loops/classifier/standard.py
helmutm bee421bece minor improvements, esp for classifier
git-svn-id: svn://svn.cy55.de/Zope3/src/loops/trunk@2174 fd906abe-77d9-0310-91a1-e0d9ade77398
2007-11-12 16:21:36 +00:00

84 lines
2.4 KiB
Python

#
# Copyright (c) 2007 Helmut Merz helmutm@cy55.de
#
# This program 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.
#
# This program 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 this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
#
"""
Standard implementations of classifier components.
$Id$
"""
import os
import re
from zope.cachedescriptors.property import Lazy
from zope.component import adapts
from zope.traversing.api import getName
from loops.classifier.base import Analyzer, Extractor
from loops.classifier.base import InformationSet
from loops.classifier.base import Statement
from loops.interfaces import IExternalFile
class FilenameExtractor(Extractor):
adapts(IExternalFile)
def __init__(self, context):
self.context = context
def extractInformationSet(self):
filename, ext = os.path.splitext(self.context.externalAddress)
return InformationSet(filename=filename)
class PathExtractor(Extractor):
adapts(IExternalFile)
def __init__(self, context):
self.context = context
def extractInformationSet(self):
params = self.context.storageParams
if 'subdir' in params:
return InformationSet(path=params['subdir'])
else:
return InformationSet()
class WordBasedAnalyzer(Analyzer):
stopWords = [u'and', u'und']
def extractStatements(self, informationSet):
result = []
for key, value in informationSet.items():
words = self.split(value)
for w in words:
if w in self.stopWords:
continue
if len(w) > 1:
result.extend([Statement(c) for c in self.findConcepts(w)])
return result
wordPattern = '\\'.join(list(' .,+*%&-!?/:_[](){}'))
def split(self, text):
return re.split('[%s]+' % self.wordPattern, text)
#return re.split(r'[\W_]+', text)