• linux-64 v0.6.1
• osx-64 v0.6.1

conda install

To install this package run one of the following:
conda install quantopian::parameterized

---

Parameterized testing with any Python test framework

.. image:: https://travis-ci.org/wolever/parameterized.svg?branch=master :target: https://travis-ci.org/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

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)

With nose (and nose2)::

$ nosetests -v test_math.py
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_floor_0_negative (test_math.TestMathUnitTest) ... ok
test_floor_1_integer (test_math.TestMathUnitTest) ... ok
test_floor_2_large_fraction (test_math.TestMathUnitTest) ... ok

----------------------------------------------------------------------
Ran 7 tests in 0.002s

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 2.7.2 -- py-1.4.30 -- pytest-2.7.1
collected 7 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
test_math.py::TestMathUnitTest::test_floor_1_integer
test_math.py::TestMathUnitTest::test_floor_2_large_fraction

=========================== 7 passed in 0.10 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

----------------------------------------------------------------------
Ran 3 tests in 0.000s

OK

(note: because unittest does not support test decorators, only tests created with @parameterized.expand will be executed)

Installation

::

$ pip install parameterized

Compatibility

Yes__.

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

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

• -
  • Py2.6
  • Py2.7
  • Py3.3
  • Py3.4
  • PyPy
• • nose
  • yes
  • yes
  • yes
  • yes
  • yes
• • nose2
  • yes
  • yes
  • yes
  • yes
  • yes
• • py.test
  • yes
  • yes
  • yes
  • yes
  • yes
• • | unittest | (@parameterized.expand)
  • yes
  • yes
  • yes
  • yes
  • yes
• • | unittest2 | (@parameterized.expand)
  • yes
  • yes
  • yes
  • yes
  • yes

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 testcase_func_name 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),
    ], testcase_func_name=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

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.