mirror of
https://github.com/SickGear/SickGear.git
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163 lines
6.6 KiB
Python
163 lines
6.6 KiB
Python
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#!/usr/bin/env python2
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# -*- coding: utf-8 -*-
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#
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# GuessIt - A library for guessing information from filenames
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# Copyright (c) 2012 Nicolas Wack <wackou@gmail.com>
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#
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# GuessIt is free software; you can redistribute it and/or modify it under
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# the terms of the Lesser GNU General Public License as published by
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# the Free Software Foundation; either version 3 of the License, or
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# (at your option) any later version.
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#
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# GuessIt is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# Lesser GNU General Public License for more details.
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#
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# You should have received a copy of the Lesser GNU General Public License
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# along with this program. If not, see <http://www.gnu.org/licenses/>.
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#
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from __future__ import unicode_literals
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from guessit import PY3, u, base_text_type
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from guessit.matchtree import MatchTree
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from guessit.textutils import normalize_unicode, clean_string
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import logging
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log = logging.getLogger(__name__)
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class IterativeMatcher(object):
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def __init__(self, filename, filetype='autodetect', opts=None):
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"""An iterative matcher tries to match different patterns that appear
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in the filename.
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The 'filetype' argument indicates which type of file you want to match.
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If it is 'autodetect', the matcher will try to see whether it can guess
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that the file corresponds to an episode, or otherwise will assume it is
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a movie.
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The recognized 'filetype' values are:
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[ autodetect, subtitle, movie, moviesubtitle, episode, episodesubtitle ]
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The IterativeMatcher works mainly in 2 steps:
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First, it splits the filename into a match_tree, which is a tree of groups
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which have a semantic meaning, such as episode number, movie title,
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etc...
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The match_tree created looks like the following:
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0000000000000000000000000000000000000000000000000000000000000000000000000000000000 111
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0000011111111111112222222222222233333333444444444444444455555555666777777778888888 000
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0000000000000000000000000000000001111112011112222333333401123334000011233340000000 000
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__________________(The.Prestige).______.[____.HP.______.{__-___}.St{__-___}.Chaps].___
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xxxxxttttttttttttt ffffff vvvv xxxxxx ll lll xx xxx ccc
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[XCT].Le.Prestige.(The.Prestige).DVDRip.[x264.HP.He-Aac.{Fr-Eng}.St{Fr-Eng}.Chaps].mkv
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The first 3 lines indicates the group index in which a char in the
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filename is located. So for instance, x264 is the group (0, 4, 1), and
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it corresponds to a video codec, denoted by the letter'v' in the 4th line.
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(for more info, see guess.matchtree.to_string)
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Second, it tries to merge all this information into a single object
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containing all the found properties, and does some (basic) conflict
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resolution when they arise.
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"""
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valid_filetypes = ('autodetect', 'subtitle', 'video',
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'movie', 'moviesubtitle',
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'episode', 'episodesubtitle')
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if filetype not in valid_filetypes:
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raise ValueError("filetype needs to be one of %s" % valid_filetypes)
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if not PY3 and not isinstance(filename, unicode):
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log.warning('Given filename to matcher is not unicode...')
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filename = filename.decode('utf-8')
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filename = normalize_unicode(filename)
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if opts is None:
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opts = []
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elif isinstance(opts, base_text_type):
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opts = opts.split()
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self.match_tree = MatchTree(filename)
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# sanity check: make sure we don't process a (mostly) empty string
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if clean_string(filename) == '':
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return
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mtree = self.match_tree
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mtree.guess.set('type', filetype, confidence=1.0)
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def apply_transfo(transfo_name, *args, **kwargs):
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transfo = __import__('guessit.transfo.' + transfo_name,
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globals=globals(), locals=locals(),
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fromlist=['process'], level=0)
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transfo.process(mtree, *args, **kwargs)
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# 1- first split our path into dirs + basename + ext
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apply_transfo('split_path_components')
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# 2- guess the file type now (will be useful later)
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apply_transfo('guess_filetype', filetype)
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if mtree.guess['type'] == 'unknown':
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return
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# 3- split each of those into explicit groups (separated by parentheses
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# or square brackets)
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apply_transfo('split_explicit_groups')
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# 4- try to match information for specific patterns
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# NOTE: order needs to comply to the following:
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# - website before language (eg: tvu.org.ru vs russian)
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# - language before episodes_rexps
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# - properties before language (eg: he-aac vs hebrew)
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# - release_group before properties (eg: XviD-?? vs xvid)
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if mtree.guess['type'] in ('episode', 'episodesubtitle'):
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strategy = [ 'guess_date', 'guess_website', 'guess_release_group',
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'guess_properties', 'guess_language',
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'guess_video_rexps',
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'guess_episodes_rexps', 'guess_weak_episodes_rexps' ]
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else:
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strategy = [ 'guess_date', 'guess_website', 'guess_release_group',
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'guess_properties', 'guess_language',
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'guess_video_rexps' ]
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if 'nolanguage' in opts:
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strategy.remove('guess_language')
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for name in strategy:
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apply_transfo(name)
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# more guessers for both movies and episodes
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apply_transfo('guess_bonus_features')
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apply_transfo('guess_year', skip_first_year=('skip_first_year' in opts))
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if 'nocountry' not in opts:
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apply_transfo('guess_country')
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apply_transfo('guess_idnumber')
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# split into '-' separated subgroups (with required separator chars
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# around the dash)
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apply_transfo('split_on_dash')
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# 5- try to identify the remaining unknown groups by looking at their
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# position relative to other known elements
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if mtree.guess['type'] in ('episode', 'episodesubtitle'):
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apply_transfo('guess_episode_info_from_position')
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else:
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apply_transfo('guess_movie_title_from_position')
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# 6- perform some post-processing steps
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apply_transfo('post_process')
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log.debug('Found match tree:\n%s' % u(mtree))
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def matched(self):
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return self.match_tree.matched()
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