Metadata-Version: 2.1 Name: allpairspy Version: 2.5.1 Summary: Pairwise test combinations generator Home-page: https://github.com/thombashi/allpairspy Author: MetaCommunications Engineering Author-email: metacomm@users.sourceforge.net Maintainer: Tsuyoshi Hombashi Maintainer-email: tsuyoshi.hombashi@gmail.com License: MIT License Project-URL: Source, https://github.com/thombashi/allpairspy Project-URL: Tracker, https://github.com/thombashi/allpairspy/issues Classifier: Development Status :: 5 - Production/Stable Classifier: Environment :: Console Classifier: Intended Audience :: Developers Classifier: Intended Audience :: Information Technology Classifier: Intended Audience :: System Administrators Classifier: License :: OSI Approved :: MIT License Classifier: Natural Language :: English Classifier: Operating System :: OS Independent Classifier: Programming Language :: Python Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3.7 Classifier: Programming Language :: Python :: 3.8 Classifier: Programming Language :: Python :: 3.9 Classifier: Programming Language :: Python :: 3.10 Classifier: Programming Language :: Python :: 3.11 Classifier: Programming Language :: Python :: 3 :: Only Classifier: Programming Language :: Python :: Implementation :: CPython Classifier: Programming Language :: Python :: Implementation :: PyPy Classifier: Topic :: Software Development :: Libraries Classifier: Topic :: Software Development :: Libraries :: Python Modules Classifier: Topic :: Software Development :: Testing Classifier: Topic :: Utilities Requires-Python: >=3.7 Description-Content-Type: text/x-rst License-File: LICENSE.txt Provides-Extra: test Requires-Dist: pytest (>=6.0.1) ; extra == 'test' Requires-Dist: pytest-md-report (>=0.3) ; extra == 'test' .. contents:: **allpairspy** forked from `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://github.com/thombashi/allpairspy/workflows/Tests/badge.svg :target: https://github.com/thombashi/allpairspy/actions?query=workflow%3ATests :alt: Linux/macOS/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 a 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] Data Source: OrderedDict ==================================== You can use ``collections.OrderedDict`` instance as an argument for ``AllPairs`` constructor. Pairs will be 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 pairwise by using pytest ==================================================================== Parameterized testing: value matrix ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :Sample Code: .. code:: python import pytest from allpairspy import AllPairs def function_to_be_tested(brand, operating_system, minute) -> bool: # do something return True class TestParameterized(object): @pytest.mark.parametrize(["brand", "operating_system", "minute"], [ values for values 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%] Parameterized testing: OrderedDict ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :Sample Code: .. code:: python import pytest from allpairspy import AllPairs def function_to_be_tested(brand, operating_system, minute) -> bool: # do something return True class TestParameterized(object): @pytest.mark.parametrize( ["pair"], [ [pair] for pair in AllPairs( OrderedDict( { "brand": ["Brand X", "Brand Y"], "operating_system": ["98", "NT", "2000", "XP"], "minute": [10, 15, 30, 60], } ) ) ], ) def test(self, pair): assert function_to_be_tested(pair.brand, pair.operating_system, pair.minute) Other Examples ================= Other examples could be found in `examples `__ directory. Installation ------------ Installation: pip ================================== :: pip install allpairspy Installation: apt ================================== You can install the package by ``apt`` via a Personal Package Archive (`PPA `__): :: 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 3.7+ no external dependencies. 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