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Parameterized testing in Python sucks.
parameterized
fixes that. For everything. Parameterized testing for nose,
parameterized testing for py.test, parameterized testing for unittest.
.. code:: python
from nose.tools import assert_equal from parameterized import parameterized, parameterized_class
import unittest import math
@parameterized([ (2, 2, 4), (2, 3, 8), (1, 9, 1), (0, 9, 0), ]) def test_pow(base, exponent, expected): assert_equal(math.pow(base, exponent), expected)
class TestMathUnitTest(unittest.TestCase): @parameterized.expand([ ("negative", -1.5, -2.0), ("integer", 1, 1.0), ("large fraction", 1.6, 1), ]) def test_floor(self, name, input, expected): assert_equal(math.floor(input), expected)
@parameterized_class(('a', 'b', 'expected_sum', 'expected_product'), [ (1, 2, 3, 2), (5, 5, 10, 25), ]) class TestMathClass(unittest.TestCase): def test_add(self): assert_equal(self.a + self.b, self.expected_sum)
def test_multiply(self):
assert_equal(self.a * self.b, self.expected_product)
@parameterized_class([ { "a": 3, "expected": 2 }, { "b": 5, "expected": -4 }, ]) class TestMathClassDict(unittest.TestCase): a = 1 b = 1
def test_subtract(self):
assert_equal(self.a - self.b, self.expected)
With nose (and nose2)::
$ nosetests -v test_math.py
test_floor_0_negative (test_math.TestMathUnitTest) ... ok
test_floor_1_integer (test_math.TestMathUnitTest) ... ok
test_floor_2_large_fraction (test_math.TestMathUnitTest) ... ok
test_math.test_pow(2, 2, 4, {}) ... ok
test_math.test_pow(2, 3, 8, {}) ... ok
test_math.test_pow(1, 9, 1, {}) ... ok
test_math.test_pow(0, 9, 0, {}) ... ok
test_add (test_math.TestMathClass_0) ... ok
test_multiply (test_math.TestMathClass_0) ... ok
test_add (test_math.TestMathClass_1) ... ok
test_multiply (test_math.TestMathClass_1) ... ok
test_subtract (test_math.TestMathClassDict_0) ... ok
----------------------------------------------------------------------
Ran 12 tests in 0.015s
OK
As the package name suggests, nose is best supported and will be used for all further examples.
With py.test (version 2.0 and above)::
$ py.test -v test_math.py
============================= test session starts ==============================
platform darwin -- Python 3.6.1, pytest-3.1.3, py-1.4.34, pluggy-0.4.0
collecting ... collected 13 items
test_math.py::test_pow::[0] PASSED
test_math.py::test_pow::[1] PASSED
test_math.py::test_pow::[2] PASSED
test_math.py::test_pow::[3] PASSED
test_math.py::TestMathUnitTest::test_floor_0_negative PASSED
test_math.py::TestMathUnitTest::test_floor_1_integer PASSED
test_math.py::TestMathUnitTest::test_floor_2_large_fraction PASSED
test_math.py::TestMathClass_0::test_add PASSED
test_math.py::TestMathClass_0::test_multiply PASSED
test_math.py::TestMathClass_1::test_add PASSED
test_math.py::TestMathClass_1::test_multiply PASSED
test_math.py::TestMathClassDict_0::test_subtract PASSED
==================== 12 passed, 4 warnings in 0.16 seconds =====================
With unittest (and unittest2)::
$ python -m unittest -v test_math
test_floor_0_negative (test_math.TestMathUnitTest) ... ok
test_floor_1_integer (test_math.TestMathUnitTest) ... ok
test_floor_2_large_fraction (test_math.TestMathUnitTest) ... ok
test_add (test_math.TestMathClass_0) ... ok
test_multiply (test_math.TestMathClass_0) ... ok
test_add (test_math.TestMathClass_1) ... ok
test_multiply (test_math.TestMathClass_1) ... ok
test_subtract (test_math.TestMathClassDict_0) ... ok
----------------------------------------------------------------------
Ran 8 tests in 0.001s
OK
(note: because unittest does not support test decorators, only tests created
with @parameterized.expand
will be executed)
With green::
$ green test_math.py -vvv
test_math
TestMathClass_1
. test_method_a
. test_method_b
TestMathClass_2
. test_method_a
. test_method_b
TestMathClass_3
. test_method_a
. test_method_b
TestMathUnitTest
. test_floor_0_negative
. test_floor_1_integer
. test_floor_2_large_fraction
TestMathClass_0
. test_add
. test_multiply
TestMathClass_1
. test_add
. test_multiply
TestMathClassDict_0
. test_subtract
Ran 12 tests in 0.121s
OK (passes=9)
::
$ pip install parameterized
Yes
__ (mostly).
__ https://app.circleci.com/pipelines/github/wolever/parameterized?branch=master
.. list-table:: :header-rows: 1 :stub-columns: 1
@mock.patch
@parameterized.expand
)
@parameterized.expand
)
§: nose and unittest2 - both of which were last updated in 2015 - sadly do not appear to support Python 3.10 or 3.11.
