189 lines
8.5 KiB
Python
189 lines
8.5 KiB
Python
# Created By: Virgil Dupras
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# Created On: 2006/03/03
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# Copyright 2013 Hardcoded Software (http://www.hardcoded.net)
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#
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# This software is licensed under the "BSD" 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/bsd_license
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import logging
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import re
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import os.path as op
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from jobprogress import job
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from hscommon.util import dedupe, rem_file_ext, get_file_ext
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from hscommon.trans import tr
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from . import engine
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from .ignore import IgnoreList
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# It's quite ugly to have scan types from all editions all put in the same class, but because there's
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# there will be some nasty bugs popping up (ScanType is used in core when in should exclusively be
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# used in core_*). One day I'll clean this up.
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class ScanType:
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Filename = 0
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Fields = 1
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FieldsNoOrder = 2
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Tag = 3
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Folders = 4
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Contents = 5
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ContentsAudio = 6
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#PE
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FuzzyBlock = 10
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ExifTimestamp = 11
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TriggerHappyMode = 12
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SCANNABLE_TAGS = ['track', 'artist', 'album', 'title', 'genre', 'year']
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RE_DIGIT_ENDING = re.compile(r'\d+|\(\d+\)|\[\d+\]|{\d+}')
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def is_same_with_digit(name, refname):
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# Returns True if name is the same as refname, but with digits (with brackets or not) at the end
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if not name.startswith(refname):
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return False
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end = name[len(refname):].strip()
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return RE_DIGIT_ENDING.match(end) is not None
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def remove_dupe_paths(files):
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# Returns files with duplicates-by-path removed. Files with the exact same path are considered
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# duplicates and only the first file to have a path is kept. In certain cases, we have files
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# that have the same path, but not with the same case, that's why we normalize. However, we also
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# have case-sensitive filesystems, and in those, we don't want to falsely remove duplicates,
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# that's why we have a `samefile` mechanism.
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result = []
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path2file = {}
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for f in files:
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normalized = str(f.path).lower()
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if normalized in path2file:
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try:
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if op.samefile(normalized, str(path2file[normalized].path)):
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continue # same file, it's a dupe
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else:
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pass # We don't treat them as dupes
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except OSError:
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continue # File doesn't exist? Well, treat them as dupes
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else:
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path2file[normalized] = f
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result.append(f)
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return result
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class Scanner:
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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, tr("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 {ScanType.Contents, ScanType.ContentsAudio, ScanType.Folders}:
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sizeattr = 'audiosize' if self.scan_type == ScanType.ContentsAudio else 'size'
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return engine.getmatches_by_contents(files, sizeattr, partial=self.scan_type==ScanType.ContentsAudio, 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 == ScanType.FieldsNoOrder:
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self.scan_type = ScanType.Fields
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kw['no_field_order'] = True
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func = {
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ScanType.Filename: lambda f: engine.getwords(rem_file_ext(f.name)),
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ScanType.Fields: lambda f: engine.getfields(rem_file_ext(f.name)),
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ScanType.Tag: lambda f: [engine.getwords(str(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, tr("Read metadata of %d/%d files")):
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logging.debug("Reading metadata of {}".format(str(f.path)))
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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 -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 dupename:
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return False
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if 'copy' in refname:
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return True
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if is_same_with_digit(dupename, refname):
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return False
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if is_same_with_digit(refname, dupename):
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return True
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return len(dupe.path) > len(ref.path)
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def get_dupe_groups(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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files = remove_dupe_paths(files)
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logging.info("Getting matches. Scan type: %d", self.scan_type)
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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, tr("Removing false matches"))
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# In removing what we call here "false matches", we first want to remove, if we scan by
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# folders, we want to remove folder matches for which the parent is also in a match (they're
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# "duplicated duplicates if you will). Then, we also don't want mixed file kinds if the
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# option isn't enabled, we want matches for which both files exist and, lastly, we don't
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# want matches with both files as ref.
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if self.scan_type == ScanType.Folders and matches:
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allpath = {m.first.path for m in matches}
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allpath |= {m.second.path for m in matches}
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sortedpaths = sorted(allpath)
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toremove = set()
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last_parent_path = sortedpaths[0]
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for p in sortedpaths[1:]:
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if p in last_parent_path:
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toremove.add(p)
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else:
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last_parent_path = p
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matches = [m for m in matches if m.first.path not in toremove or m.second.path not in toremove]
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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 m.first.path.exists() and m.second.path.exists()]
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matches = [m for m in matches if not (m.first.is_ref and m.second.is_ref)]
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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, tr("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(str(m.first.path), str(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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if self.scan_type in {ScanType.Filename, ScanType.Fields, ScanType.FieldsNoOrder, ScanType.Tag}:
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self.discarded_file_count = len(matched_files) - sum(len(g) for g in groups)
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else:
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# Ticket #195
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# To speed up the scan, we don't bother comparing contents of files that are both ref
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# files. However, this messes up "discarded" counting because there's a missing match
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# in cases where we end up with a dupe group anyway (with a non-ref file). Because it's
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# impossible to have discarded matches in exact dupe scans, we simply set it at 0, thus
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# bypassing our tricky problem.
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# Also, although ScanType.FuzzyBlock is not always doing exact comparisons, we also
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# bypass ref comparison, thus messing up with our "discarded" count. So we're
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# effectively disabling the "discarded" feature in PE, but it's better than falsely
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# reporting discarded matches.
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self.discarded_file_count = 0
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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, tr("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 = ScanType.Filename
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scanned_tags = {'artist', 'title'}
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size_threshold = 0
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word_weighting = False
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