155 lines
5.4 KiB
Python
155 lines
5.4 KiB
Python
# Copyright (c) 2017 Adler Neves <adlerosn@gmail.com>
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#
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# MIT License
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#
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# Permission is hereby granted, free of charge, to any person obtaining
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# a copy of this software and associated documentation files (the
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# "Software"), to deal in the Software without restriction, including
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# without limitation the rights to use, copy, modify, merge, publish,
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# distribute, sublicense, and/or sell copies of the Software, and to
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# permit persons to whom the Software is furnished to do so, subject to
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# the following conditions:
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#
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# The above copyright notice and this permission notice shall be
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# included in all copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
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# LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
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# OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
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# WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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import os
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pluginName = os.path.abspath(__file__).split(os.path.sep)[-2]
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pluginNameFriendly = (pluginName[0].upper()+pluginName[1:]).replace('_',' ')
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from corpusslayer.hooks import getAnalysisOptionsEmptyContainer
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from corpusslayer.bootstrap_constants import COLOR
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from django.utils.translation import ugettext_lazy as _
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randfactor = .1494648
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def getAnalysisOptions():
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dropcache = getAnalysisOptionsEmptyContainer(
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pluginName = pluginName,
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)
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dropcache['text'] = _('Delete processed data [Unitex/GramLab]')
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dropcache['priority'] = -2000+randfactor
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dropcache['icon'] = 'close'
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dropcache['link'] = pluginName+'_nuke'
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dropcache['color'] = COLOR.RED
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createcache = getAnalysisOptionsEmptyContainer(
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pluginName = pluginName,
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)
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createcache['text'] = _('Process Corpus [Unitex/GramLab]')
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createcache['priority'] = -1000+randfactor
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createcache['icon'] = 'arrow-right'
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createcache['link'] = pluginName+'_process'
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createcache['color'] = COLOR.GREEN
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sentences = getAnalysisOptionsEmptyContainer(
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pluginName = pluginName,
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)
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sentences['text'] = _('Sentence List [Unitex/GramLab]')
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sentences['priority'] = 10+randfactor
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sentences['icon'] = 'list'
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sentences['link'] = pluginName+'_sentences'
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wordfreq = getAnalysisOptionsEmptyContainer(
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pluginName = pluginName,
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)
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wordfreq['text'] = _('Word Frequency [Unitex/GramLab]')
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wordfreq['priority'] = 20+randfactor
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wordfreq['icon'] = 'list-ol'
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wordfreq['link'] = pluginName+'_wordfreq'
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wordlist = getAnalysisOptionsEmptyContainer(
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pluginName = pluginName,
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)
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wordlist['text'] = _('Word List [Unitex/GramLab]')
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wordlist['priority'] = 25+randfactor
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wordlist['icon'] = 'list-ul'
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wordlist['link'] = pluginName+'_wordlist'
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sntauto = getAnalysisOptionsEmptyContainer(
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pluginName = pluginName,
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)
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sntauto['text'] = _('Sentence Automata [Unitex/GramLab]')
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sntauto['priority'] = 30+randfactor
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sntauto['icon'] = 'reorder'
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sntauto['link'] = pluginName+'_sntauto'
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txtauto = getAnalysisOptionsEmptyContainer(
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pluginName = pluginName,
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)
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txtauto['text'] = _('Text Automata [Unitex/GramLab]')
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txtauto['priority'] = 30+randfactor
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txtauto['icon'] = 'sliders'
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txtauto['link'] = pluginName+'_txtauto'
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return [
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dropcache,
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createcache,
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sentences,
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wordfreq,
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wordlist,
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sntauto,
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txtauto,
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]
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import json
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from django.urls import reverse
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from django.http import HttpResponseRedirect
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importline1 = 'import '+('.'.join(['plugins',pluginName,'models'])+' as models')
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exec(importline1) #import plugins.thisplugin.models as models
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def getSentenceList(corpus):
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val = None
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try:
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val = json.loads(models.CorpusProcessed.objects.get(corpus__pk=corpus.pk).sentences)
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val = list(filter(lambda l: len(l)>0, val))
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if len(val)==0:
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raise Exception()
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except:
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val = HttpResponseRedirect(reverse(pluginName+'_process',None,[corpus.pk]))
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return {
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'key': pluginName,
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'name': 'Unitex/GramLab',
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'sentences': val,
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}
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def getSentenceTokens(corpus):
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val = None
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try:
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val = json.loads(models.CorpusProcessed.objects.get(corpus__pk=corpus.pk).fsttext)
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val = [
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[
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palavra
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for palavra in sentence['componentes']
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if palavra.isprintable() and not palavra.isspace()
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]
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for sentence in val
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]
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except:
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val = HttpResponseRedirect(reverse(pluginName+'_process',None,[corpus.pk]))
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return {
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'key': pluginName,
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'name': 'Unitex/GramLab',
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'sentences': val,
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}
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_('Unitex/GramLab (tags are empty)')
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def getSentenceTokensTagged(corpus):
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tok = getSentenceTokens(corpus)
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tok['name']=_(tok['name']+' (tags are empty)')
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if not isinstance(tok['sentences'], HttpResponseRedirect):
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tok['sentences'] = [[[word, ''] for word in sentence] for sentence in tok['sentences']]
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return tok;
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def getHooks():
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return {
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'query:sentencelist':[
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getSentenceList
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],
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'query:sentencetokens':[
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getSentenceTokens
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],
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'query:sentencetokenstagged':[
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getSentenceTokensTagged
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],
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}
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