all
allpairspy
pypi i allpairspy
all

allpairspy

A python library for test combinations generator. The generator allows one to create a set of tests using "pairwise combinations" method, reducing a number of combinations of variables into a lesser set that covers most situations.

by Tsuyoshi Hombashi

2.5.0 (see all)License:MIT License
pypi i allpairspy
Readme

.. contents:: allpairspy forked from bayandin/allpairs <https://github.com/bayandin/allpairs>__ :backlinks: top :depth: 2

.. image:: https://badge.fury.io/py/allpairspy.svg :target: https://badge.fury.io/py/allpairspy :alt: PyPI package version

.. image:: https://img.shields.io/pypi/pyversions/allpairspy.svg :target: https://pypi.org/project/allpairspy :alt: Supported Python versions

.. image:: https://img.shields.io/travis/thombashi/allpairspy/master.svg?label=Linux/macOS%20CI :target: https://travis-ci.org/thombashi/allpairspy :alt: Linux/macOS CI status

.. image:: https://img.shields.io/appveyor/ci/thombashi/allpairspy/master.svg?label=Windows%20CI :target: https://ci.appveyor.com/project/thombashi/allpairspy :alt: Windows CI status

.. image:: https://coveralls.io/repos/github/thombashi/allpairspy/badge.svg?branch=master :target: https://coveralls.io/github/thombashi/allpairspy?branch=master :alt: Test coverage

AllPairs test combinations generator

AllPairs is an open source test combinations generator written in Python, developed and maintained by MetaCommunications Engineering. The generator allows one to create a set of tests using "pairwise combinations" method, reducing a number of combinations of variables into a lesser set that covers most situations.

For more info on pairwise testing see http://www.pairwise.org.

Features

  • Produces good enough dataset.
  • Pythonic, iterator-style enumeration interface.
  • Allows to filter out "invalid" combinations during search for the next combination.
  • Goes beyond pairs! If/when required can generate n-wise combinations.

Get Started

Basic Usage

:Sample Code: .. code:: python

    from allpairspy import AllPairs

    parameters = [
        ["Brand X", "Brand Y"],
        ["98", "NT", "2000", "XP"],
        ["Internal", "Modem"],
        ["Salaried", "Hourly", "Part-Time", "Contr."],
        [6, 10, 15, 30, 60],
    ]

    print("PAIRWISE:")
    for i, pairs in enumerate(AllPairs(parameters)):
        print("{:2d}: {}".format(i, pairs))

:Output: .. code::

    PAIRWISE:
     0: ['Brand X', '98', 'Internal', 'Salaried', 6]
     1: ['Brand Y', 'NT', 'Modem', 'Hourly', 6]
     2: ['Brand Y', '2000', 'Internal', 'Part-Time', 10]
     3: ['Brand X', 'XP', 'Modem', 'Contr.', 10]
     4: ['Brand X', '2000', 'Modem', 'Part-Time', 15]
     5: ['Brand Y', 'XP', 'Internal', 'Hourly', 15]
     6: ['Brand Y', '98', 'Modem', 'Salaried', 30]
     7: ['Brand X', 'NT', 'Internal', 'Contr.', 30]
     8: ['Brand X', '98', 'Internal', 'Hourly', 60]
     9: ['Brand Y', '2000', 'Modem', 'Contr.', 60]
    10: ['Brand Y', 'NT', 'Modem', 'Salaried', 60]
    11: ['Brand Y', 'XP', 'Modem', 'Part-Time', 60]
    12: ['Brand Y', '2000', 'Modem', 'Hourly', 30]
    13: ['Brand Y', '98', 'Modem', 'Contr.', 15]
    14: ['Brand Y', 'XP', 'Modem', 'Salaried', 15]
    15: ['Brand Y', 'NT', 'Modem', 'Part-Time', 15]
    16: ['Brand Y', 'XP', 'Modem', 'Part-Time', 30]
    17: ['Brand Y', '98', 'Modem', 'Part-Time', 6]
    18: ['Brand Y', '2000', 'Modem', 'Salaried', 6]
    19: ['Brand Y', '98', 'Modem', 'Salaried', 10]
    20: ['Brand Y', 'XP', 'Modem', 'Contr.', 6]
    21: ['Brand Y', 'NT', 'Modem', 'Hourly', 10]

Filtering

You can restrict pairs by setting filtering function to filter_func at AllPairs constructor.

