{
    "info": {
        "author": "Antti Kaihola",
        "author_email": "antti dot kaihola at eniram and finally fi for finland",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: BSD License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5"
        ],
        "description": "Multi-dimensional parameterized testing with Pytest\n===================================================\n\n.. image:: https://travis-ci.org/akaihola/testdimensions.svg?branch=master\n    :target: https://travis-ci.org/akaihola/testdimensions\n\nThere are multiple ways to write parameterized tests in Python. Unittest has\nsome support these days, Nose allows yielding test cases, Pytest has built-in\nparameterization support, and the excellent nose_parameterized_ package enhances\nthese capabilities in most test frameworks.\n\n``testdimensions`` provides a convenient way to write multi-dimensional test\nmatrices in some simple scenarios. If your function accepts multiple arguments\nand you want to test a cross product set of parameter combinations,\n``testdimensions`` is for you.\n\nSpecify your tests as a table whose:\n\n- Y axis labels are values for the third-last parameter\n- X axis labels are values for the second-last paremeter\n- cell values are the expected values (last parameter)\n- columns are separated by two spaces\n  (make sure this is true on all rows)\n\n.. code:: python\n\n   # test_math.py\n   @pytest_mark_dimensions('base,exponent,expected', '''\n       # y: base\n       # x: exponent\n       # cell: expected\n\n             2    3    9\n        0    0    0    0\n        1    1    1    1\n        2    4    8  512\n   ''')\n   def test_pow(base, exponent, expected):\n       assert math.pow(base, exponent) == expected\n\n\n   @pytest_mark_dimensions('input,function,expected', '''\n                   round  math.floor  math.ceil\n       -1.5         -2.0        -2.0       -1.0\n        1.0          1.0         1.0        1.0\n        1.6          2.0         1.0        2.0\n   ''')\n   def test_round_floor_ceil(input, function, expected):\n       assert function(input) == expected\n\nOutput::\n\n    $ pytest -v\n    =========================== test session starts ===============================\n    platform linux -- Python 3.5.2, pytest-3.0.3, py-1.4.31, pluggy-0.4.0\n    collected 18 items\n\n    test_math.py::test_pow[0-2-0] PASSED\n    test_math.py::test_pow[0-3-0] PASSED\n    test_math.py::test_pow[0-9-0] PASSED\n    test_math.py::test_pow[1-2-1] PASSED\n    test_math.py::test_pow[1-3-1] PASSED\n    test_math.py::test_pow[1-9-1] PASSED\n    test_math.py::test_pow[2-2-4] PASSED\n    test_math.py::test_pow[2-3-8] PASSED\n    test_math.py::test_pow[2-9-512] PASSED\n    test_math.py::test_round_floor_ceil[-1.5-function0--2.0] PASSED\n    test_math.py::test_round_floor_ceil[-1.5-function1--2.0] PASSED\n    test_math.py::test_round_floor_ceil[-1.5-function2--1.0] PASSED\n    test_math.py::test_round_floor_ceil[1.0-function3-1.0] PASSED\n    test_math.py::test_round_floor_ceil[1.0-function4-1.0] PASSED\n    test_math.py::test_round_floor_ceil[1.0-function5-1.0] PASSED\n    test_math.py::test_round_floor_ceil[1.6-function6-2.0] PASSED\n    test_math.py::test_round_floor_ceil[1.6-function7-1.0] PASSED\n    test_math.py::test_round_floor_ceil[1.6-function8-2.0] PASSED\n\n    ============================ 18 passed in 0.03 seconds ========================\n\nInstallation\n------------\n\n::\n\n    $ pip install testdimensions\n\n\nCompatibility\n-------------\n\n.. list-table::\n   :header-rows: 1\n   :stub-columns: 1\n\n   * -\n     - Py2.6\n     - Py2.7\n     - Py3.3\n     - Py3.4\n     - Py3.5\n     - PyPy\n   * - nose\n     - no\n     - yes\n     - no\n     - no\n     - yes\n     - no\n   * - nose2\n     - no\n     - no\n     - no\n     - no\n     - no\n     - no\n   * - py.test\n     - not tested\n     - yes\n     - not tested\n     - not tested\n     - yes\n     - not tested\n   * - unittest\n     - no\n     - no\n     - no\n     - no\n     - no\n     - no\n   * - unittest2\n     - no\n     - no\n     - no\n     - no\n     - no\n     - no\n\nDependencies\n------------\n\n- nose_parameterized_ for Nose support\n\n\nExhaustive Usage Examples\n--------------------------\n\nThe ``@pytest_mark_dimensions`` decorator is an extension of\n``@pytest.mark.parametrize`` and requires a comma-separated list of test\nparameters as its first argument. The second argument is a multi-line string\nwhich defines the actual tests. You can also inject values into the test\nglobals namespace using keyword arguments.\n\nTo create higher than two-dimensional tests, just define multiple tables\ninterspersed with values for the additional parameters.\n\n.. code:: python\n\n   @pytest_mark_dimensions('a,b,expected', '''\n               -10   0   9  million\n       -9      -19  -9   0   999991\n        0      -10   0   9  million\n       10        0  10  19  1000010\n       ''',\n       million=1000000)\n   def test_add(a, b, expected):\n       assert a + b == expected\n\n\n   @pytest_mark_dimensions('operation,a,b,expected', '''\n       operation = operator.sub\n\n               -10   0    9   million\n       -9        1  -9  -18  -1000009\n        0       10   0   -9  -million\n       10       20  10    1   -999990\n\n       operation = operator.add\n\n               -10   0   9  million\n       -9      -19  -9   0   999991\n        0      -10   0   9  million\n       10        0  10  19  1000010\n\n       operation = operator.mul\n\n               -10   0    9   million\n       -9       90   0  -81  -9000000\n        0        0   0    0         0\n       10     -100   0   90  10000000\n\n       ''',\n       million=1000000)\n   def test_arithmetic_operations(operation, a, b, expected):\n       assert operation(a, b) == expected\n\nFor Nose support, you need to install nose_parameterized_ and use the\n``@nosedimensions`` decorator:\n\n.. code:: python\n\n   @nosedimensions('a,b,expected', '''\n               -10   0   9  million\n       -9      -19  -9   0   999991\n        0      -10   0   9  million\n       10        0  10  19  1000010\n       ''',\n       million=1000000)\n   def test_add(a, b, expected):\n       assert a + b == expected\n\n\n   @nosedimensions('operation,a,b,expected', '''\n       operation = operator.sub\n\n               -10   0    9   million\n       -9        1  -9  -18  -1000009\n        0       10   0   -9  -million\n       10       20  10    1   -999990\n\n       operation = operator.add\n\n               -10   0   9  million\n       -9      -19  -9   0   999991\n        0      -10   0   9  million\n       10        0  10  19  1000010\n\n       operation = operator.mul\n\n               -10   0    9   million\n       -9       90   0  -81  -9000000\n        0        0   0    0         0\n       10     -100   0   90  10000000\n\n       ''',\n       million=1000000)\n   def test_arithmetic_operations(operation, a, b, expected):\n       assert operation(a, b) == expected\n\nNote that you still need to enumerate the test parameters just like with Pytest.\n\n.. _nose_parameterized: https://pypi.org/project/nose-parameterized/",
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