mirror of
https://github.com/moparisthebest/SickRage
synced 2024-12-12 11:02:21 -05:00
0d9fbc1ad7
This version of SickBeard uses both TVDB and TVRage to search and gather it's series data from allowing you to now have access to and download shows that you couldn't before because of being locked into only what TheTVDB had to offer. Also this edition is based off the code we used in our XEM editon so it does come with scene numbering support as well as all the other features our XEM edition has to offer. Please before using this with your existing database (sickbeard.db) please make a backup copy of it and delete any other database files such as cache.db and failed.db if present, we HIGHLY recommend starting out with no database files at all to make this a fresh start but the choice is at your own risk! Enjoy!
163 lines
6.6 KiB
Python
163 lines
6.6 KiB
Python
#!/usr/bin/env python2
|
|
# -*- coding: utf-8 -*-
|
|
#
|
|
# GuessIt - A library for guessing information from filenames
|
|
# Copyright (c) 2012 Nicolas Wack <wackou@gmail.com>
|
|
#
|
|
# GuessIt is free software; you can redistribute it and/or modify it under
|
|
# the terms of the Lesser GNU General Public License as published by
|
|
# the Free Software Foundation; either version 3 of the License, or
|
|
# (at your option) any later version.
|
|
#
|
|
# GuessIt is distributed in the hope that it will be useful,
|
|
# but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
|
# Lesser GNU General Public License for more details.
|
|
#
|
|
# You should have received a copy of the Lesser GNU General Public License
|
|
# along with this program. If not, see <http://www.gnu.org/licenses/>.
|
|
#
|
|
|
|
from __future__ import unicode_literals
|
|
from guessit import PY3, u, base_text_type
|
|
from guessit.matchtree import MatchTree
|
|
from guessit.textutils import normalize_unicode, clean_string
|
|
import logging
|
|
|
|
log = logging.getLogger(__name__)
|
|
|
|
|
|
class IterativeMatcher(object):
|
|
def __init__(self, filename, filetype='autodetect', opts=None):
|
|
"""An iterative matcher tries to match different patterns that appear
|
|
in the filename.
|
|
|
|
The 'filetype' argument indicates which type of file you want to match.
|
|
If it is 'autodetect', the matcher will try to see whether it can guess
|
|
that the file corresponds to an episode, or otherwise will assume it is
|
|
a movie.
|
|
|
|
The recognized 'filetype' values are:
|
|
[ autodetect, subtitle, movie, moviesubtitle, episode, episodesubtitle ]
|
|
|
|
|
|
The IterativeMatcher works mainly in 2 steps:
|
|
|
|
First, it splits the filename into a match_tree, which is a tree of groups
|
|
which have a semantic meaning, such as episode number, movie title,
|
|
etc...
|
|
|
|
The match_tree created looks like the following:
|
|
|
|
0000000000000000000000000000000000000000000000000000000000000000000000000000000000 111
|
|
0000011111111111112222222222222233333333444444444444444455555555666777777778888888 000
|
|
0000000000000000000000000000000001111112011112222333333401123334000011233340000000 000
|
|
__________________(The.Prestige).______.[____.HP.______.{__-___}.St{__-___}.Chaps].___
|
|
xxxxxttttttttttttt ffffff vvvv xxxxxx ll lll xx xxx ccc
|
|
[XCT].Le.Prestige.(The.Prestige).DVDRip.[x264.HP.He-Aac.{Fr-Eng}.St{Fr-Eng}.Chaps].mkv
|
|
|
|
The first 3 lines indicates the group index in which a char in the
|
|
filename is located. So for instance, x264 is the group (0, 4, 1), and
|
|
it corresponds to a video codec, denoted by the letter'v' in the 4th line.
|
|
(for more info, see guess.matchtree.to_string)
|
|
|
|
|
|
Second, it tries to merge all this information into a single object
|
|
containing all the found properties, and does some (basic) conflict
|
|
resolution when they arise.
