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f070e90347
--HG-- extra : convert_revision : svn%3Ac306627e-7827-47d3-bdf0-9a457c9553a1/trunk%40225
110 lines
4.8 KiB
Python
110 lines
4.8 KiB
Python
# Created By: Virgil Dupras
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# Created On: 2006/03/03
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# $Id$
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# Copyright 2009 Hardcoded Software (http://www.hardcoded.net)
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#
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# This software is licensed under the "HS" License as described in the "LICENSE" file,
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# which should be included with this package. The terms are also available at
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# http://www.hardcoded.net/licenses/hs_license
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import logging
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from hsutil import job, io
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from hsutil.misc import dedupe
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from hsutil.str import get_file_ext, rem_file_ext
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from . import engine
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from .ignore import IgnoreList
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(SCAN_TYPE_FILENAME,
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SCAN_TYPE_FIELDS,
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SCAN_TYPE_FIELDS_NO_ORDER,
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SCAN_TYPE_TAG,
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UNUSED, # Must not be removed. Constants here are what scan_type in the prefs are.
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SCAN_TYPE_CONTENT,
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SCAN_TYPE_CONTENT_AUDIO) = range(7)
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SCANNABLE_TAGS = ['track', 'artist', 'album', 'title', 'genre', 'year']
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class Scanner(object):
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def __init__(self):
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self.ignore_list = IgnoreList()
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self.discarded_file_count = 0
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def _getmatches(self, files, j):
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if self.size_threshold:
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j = j.start_subjob([2, 8])
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for f in j.iter_with_progress(files, 'Read size of %d/%d files'):
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f.size # pre-read, makes a smoother progress if read here (especially for bundles)
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files = [f for f in files if f.size >= self.size_threshold]
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if self.scan_type in (SCAN_TYPE_CONTENT, SCAN_TYPE_CONTENT_AUDIO):
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sizeattr = 'size' if self.scan_type == SCAN_TYPE_CONTENT else 'audiosize'
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return engine.getmatches_by_contents(files, sizeattr, partial=self.scan_type==SCAN_TYPE_CONTENT_AUDIO, j=j)
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else:
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j = j.start_subjob([2, 8])
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kw = {}
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kw['match_similar_words'] = self.match_similar_words
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kw['weight_words'] = self.word_weighting
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kw['min_match_percentage'] = self.min_match_percentage
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if self.scan_type == SCAN_TYPE_FIELDS_NO_ORDER:
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self.scan_type = SCAN_TYPE_FIELDS
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kw['no_field_order'] = True
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func = {
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SCAN_TYPE_FILENAME: lambda f: engine.getwords(rem_file_ext(f.name)),
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SCAN_TYPE_FIELDS: lambda f: engine.getfields(rem_file_ext(f.name)),
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SCAN_TYPE_TAG: lambda f: [engine.getwords(unicode(getattr(f, attrname))) for attrname in SCANNABLE_TAGS if attrname in self.scanned_tags],
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}[self.scan_type]
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for f in j.iter_with_progress(files, 'Read metadata of %d/%d files'):
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f.words = func(f)
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return engine.getmatches(files, j=j, **kw)
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@staticmethod
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def _key_func(dupe):
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return (not dupe.is_ref, -dupe.size)
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@staticmethod
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def _tie_breaker(ref, dupe):
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refname = rem_file_ext(ref.name).lower()
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dupename = rem_file_ext(dupe.name).lower()
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if 'copy' in refname and 'copy' not in dupename:
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return True
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if refname.startswith(dupename) and (refname[len(dupename):].strip().isdigit()):
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return True
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return len(dupe.path) > len(ref.path)
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def GetDupeGroups(self, files, j=job.nulljob):
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j = j.start_subjob([8, 2])
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for f in [f for f in files if not hasattr(f, 'is_ref')]:
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f.is_ref = False
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logging.info('Getting matches')
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matches = self._getmatches(files, j)
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logging.info('Found %d matches' % len(matches))
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j.set_progress(100, 'Removing false matches')
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if not self.mix_file_kind:
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matches = [m for m in matches if get_file_ext(m.first.name) == get_file_ext(m.second.name)]
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matches = [m for m in matches if io.exists(m.first.path) and io.exists(m.second.path)]
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if self.ignore_list:
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j = j.start_subjob(2)
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iter_matches = j.iter_with_progress(matches, 'Processed %d/%d matches against the ignore list')
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matches = [m for m in iter_matches
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if not self.ignore_list.AreIgnored(unicode(m.first.path), unicode(m.second.path))]
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logging.info('Grouping matches')
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groups = engine.get_groups(matches, j)
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matched_files = dedupe([m.first for m in matches] + [m.second for m in matches])
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self.discarded_file_count = len(matched_files) - sum(len(g) for g in groups)
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groups = [g for g in groups if any(not f.is_ref for f in g)]
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logging.info('Created %d groups' % len(groups))
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j.set_progress(100, 'Doing group prioritization')
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for g in groups:
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g.prioritize(self._key_func, self._tie_breaker)
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return groups
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match_similar_words = False
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min_match_percentage = 80
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mix_file_kind = True
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scan_type = SCAN_TYPE_FILENAME
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scanned_tags = set(['artist', 'title'])
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size_threshold = 0
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word_weighting = False
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