#!/usr/bin/env python # -*- coding: utf-8 -*- # # GuessIt - A library for guessing information from filenames # Copyright (c) 2013 Nicolas Wack # # 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 . # from __future__ import absolute_import, division, print_function, unicode_literals from os.path import splitext from guessit.plugins.transformers import Transformer from guessit import fileutils class SplitPathComponents(Transformer): def __init__(self): Transformer.__init__(self, 255) def process(self, mtree, options=None): """first split our path into dirs + basename + ext :return: the filename split into [ dir*, basename, ext ] """ if not options.get('name_only'): components = fileutils.split_path(mtree.value) basename = components.pop(-1) components += list(splitext(basename)) components[-1] = components[-1][1:] # remove the '.' from the extension mtree.split_on_components(components, category='path') else: mtree.split_on_components([mtree.value, ''], category='path') def post_process(self, mtree, options=None): """ Decrease confidence for properties found in directories, filename should always have priority. :param mtree: :param options: :return: """ if not options.get('name_only'): path_nodes = [node for node in mtree.nodes() if node.category == 'path'] for path_node in path_nodes[:-2]: self.alter_confidence(path_node, 0.3) try: last_directory_node = path_nodes[-2] self.alter_confidence(last_directory_node, 0.6) except IndexError: pass def alter_confidence(self, node, factor): for guess in node.guesses: for k in guess.keys(): confidence = guess.confidence(k) guess.set_confidence(k, confidence * factor)