feat(08): implement SSOT architecture for network configuration
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306
venv/lib/python3.12/site-packages/fuzzywuzzy/fuzz.py
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306
venv/lib/python3.12/site-packages/fuzzywuzzy/fuzz.py
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#!/usr/bin/env python
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# encoding: utf-8
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from __future__ import unicode_literals
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import platform
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import warnings
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try:
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from .StringMatcher import StringMatcher as SequenceMatcher
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except ImportError:
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if platform.python_implementation() != "PyPy":
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warnings.warn('Using slow pure-python SequenceMatcher. Install python-Levenshtein to remove this warning')
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from difflib import SequenceMatcher
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from . import utils
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###########################
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# Basic Scoring Functions #
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###########################
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@utils.check_for_none
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@utils.check_for_equivalence
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@utils.check_empty_string
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def ratio(s1, s2):
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s1, s2 = utils.make_type_consistent(s1, s2)
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m = SequenceMatcher(None, s1, s2)
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return utils.intr(100 * m.ratio())
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@utils.check_for_none
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@utils.check_for_equivalence
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@utils.check_empty_string
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def partial_ratio(s1, s2):
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""""Return the ratio of the most similar substring
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as a number between 0 and 100."""
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s1, s2 = utils.make_type_consistent(s1, s2)
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if len(s1) <= len(s2):
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shorter = s1
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longer = s2
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else:
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shorter = s2
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longer = s1
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m = SequenceMatcher(None, shorter, longer)
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blocks = m.get_matching_blocks()
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# each block represents a sequence of matching characters in a string
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# of the form (idx_1, idx_2, len)
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# the best partial match will block align with at least one of those blocks
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# e.g. shorter = "abcd", longer = XXXbcdeEEE
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# block = (1,3,3)
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# best score === ratio("abcd", "Xbcd")
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scores = []
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for block in blocks:
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long_start = block[1] - block[0] if (block[1] - block[0]) > 0 else 0
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long_end = long_start + len(shorter)
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long_substr = longer[long_start:long_end]
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m2 = SequenceMatcher(None, shorter, long_substr)
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r = m2.ratio()
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if r > .995:
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return 100
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else:
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scores.append(r)
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return utils.intr(100 * max(scores))
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##############################
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# Advanced Scoring Functions #
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##############################
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def _process_and_sort(s, force_ascii, full_process=True):
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"""Return a cleaned string with token sorted."""
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# pull tokens
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ts = utils.full_process(s, force_ascii=force_ascii) if full_process else s
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tokens = ts.split()
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# sort tokens and join
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sorted_string = u" ".join(sorted(tokens))
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return sorted_string.strip()
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# Sorted Token
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# find all alphanumeric tokens in the string
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# sort those tokens and take ratio of resulting joined strings
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# controls for unordered string elements
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@utils.check_for_none
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def _token_sort(s1, s2, partial=True, force_ascii=True, full_process=True):
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sorted1 = _process_and_sort(s1, force_ascii, full_process=full_process)
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sorted2 = _process_and_sort(s2, force_ascii, full_process=full_process)
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if partial:
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return partial_ratio(sorted1, sorted2)
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else:
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return ratio(sorted1, sorted2)
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def token_sort_ratio(s1, s2, force_ascii=True, full_process=True):
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"""Return a measure of the sequences' similarity between 0 and 100
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but sorting the token before comparing.
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"""
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return _token_sort(s1, s2, partial=False, force_ascii=force_ascii, full_process=full_process)
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def partial_token_sort_ratio(s1, s2, force_ascii=True, full_process=True):
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"""Return the ratio of the most similar substring as a number between
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0 and 100 but sorting the token before comparing.
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"""
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return _token_sort(s1, s2, partial=True, force_ascii=force_ascii, full_process=full_process)
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@utils.check_for_none
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def _token_set(s1, s2, partial=True, force_ascii=True, full_process=True):
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"""Find all alphanumeric tokens in each string...