:Sample Code: .. code:: python

    from allpairspy import AllPairs

    def is_valid_combination(row):
        """
        This is a filtering function. Filtering functions should return True
        if combination is valid and False otherwise.

        Test row that is passed here can be incomplete.
        To prevent search for unnecessary items filtering function
        is executed with found subset of data to validate it.
        """

        n = len(row)

        if n > 1:
            # Brand Y does not support Windows 98
            if "98" == row[1] and "Brand Y" == row[0]:
                return False

            # Brand X does not work with XP
            if "XP" == row[1] and "Brand X" == row[0]:
                return False

        if n > 4:
            # Contractors are billed in 30 min increments
            if "Contr." == row[3] and row[4] < 30:
                return False

        return True

    parameters = [
        ["Brand X", "Brand Y"],
        ["98", "NT", "2000", "XP"],
        ["Internal", "Modem"],
        ["Salaried", "Hourly", "Part-Time", "Contr."],
        [6, 10, 15, 30, 60]
    ]

    print("PAIRWISE:")
    for i, pairs in enumerate(AllPairs(parameters, filter_func=is_valid_combination)):
        print("{:2d}: {}".format(i, pairs))

:Output: .. code::

    PAIRWISE:
     0: ['Brand X', '98', 'Internal', 'Salaried', 6]
     1: ['Brand Y', 'NT', 'Modem', 'Hourly', 6]
     2: ['Brand Y', '2000', 'Internal', 'Part-Time', 10]
     3: ['Brand X', '2000', 'Modem', 'Contr.', 30]
     4: ['Brand X', 'NT', 'Internal', 'Contr.', 60]
     5: ['Brand Y', 'XP', 'Modem', 'Salaried', 60]
     6: ['Brand X', '98', 'Modem', 'Part-Time', 15]
     7: ['Brand Y', 'XP', 'Internal', 'Hourly', 15]
     8: ['Brand Y', 'NT', 'Internal', 'Part-Time', 30]
     9: ['Brand X', '2000', 'Modem', 'Hourly', 10]
    10: ['Brand Y', 'XP', 'Modem', 'Contr.', 30]
    11: ['Brand Y', '2000', 'Modem', 'Salaried', 15]
    12: ['Brand Y', 'NT', 'Modem', 'Salaried', 10]
    13: ['Brand Y', 'XP', 'Modem', 'Part-Time', 6]
    14: ['Brand Y', '2000', 'Modem', 'Contr.', 60]

OrderedDict

You can use collections.OrderedDict instance as an argument for AllPairs constructor. Pairs returned as collections.namedtuple instances.

:Sample Code: .. code:: python

    from collections import OrderedDict
    from allpairspy import AllPairs

    parameters = OrderedDict({
        "brand": ["Brand X", "Brand Y"],
        "os": ["98", "NT", "2000", "XP"],
        "minute": [15, 30, 60],
    })

    print("PAIRWISE:")
    for i, pairs in enumerate(AllPairs(parameters)):
        print("{:2d}: {}".format(i, pairs))

:Sample Code: .. code::

    PAIRWISE:
     0: Pairs(brand='Brand X', os='98', minute=15)
     1: Pairs(brand='Brand Y', os='NT', minute=15)
     2: Pairs(brand='Brand Y', os='2000', minute=30)
     3: Pairs(brand='Brand X', os='XP', minute=30)
     4: Pairs(brand='Brand X', os='2000', minute=60)
     5: Pairs(brand='Brand Y', os='XP', minute=60)
     6: Pairs(brand='Brand Y', os='98', minute=60)
     7: Pairs(brand='Brand X', os='NT', minute=60)
     8: Pairs(brand='Brand X', os='NT', minute=30)
     9: Pairs(brand='Brand X', os='98', minute=30)
    10: Pairs(brand='Brand X', os='XP', minute=15)
    11: Pairs(brand='Brand X', os='2000', minute=15)