*: py.test 2 does not appear to work under Python 3 (#71)
, and
py.test 3 does not appear to work under Python 3.10 or 3.11 (#154)
.
**: py.test 4 is not yet supported (but coming!) in issue #34
__
†: py.test fixture support is documented in issue #81
__
https://github.com/wolever/parameterized/issues/71 https://github.com/wolever/parameterized/issues/154 https://github.com/wolever/parameterized/issues/34 https://github.com/wolever/parameterized/issues/81
(this section left intentionally blank)
The @parameterized
and @parameterized.expand
decorators accept a list
or iterable of tuples or param(...)
, or a callable which returns a list or
iterable:
.. code:: python
from parameterized import parameterized, param
# A list of tuples
@parameterized([
(2, 3, 5),
(3, 5, 8),
])
def test_add(a, b, expected):
assert_equal(a + b, expected)
# A list of params
@parameterized([
param("10", 10),
param("10", 16, base=16),
])
def test_int(str_val, expected, base=10):
assert_equal(int(str_val, base=base), expected)
# An iterable of params
@parameterized(
param.explicit(*json.loads(line))
for line in open("testcases.jsons")
)
def test_from_json_file(...):
...
# A callable which returns a list of tuples
def load_test_cases():
return [
("test1", ),
("test2", ),
]
@parameterized(load_test_cases)
def test_from_function(name):
...
.. **
Note that, when using an iterator or a generator, all the items will be loaded into memory before the start of the test run (we do this explicitly to ensure that generators are exhausted exactly once in multi-process or multi-threaded testing environments).
The @parameterized
decorator can be used test class methods, and standalone
functions:
.. code:: python
from parameterized import parameterized
class AddTest(object):
@parameterized([
(2, 3, 5),
])
def test_add(self, a, b, expected):
assert_equal(a + b, expected)
@parameterized([
(2, 3, 5),
])
def test_add(a, b, expected):
assert_equal(a + b, expected)
And @parameterized.expand
can be used to generate test methods in
situations where test generators cannot be used (for example, when the test
class is a subclass of unittest.TestCase
):
.. code:: python
import unittest
from parameterized import parameterized
class AddTestCase(unittest.TestCase):
@parameterized.expand([
("2 and 3", 2, 3, 5),
("3 and 5", 3, 5, 8),
])
def test_add(self, _, a, b, expected):
assert_equal(a + b, expected)
Will create the test cases::
$ nosetests example.py
test_add_0_2_and_3 (example.AddTestCase) ... ok
test_add_1_3_and_5 (example.AddTestCase) ... ok
----------------------------------------------------------------------
Ran 2 tests in 0.001s
OK
Note that @parameterized.expand
works by creating new methods on the test
class. If the first parameter is a string, that string will be added to the end
of the method name. For example, the test case above will generate the methods
test_add_0_2_and_3
and test_add_1_3_and_5
.
The names of the test cases generated by @parameterized.expand
can be
customized using the name_func
keyword argument. The value should
be a function which accepts three arguments: testcase_func
, param_num
,
and params
, and it should return the name of the test case.
testcase_func
will be the function to be tested, param_num
will be the
index of the test case parameters in the list of parameters, and param
(an instance of param
) will be the parameters which will be used.
.. code:: python
import unittest
from parameterized import parameterized
def custom_name_func(testcase_func, param_num, param):
return "%s_%s" %(
testcase_func.__name__,
parameterized.to_safe_name("_".join(str(x) for x in param.args)),
)
class AddTestCase(unittest.TestCase):
@parameterized.expand([
(2, 3, 5),
(2, 3, 5),
], name_func=custom_name_func)
def test_add(self, a, b, expected):
assert_equal(a + b, expected)
Will create the test cases::
$ nosetests example.py
test_add_1_2_3 (example.AddTestCase) ... ok
test_add_2_3_5 (example.AddTestCase) ... ok
----------------------------------------------------------------------
Ran 2 tests in 0.001s
OK
The param(...)