|
|
"""
|
|
|
|
valid_filetypes = ('autodetect', 'subtitle', 'video',
|
|
'movie', 'moviesubtitle',
|
|
'episode', 'episodesubtitle')
|
|
if filetype not in valid_filetypes:
|
|
raise ValueError("filetype needs to be one of %s" % valid_filetypes)
|
|
if not PY3 and not isinstance(filename, unicode):
|
|
log.warning('Given filename to matcher is not unicode...')
|
|
filename = filename.decode('utf-8')
|
|
|
|
filename = normalize_unicode(filename)
|
|
|
|
if opts is None:
|
|
opts = []
|
|
elif isinstance(opts, base_text_type):
|
|
opts = opts.split()
|
|
|
|
self.match_tree = MatchTree(filename)
|
|
|
|
# sanity check: make sure we don't process a (mostly) empty string
|
|
if clean_string(filename) == '':
|
|
return
|
|
|
|
mtree = self.match_tree
|
|
mtree.guess.set('type', filetype, confidence=1.0)
|
|
|
|
def apply_transfo(transfo_name, *args, **kwargs):
|
|
transfo = __import__('guessit.transfo.' + transfo_name,
|
|
globals=globals(), locals=locals(),
|
|
fromlist=['process'], level=0)
|
|
transfo.process(mtree, *args, **kwargs)
|
|
|
|
# 1- first split our path into dirs + basename + ext
|
|
apply_transfo('split_path_components')
|
|
|
|
# 2- guess the file type now (will be useful later)
|
|
apply_transfo('guess_filetype', filetype)
|
|
if mtree.guess['type'] == 'unknown':
|
|
return
|
|
|
|
# 3- split each of those into explicit groups (separated by parentheses
|
|
# or square brackets)
|
|
apply_transfo('split_explicit_groups')
|
|
|
|
# 4- try to match information for specific patterns
|
|
# NOTE: order needs to comply to the following:
|
|
# - website before language (eg: tvu.org.ru vs russian)
|
|
# - language before episodes_rexps
|
|
# - properties before language (eg: he-aac vs hebrew)
|
|
# - release_group before properties (eg: XviD-?? vs xvid)
|
|
if mtree.guess['type'] in ('episode', 'episodesubtitle'):
|
|
strategy = [ 'guess_date', 'guess_website', 'guess_release_group',
|
|
'guess_properties', 'guess_language',
|
|
'guess_video_rexps',
|
|
'guess_episodes_rexps', 'guess_weak_episodes_rexps' ]
|
|
else:
|
|
strategy = [ 'guess_date', 'guess_website', 'guess_release_group',
|
|
'guess_properties', 'guess_language',
|
|
'guess_video_rexps' ]
|
|
|
|
if 'nolanguage' in opts:
|
|
strategy.remove('guess_language')
|
|
|
|
for name in strategy:
|
|
apply_transfo(name)
|
|
|
|
# more guessers for both movies and episodes
|
|
apply_transfo('guess_bonus_features')
|
|
apply_transfo('guess_year', skip_first_year=('skip_first_year' in opts))
|
|
|
|
if 'nocountry' not in opts:
|
|
apply_transfo('guess_country')
|
|
|
|
apply_transfo('guess_idnumber')
|
|
|
|
|
|
# split into '-' separated subgroups (with required separator chars
|
|
# around the dash)
|
|
apply_transfo('split_on_dash')
|
|
|
|
# 5- try to identify the remaining unknown groups by looking at their
|
|
# position relative to other known elements
|
|
if mtree.guess['type'] in ('episode', 'episodesubtitle'):
|
|
apply_transfo('guess_episode_info_from_position')
|
|
else:
|
|
apply_transfo('guess_movie_title_from_position')
|
|
|
|
# 6- perform some post-processing steps
|
|
apply_transfo('post_process')
|
|
|
|
log.debug('Found match tree:\n%s' % u(mtree))
|
|
|
|
def matched(self):
|
|
return self.match_tree.matched()
|