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R3600/modules/bibindex/lib/tokenizers/BibIndexEmptyTokenizer.py
ab532de38f71iugw2017

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BibIndexEmptyTokenizer.py
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# -*- coding:utf-8 -*-
##
## This file is part of Invenio.
## Copyright (C) 2010, 2011, 2012 CERN.
##
## Invenio is free software; you can redistribute it and/or
## modify it under the terms of the GNU General Public License as
## published by the Free Software Foundation; either version 2 of the
## License, or (at your option) any later version.
##
## Invenio 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 GNU
## General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with Invenio; if not, write to the Free Software Foundation, Inc.,
## 59 Temple Place, Suite 330, Boston, MA 02111-1307, USA.
"""BibIndexEmptyTokenizer: useful for situations when we want to apply tokenizer
for consistency, but we don't want to have any results from it.
"""
from invenio.bibindex_engine_config import CFG_BIBINDEX_INDEX_TABLE_TYPE
from invenio.bibindex_tokenizers.BibIndexTokenizer import BibIndexTokenizer
class BibIndexEmptyTokenizer(BibIndexTokenizer):
"""Empty tokenizer do nothing.
It returns empty lists for tokenize_for_words, tokenize_for_pairs and tokenize_for_phrases methods.
"""
def __init__(self, stemming_language = None, remove_stopwords = False, remove_html_markup = False, remove_latex_markup = False):
"""@param stemming_language: dummy
@param remove_stopwords: dummy
@param remove_html_markup: dummy
@param remove_latex_markup: dummy
"""
pass
def get_tokenizing_function(self, wordtable_type):
"""Picks correct tokenize_for_xxx function depending on type of tokenization (wordtable_type)"""
if wordtable_type == CFG_BIBINDEX_INDEX_TABLE_TYPE["Words"]:
return self.tokenize_for_words
elif wordtable_type == CFG_BIBINDEX_INDEX_TABLE_TYPE["Pairs"]:
return self.tokenize_for_pairs
elif wordtable_type == CFG_BIBINDEX_INDEX_TABLE_TYPE["Phrases"]:
return self.tokenize_for_phrases
def tokenize_for_words(self, phrase):
return []
def tokenize_for_pairs(self, phrase):
return []
def tokenize_for_phrases(self, phrase):
return []
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