pairwise的python包示例allpairspy
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))
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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] |
Filtering
You can restrict pairs by setting 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))
|
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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] |
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: |
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))
|
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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) |