helper class stores the parameters for one specific test
case. It can be used to pass keyword arguments to test cases:
.. code:: python
from parameterized import parameterized, param
@parameterized([
param("10", 10),
param("10", 16, base=16),
])
def test_int(str_val, expected, base=10):
assert_equal(int(str_val, base=base), expected)
If test cases have a docstring, the parameters for that test case will be
appended to the first line of the docstring. This behavior can be controlled
with the doc_func
argument:
.. code:: python
from parameterized import parameterized
@parameterized([
(1, 2, 3),
(4, 5, 9),
])
def test_add(a, b, expected):
""" Test addition. """
assert_equal(a + b, expected)
def my_doc_func(func, num, param):
return "%s: %s with %s" %(num, func.__name__, param)
@parameterized([
(5, 4, 1),
(9, 6, 3),
], doc_func=my_doc_func)
def test_subtraction(a, b, expected):
assert_equal(a - b, expected)
::
$ nosetests example.py
Test addition. [with a=1, b=2, expected=3] ... ok
Test addition. [with a=4, b=5, expected=9] ... ok
0: test_subtraction with param(*(5, 4, 1)) ... ok
1: test_subtraction with param(*(9, 6, 3)) ... ok
----------------------------------------------------------------------
Ran 4 tests in 0.001s
OK
Finally @parameterized_class
parameterizes an entire class, using
either a list of attributes, or a list of dicts that will be applied to the
class:
.. code:: python
from yourapp.models import User
from parameterized import parameterized_class
@parameterized_class([
{ "username": "user_1", "access_level": 1 },
{ "username": "user_2", "access_level": 2, "expected_status_code": 404 },
])
class TestUserAccessLevel(TestCase):
expected_status_code = 200
def setUp(self):
self.client.force_login(User.objects.get(username=self.username)[0])
def test_url_a(self):
response = self.client.get('/url')
self.assertEqual(response.status_code, self.expected_status_code)
def tearDown(self):
self.client.logout()
@parameterized_class(("username", "access_level", "expected_status_code"), [
("user_1", 1, 200),
("user_2", 2, 404)
])
class TestUserAccessLevel(TestCase):
def setUp(self):
self.client.force_login(User.objects.get(username=self.username)[0])
def test_url_a(self):
response = self.client.get("/url")
self.assertEqual(response.status_code, self.expected_status_code)
def tearDown(self):
self.client.logout()
The @parameterized_class
decorator accepts a class_name_func
argument,
which controls the name of the parameterized classes generated by
@parameterized_class
:
.. code:: python
from parameterized import parameterized, parameterized_class
def get_class_name(cls, num, params_dict):
# By default the generated class named includes either the "name"
# parameter (if present), or the first string value. This example shows
# multiple parameters being included in the generated class name:
return "%s_%s_%s%s" %(
cls.__name__,
num,
parameterized.to_safe_name(params_dict['a']),
parameterized.to_safe_name(params_dict['b']),
)
@parameterized_class([
{ "a": "hello", "b": " world!", "expected": "hello world!" },
{ "a": "say ", "b": " cheese :)", "expected": "say cheese :)" },
], class_name_func=get_class_name)
class TestConcatenation(TestCase):
def test_concat(self):
self.assertEqual(self.a + self.b, self.expected)
::
$ nosetests -v test_math.py
test_concat (test_concat.TestConcatenation_0_hello_world_) ... ok
test_concat (test_concat.TestConcatenation_0_say_cheese__) ... ok
Using with Single Parameters ............................
If a test function only accepts one parameter and the value is not iterable, then it is possible to supply a list of values without wrapping each one in a tuple:
.. code:: python
@parameterized([1, 2, 3]) def test_greater_than_zero(value): assert value > 0
Note, however, that if the single parameter is iterable (such as a list or
tuple), then it must be wrapped in a tuple, list, or the param(...)
helper:
.. code:: python
@parameterized([ ([1, 2, 3], ), ([3, 3], ), ([6], ), ]) def test_sums_to_6(numbers): assert sum(numbers) == 6
(note, also, that Python requires single element tuples to be defined with a
trailing comma: (foo, )
)
Using with @mock.patch
..........................
parameterized
can be used with mock.patch
, but the argument ordering
can be confusing. The @mock.patch(...)
decorator must come below the
@parameterized(...)
, and the mocked parameters must come last:
.. code:: python
@mock.patch("os.getpid") class TestOS(object): @parameterized(...) @mock.patch("os.fdopen") @mock.patch("os.umask") def test_method(self, param1, param2, ..., mock_umask, mock_fdopen, mock_getpid): ...
Note: the same holds true when using @parameterized.expand
.
nose-parameterized
to parameterized
To migrate a codebase from nose-parameterized
to parameterized
:
Update your requirements file, replacing nose-parameterized
with
parameterized
.
Replace all references to nose_parameterized
with parameterized
::
$ perl -pi -e 's/nose_parameterized/parameterized/g' your-codebase/
You're done!
What happened to Python 2.X, 3.5, and 3.6 support?
As of version 0.9.0, parameterized
no longer supports Python 2.X, 3.5,
or 3.6. Previous versions of parameterized
- 0.8.1 being the latest -
will continue to work, but will not receive any new features or bug fixes.
What do you mean when you say "nose is best supported"?
There are small caveates with py.test
and unittest
: py.test
does not show the parameter values (ex, it will show test_add[0]
instead of test_add[1, 2, 3]
), and unittest
/unittest2
do not
support test generators so @parameterized.expand
must be used.
Why not use @pytest.mark.parametrize
?
Because spelling is difficult. Also, parameterized
doesn't require you
to repeat argument names, and (using param
) it supports optional
keyword arguments.
Why do I get an AttributeError: 'function' object has no attribute 'expand'
with @parameterized.expand
?
You've likely installed the parametrized
(note the missing e)
package. Use parameterized
(with the e) instead and you'll be all
set.
What happened to nose-parameterized
?
Originally only nose was supported. But now everything is supported, and it
only made sense to change the name!