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- treat them as a set
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- construct two strings of the form:
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<sorted_intersection><sorted_remainder>
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- take ratios of those two strings
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- controls for unordered partial matches"""
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if not full_process and s1 == s2:
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return 100
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p1 = utils.full_process(s1, force_ascii=force_ascii) if full_process else s1
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p2 = utils.full_process(s2, force_ascii=force_ascii) if full_process else s2
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if not utils.validate_string(p1):
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return 0
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if not utils.validate_string(p2):
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return 0
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# pull tokens
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tokens1 = set(p1.split())
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tokens2 = set(p2.split())
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intersection = tokens1.intersection(tokens2)
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diff1to2 = tokens1.difference(tokens2)
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diff2to1 = tokens2.difference(tokens1)
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sorted_sect = " ".join(sorted(intersection))
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sorted_1to2 = " ".join(sorted(diff1to2))
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sorted_2to1 = " ".join(sorted(diff2to1))
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combined_1to2 = sorted_sect + " " + sorted_1to2
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combined_2to1 = sorted_sect + " " + sorted_2to1
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# strip
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sorted_sect = sorted_sect.strip()
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combined_1to2 = combined_1to2.strip()
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combined_2to1 = combined_2to1.strip()
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if partial:
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ratio_func = partial_ratio
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else:
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ratio_func = ratio
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pairwise = [
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ratio_func(sorted_sect, combined_1to2),
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ratio_func(sorted_sect, combined_2to1),
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ratio_func(combined_1to2, combined_2to1)
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]
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return max(pairwise)
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def token_set_ratio(s1, s2, force_ascii=True, full_process=True):
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return _token_set(s1, s2, partial=False, force_ascii=force_ascii, full_process=full_process)
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def partial_token_set_ratio(s1, s2, force_ascii=True, full_process=True):
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return _token_set(s1, s2, partial=True, force_ascii=force_ascii, full_process=full_process)
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###################
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# Combination API #
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###################
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# q is for quick
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def QRatio(s1, s2, force_ascii=True, full_process=True):
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"""
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Quick ratio comparison between two strings.
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Runs full_process from utils on both strings
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Short circuits if either of the strings is empty after processing.
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:param s1:
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:param s2:
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:param force_ascii: Allow only ASCII characters (Default: True)
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:full_process: Process inputs, used here to avoid double processing in extract functions (Default: True)
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:return: similarity ratio
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"""
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if full_process:
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p1 = utils.full_process(s1, force_ascii=force_ascii)
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p2 = utils.full_process(s2, force_ascii=force_ascii)
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else:
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p1 = s1
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p2 = s2
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if not utils.validate_string(p1):
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return 0
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if not utils.validate_string(p2):
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return 0
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return ratio(p1, p2)
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def UQRatio(s1, s2, full_process=True):
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"""
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Unicode quick ratio
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Calls QRatio with force_ascii set to False
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:param s1:
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:param s2:
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:return: similarity ratio
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"""
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return QRatio(s1, s2, force_ascii=False, full_process=full_process)
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# w is for weighted
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def WRatio(s1, s2, force_ascii=True, full_process=True):
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"""
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Return a measure of the sequences' similarity between 0 and 100, using different algorithms.
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**Steps in the order they occur**
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#. Run full_process from utils on both strings
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#. Short circuit if this makes either string empty
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#. Take the ratio of the two processed strings (fuzz.ratio)
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#. Run checks to compare the length of the strings
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* If one of the strings is more than 1.5 times as long as the other
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use partial_ratio comparisons - scale partial results by 0.9
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(this makes sure only full results can return 100)
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* If one of the strings is over 8 times as long as the other
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instead scale by 0.6
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#. Run the other ratio functions
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* if using partial ratio functions call partial_ratio,
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partial_token_sort_ratio and partial_token_set_ratio
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scale all of these by the ratio based on length
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* otherwise call token_sort_ratio and token_set_ratio
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* all token based comparisons are scaled by 0.95
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(on top of any partial scalars)
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#. Take the highest value from these results
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round it and return it as an integer.
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:param s1:
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:param s2:
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:param force_ascii: Allow only ascii characters
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:type force_ascii: bool
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:full_process: Process inputs, used here to avoid double processing in extract functions (Default: True)
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:return:
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"""
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if full_process:
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p1 = utils.full_process(s1, force_ascii=force_ascii)
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p2 = utils.full_process(s2, force_ascii=force_ascii)
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else:
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p1 = s1
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p2 = s2
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if not utils.validate_string(p1):
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return 0
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if not utils.validate_string(p2):
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return 0
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# should we look at partials?
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try_partial = True
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unbase_scale = .95
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partial_scale = .90
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base = ratio(p1, p2)
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len_ratio = float(max(len(p1), len(p2))) / min(len(p1), len(p2))
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# if strings are similar length, don't use partials
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if len_ratio < 1.5:
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try_partial = False
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# if one string is much much shorter than the other
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if len_ratio > 8:
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partial_scale = .6
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if try_partial:
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partial = partial_ratio(p1, p2) * partial_scale
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ptsor = partial_token_sort_ratio(p1, p2, full_process=False) \
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* unbase_scale * partial_scale
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ptser = partial_token_set_ratio(p1, p2, full_process=False) \
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* unbase_scale * partial_scale
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return utils.intr(max(base, partial, ptsor, ptser))
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else:
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tsor = token_sort_ratio(p1, p2, full_process=False) * unbase_scale
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tser = token_set_ratio(p1, p2, full_process=False) * unbase_scale
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return utils.intr(max(base, tsor, tser))
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def UWRatio(s1, s2, full_process=True):
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"""Return a measure of the sequences' similarity between 0 and 100,
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using different algorithms. Same as WRatio but preserving unicode.
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"""
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return WRatio(s1, s2, force_ascii=False, full_process=full_process)
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