allpairspy forked from bayandin/allpairs
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.
- 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.
- Sample Code
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
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]
You can restrict pairs by setting a filtering function to filter_func at AllPairs constructor.
- Sample Code
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
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]
You can use collections.OrderedDict instance as an argument for AllPairs constructor. Pairs will be returned as collections.namedtuple instances.
- Sample Code
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
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)
- Sample Code
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
$ 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%]
- Sample Code
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 could be found in examples directory.
pip install allpairspyYou 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- 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).
Python 3.7+ no external dependencies.