Parameterized testing with pairwise by using py.test

:Sample Code: .. code:: python

    import pytest
    from allpairspy import AllPairs

    def function_to_be_tested(brand, operating_system, minute):
        # do something
        return True

    class TestParameterized(object):

        @pytest.mark.parametrize(["brand", "operating_system", "minute"], [
            value_list for value_list in AllPairs([
                ["Brand X", "Brand Y"],
                ["98", "NT", "2000", "XP"],
                [10, 15, 30, 60]
            ])
        ])
        def test(self, brand, operating_system, minute):
            assert function_to_be_tested(brand, operating_system, minute)

:Output: .. code::

    $ py.test test_parameterize.py -v
    ============================= test session starts ==============================
    ...
    collected 16 items

    test_parameterize.py::TestParameterized::test[Brand X-98-10] PASSED      [  6%]
    test_parameterize.py::TestParameterized::test[Brand Y-NT-10] PASSED      [ 12%]
    test_parameterize.py::TestParameterized::test[Brand Y-2000-15] PASSED    [ 18%]
    test_parameterize.py::TestParameterized::test[Brand X-XP-15] PASSED      [ 25%]
    test_parameterize.py::TestParameterized::test[Brand X-2000-30] PASSED    [ 31%]
    test_parameterize.py::TestParameterized::test[Brand Y-XP-30] PASSED      [ 37%]
    test_parameterize.py::TestParameterized::test[Brand Y-98-60] PASSED      [ 43%]
    test_parameterize.py::TestParameterized::test[Brand X-NT-60] PASSED      [ 50%]
    test_parameterize.py::TestParameterized::test[Brand X-NT-30] PASSED      [ 56%]
    test_parameterize.py::TestParameterized::test[Brand X-98-30] PASSED      [ 62%]
    test_parameterize.py::TestParameterized::test[Brand X-XP-60] PASSED      [ 68%]
    test_parameterize.py::TestParameterized::test[Brand X-2000-60] PASSED    [ 75%]
    test_parameterize.py::TestParameterized::test[Brand X-2000-10] PASSED    [ 81%]
    test_parameterize.py::TestParameterized::test[Brand X-XP-10] PASSED      [ 87%]
    test_parameterize.py::TestParameterized::test[Brand X-98-15] PASSED      [ 93%]
    test_parameterize.py::TestParameterized::test[Brand X-NT-15] PASSED      [100%]

Other Examples

Other examples could be found in examples <https://github.com/thombashi/allpairspy/tree/master/examples>__ directory.

Installation

Install from PyPI

::

pip install allpairspy

Install from PPA (for Ubuntu)

::

sudo add-apt-repository ppa:thombashi/ppa
sudo apt update
sudo apt install python3-allpairspy

Known issues

  • Not optimal - there are tools that can create smaller set covering all the pairs. However, they are missing some other important features and/or do not integrate well with Python.

  • Lousy written filtering function may lead to full permutation of parameters.

  • Version 2.0 has become slower (a side-effect of introducing ability to produce n-wise combinations).

Dependencies

Python 2.7+ or 3.5+

  • six <https://pypi.org/project/six/>__

GitHub Stars

165

LAST COMMIT

1yr ago

MAINTAINERS

1

CONTRIBUTORS

5

OPEN ISSUES

2

OPEN PRs

0
VersionTagPublished
2.5.0
3yrs ago
2.4.3
4yrs ago
2.4.2
4yrs ago
2.4.1
4yrs ago
No alternatives found
No tutorials found
Add a tutorial