Parameterized testing with any Python test framework
====================================================

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    :alt: PyPI
    :target: https://pypi.org/project/parameterized/

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    :alt: Circle CI
    :target: https://circleci.com/gh/wolever/parameterized


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

   # test_math.py
   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)


Installation
------------

::

    $ pip install parameterized


Compatibility
-------------

`Yes`__ (mostly).

__ https://travis-ci.org/wolever/parameterized

.. list-table::
   :header-rows: 1
   :stub-columns: 1

   * -
     - Py2.6
     - Py2.7
     - Py3.4
     - Py3.5
     - Py3.6
     - Py3.7
     - Py3.8
     - Py3.9
     - PyPy
     - ``@mock.patch``
   * - nose
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
   * - nose2
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
   * - py.test 2
     - yes
     - yes
     - no*
     - no*
     - no*
     - no*
     - yes
     - yes
     - yes
     - yes
   * - py.test 3
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
   * - py.test 4
     - no**
     - no**
     - no**
     - no**
     - no**
     - no**
     - no**
     - no**
     - no**
     - no**
   * - py.test fixtures
     - no†
     - no†
     - no†
     - no†
     - no†
     - no†
     - no†
     - no†
     - no†
     - no†
   * - | unittest
       | (``@parameterized.expand``)
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
   * - | unittest2
       | (``@parameterized.expand``)
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes
     - yes

\*: py.test 2 does `does not appear to work (#71)`__ under Python 3. Please comment on the related issues if you are affected.

\*\*: 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/34
__ https://github.com/wolever/parameterized/issues/81

Dependencies
------------

(this section left intentionally blank)


Exhaustive Usage Examples
--------------------------

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", 2, 3, 5),
        ])
        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``.


Migrating from ``nose-parameterized`` to ``parameterized``
----------------------------------------------------------

To migrate a codebase from ``nose-parameterized`` to ``parameterized``:

1. Update your requirements file, replacing ``nose-parameterized`` with
   ``parameterized``.

2. Replace all references to ``nose_parameterized`` with ``parameterized``::

    $ perl -pi -e 's/nose_parameterized/parameterized/g' your-codebase/

3. You're done!


FAQ
---

What happened to ``nose-parameterized``?
    Originally only nose was supported. But now everything is supported, and it
    only made sense to change the name!

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.