mirror of
https://github.com/SickGear/SickGear.git
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07d72e05f1
Change remove search results filtering from tv info source. Change suppress startup warnings for Fuzzywuzzy and Cheetah libs. Change show name aliases get a score -1 to give the main names priority. Change replace findCertainShow with find_show_by_id for mapped multi-indexer. Change add Trakt info source search interface. Change directly send image after it's been cached. Fix loading CachedImages images with TVDB API v2 changes.
325 lines
10 KiB
Python
325 lines
10 KiB
Python
#!/usr/bin/env python
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# encoding: utf-8
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"""
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fuzz.py
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Copyright (c) 2011 Adam Cohen
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Permission is hereby granted, free of charge, to any person obtaining
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a copy of this software and associated documentation files (the
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"Software"), to deal in the Software without restriction, including
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without limitation the rights to use, copy, modify, merge, publish,
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distribute, sublicense, and/or sell copies of the Software, and to
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permit persons to whom the Software is furnished to do so, subject to
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the following conditions:
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The above copyright notice and this permission notice shall be
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included in all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
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LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
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OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
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WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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"""
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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_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_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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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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