How do you generate dynamic (parameterized) unit tests in Python?

This is called "parametrization".

There are several tools that support this approach. E.g.:

• pytest's decorator
• parameterized

The resulting code looks like this:

from parameterized import parameterized

class TestSequence(unittest.TestCase):
    @parameterized.expand([
        ["foo", "a", "a",],
        ["bar", "a", "b"],
        ["lee", "b", "b"],
    ])
    def test_sequence(self, name, a, b):
        self.assertEqual(a,b)

Which will generate the tests:

test_sequence_0_foo (__main__.TestSequence) ... ok
test_sequence_1_bar (__main__.TestSequence) ... FAIL
test_sequence_2_lee (__main__.TestSequence) ... ok

======================================================================
FAIL: test_sequence_1_bar (__main__.TestSequence)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/local/lib/python2.7/site-packages/parameterized/parameterized.py", line 233, in <lambda>
    standalone_func = lambda *a: func(*(a + p.args), **p.kwargs)
  File "x.py", line 12, in test_sequence
    self.assertEqual(a,b)
AssertionError: 'a' != 'b'

For historical reasons I'll leave the original answer circa 2008):

I use something like this:

import unittest

l = [["foo", "a", "a",], ["bar", "a", "b"], ["lee", "b", "b"]]

class TestSequense(unittest.TestCase):
    pass

def test_generator(a, b):
    def test(self):
        self.assertEqual(a,b)
    return test

if __name__ == '__main__':
    for t in l:
        test_name = 'test_%s' % t[0]
        test = test_generator(t[1], t[2])
        setattr(TestSequense, test_name, test)
    unittest.main()

Using unittest (since 3.4)

Since Python 3.4, the standard library unittest package has the subTest context manager.

See the documentation:

• 26.4.7. Distinguishing test iterations using subtests
• subTest

Example:

from unittest import TestCase

param_list = [('a', 'a'), ('a', 'b'), ('b', 'b')]

class TestDemonstrateSubtest(TestCase):
    def test_works_as_expected(self):
        for p1, p2 in param_list:
            with self.subTest():
                self.assertEqual(p1, p2)

You can also specify a custom message and parameter values to subTest():

with self.subTest(msg="Checking if p1 equals p2", p1=p1, p2=p2):

Using nose

The nose testing framework supports this.

Example (the code below is the entire contents of the file containing the test):

param_list = [('a', 'a'), ('a', 'b'), ('b', 'b')]

def test_generator():
    for params in param_list:
        yield check_em, params[0], params[1]

def check_em(a, b):
    assert a == b

The output of the nosetests command:

> nosetests -v
testgen.test_generator('a', 'a') ... ok
testgen.test_generator('a', 'b') ... FAIL
testgen.test_generator('b', 'b') ... ok

======================================================================
FAIL: testgen.test_generator('a', 'b')
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.5/site-packages/nose-0.10.1-py2.5.egg/nose/case.py", line 203, in runTest
    self.test(*self.arg)
  File "testgen.py", line 7, in check_em
    assert a == b
AssertionError

----------------------------------------------------------------------
Ran 3 tests in 0.006s

FAILED (failures=1)

This can be solved elegantly using Metaclasses:

import unittest

l = [["foo", "a", "a",], ["bar", "a", "b"], ["lee", "b", "b"]]

class TestSequenceMeta(type):
    def __new__(mcs, name, bases, dict):

        def gen_test(a, b):
            def test(self):
                self.assertEqual(a, b)
            return test

        for tname, a, b in l:
            test_name = "test_%s" % tname
            dict[test_name] = gen_test(a,b)
        return type.__new__(mcs, name, bases, dict)

class TestSequence(unittest.TestCase):
    __metaclass__ = TestSequenceMeta

if __name__ == '__main__':
    unittest.main()