This is more an ease of use subclass of dict - rather then one that uses a lot of dict features.
If your requested item is in the dictionary (with a key that hashes the same) then it acts as a more or less normal dictionary.
If on the other hand you are looking for a string that is similar to a key in the dictionary, then the class iterates over all the keys and finds the one that is the closest match.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 | """Match items in a dictionary using fuzzy matching
Implemented for pywinauto.
This class uses difflib to match strings.
This class uses a linear search to find the items as it HAS to iterate over
every item in the dictionary (otherwise it would not be possible to know which
is the 'best' match).
If the exact item is in the dictionary (no fuzzy matching needed - then it
doesn't do the linear search and speed should be similar to standard Python
dictionaries.
>>> fuzzywuzzy = FuzzyDict({"hello" : "World", "Hiya" : 2, "Here you are" : 3})
>>> fuzzywuzzy['Me again'] = [1,2,3]
>>>
>>> fuzzywuzzy['Hi']
2
>>>
>>>
>>> # next one doesn't match well enough - so a key error is raised
...
>>> fuzzywuzzy['There']
Traceback (most recent call last):
File "<stdin>", line 1, in ?
File "pywinauto\fuzzydict.py", line 125, in __getitem__
raise KeyError(
KeyError: "'There'. closest match: 'hello' with ratio 0.400"
>>>
>>> fuzzywuzzy['you are']
3
>>> fuzzywuzzy['again']
[1, 2, 3]
>>>
"""
__revision__ = "$Rev$"
import difflib
class FuzzyDict(dict):
"Provides a dictionary that performs fuzzy lookup"
def __init__(self, items = None, cutoff = .6):
"""Construct a new FuzzyDict instance
items is an dictionary to copy items from (optional)
cutoff is the match ratio below which mathes should not be considered
cutoff needs to be a float between 0 and 1 (where zero is no match
and 1 is a perfect match)"""
super(FuzzyDict, self).__init__()
if items:
self.update(items)
self.cutoff = cutoff
# short wrapper around some super (dict) methods
self._dict_contains = lambda key: \
super(FuzzyDict,self).__contains__(key)
self._dict_getitem = lambda key: \
super(FuzzyDict,self).__getitem__(key)
def _search(self, lookfor, stop_on_first = False):
"""Returns the value whose key best matches lookfor
if stop_on_first is True then the method returns as soon
as it finds the first item
"""
# if the item is in the dictionary then just return it
if self._dict_contains(lookfor):
return True, lookfor, self._dict_getitem(lookfor), 1
# set up the fuzzy matching tool
ratio_calc = difflib.SequenceMatcher()
ratio_calc.set_seq1(lookfor)
# test each key in the dictionary
best_ratio = 0
best_match = None
best_key = None
for key in self:
# if the current key is not a string
# then we just skip it
try:
# set up the SequenceMatcher with other text
ratio_calc.set_seq2(key)
except TypeError:
continue
# we get an error here if the item to look for is not a
# string - if it cannot be fuzzy matched and we are here
# this it is defintely not in the dictionary
try:
# calculate the match value
ratio = ratio_calc.ratio()
except TypeError:
break
# if this is the best ratio so far - save it and the value
if ratio > best_ratio:
best_ratio = ratio
best_key = key
best_match = self._dict_getitem(key)
if stop_on_first and ratio >= self.cutoff:
break
return (
best_ratio >= self.cutoff,
best_key,
best_match,
best_ratio)
def __contains__(self, item):
"Overides Dictionary __contains__ to use fuzzy matching"
if self._search(item, True)[0]:
return True
else:
return False
def __getitem__(self, lookfor):
"Overides Dictionary __getitem__ to use fuzzy matching"
matched, key, item, ratio = self._search(lookfor)
if not matched:
raise KeyError(
"'%s'. closest match: '%s' with ratio %.3f"%
(str(lookfor), str(key), ratio))
return item
if __name__ == '__main__':
import unittest
class FuzzyTestCase(unittest.TestCase):
"Perform some tests"
test_dict = {
'Hiya' : 1,
u'hiy\xe4' : 2,
'test3' : 3,
1: 324}
def testCreation_Empty(self):
"Verify that not specifying any values creates an empty dictionary"
fd = FuzzyDict()
self.assertEquals(fd, {})
def testCreation_Dict(self):
"Test creating a fuzzy dict"
fd = FuzzyDict(self.test_dict)
self.assertEquals(fd, self.test_dict)
self.assertEquals(self.test_dict['Hiya'], fd['hiya'])
fd2 = FuzzyDict(self.test_dict, cutoff = .8)
self.assertEquals(fd, self.test_dict)
self.assertRaises(KeyError, fd2.__getitem__, 'hiya')
def testContains(self):
"Test checking if an item is in a FuzzyDict"
fd = FuzzyDict(self.test_dict)
self.assertEquals(True, fd.__contains__('hiya'))
self.assertEquals(True, fd.__contains__(u'test3'))
self.assertEquals(True, fd.__contains__(u'hiy\xe4'))
self.assertEquals(False, fd.__contains__('FuzzyWuzzy'))
self.assertEquals(True, fd.__contains__(1))
self.assertEquals(False, fd.__contains__(23))
def testGetItem(self):
"Test getting items from a FuzzyDict"
fd = FuzzyDict(self.test_dict)
self.assertEquals(self.test_dict["Hiya"], fd['hiya'])
self.assertRaises(KeyError, fd.__getitem__, 'FuzzyWuzzy')
fd2 = FuzzyDict(self.test_dict, cutoff = .14)
self.assertEquals(1, fd2['FuzzyWuzzy'])
self.assertEquals(324, fd2[1])
self.assertRaises(KeyError, fd2.__getitem__, 23)
unittest.main()
|
I already had a function that used difflib - but when doing some refactoring - I thought that the syntax used in a dictionary would match better the way I was using it.
As such it might be useful to others out there :-)
This was implemented for pywinauto https://sourceforge.net/projects/pywinauto/
High performance alternative. Hi,
If you need a similar data structure with high-performance, have a look at pytst, which includes a close_match method which is similar to this feature. pytst uses a Ternary Search Tree index and is implemented in C++, with a SWIG Python wrapper.
pytst also include high-performance algorithms for wildcard matches, prefix matches, etc.
Unfortunately, documentation is quite scarce. I'll work on it Real Soon Now.
http://nicolas.lehuen.com/index.php/Pytst
If you simply want to know the prev/next string in a sort order, the sortedcontainers module provides an API. It implements sorted list, sorted dict, and sorted set data types in pure-Python and is fast-as-C implementations (even faster!). Learn more about sortedcontainers, available on PyPI and github.
i don't understand how it works. is this the expected output? *
....
Ran 4 tests in 0.004s
OK * can somebody help me.... i really need help