplicated, otherwise an error will be raised.
More examples¶
For further examples, you might want to look at more parametrization examples.