def search_articles(request, input_text):
template = loader.get_template('search/search_articles.html')
articles = Article.search(input_text)
articles_info = []
for article in articles:
article_info = {}
article_info['article'] = article
article_info['authors_acronym'] = map(lambda a: a.acronym, article.authors.all())
articles_info.append(article_info)
context = RequestContext(request, {
'articles': articles_info,
})
return HttpResponse(template.render(context))
def get(self, request):
key_words = request.GET.get('s', '')
re_datas = []
if key_words:
s = Article.search()
s = s.suggest('my_suggest', key_words, completion={
"field": "title_suggest", "fuzzy": {
"fuzziness": 2
},
"size": 10
})
suggestions = s.execute_suggest()
for match in suggestions.my_suggest[0].options:
source = match._source
re_datas.append(source["title"])
return HttpResponse(json.dumps(re_datas), content_type="application/json")
def import_db(article_info):
def normalize_array_str(info):
return info if isinstance(info, (str, unicode)) else ''.join(info)
def normalize_authors(authors):
normalized_authors = []
for author in authors:
author_info = {}
if isinstance(author, (str, unicode, list)):
author_info['author'] = normalize_array_str(author)
elif isinstance(author, dict):
for k, v in author.iteritems():
author_info[k] = normalize_array_str(v)
if author_info:
normalized_authors.append(author_info)
return normalized_authors
if article_info['abstract']:
semantic_extractor = SemanticExtractor(article_info['abstract'])
extracted_keywords_map = semantic_extractor.get_keywords()
extracted_language_acr = semantic_extractor.get_language()
else:
extracted_keywords_map = {}
extracted_language_acr = None
article_title = normalize_array_str(article_info['title'])
article_authors = normalize_authors(article_info['authors'])
article = Article.add_article(article_title, article_authors,
language_acr=extracted_language_acr)
for reference in article_info.get('references', []):
r_title = normalize_array_str(reference['title'])
r_authors = normalize_authors(reference['authors'])
Reference.add_reference(article, r_title, r_authors)
for ck in article_info.get('keywords'):
if isinstance(ck, dict):
v = ck.get('keyword', [])
keyword = normalize_array_str(v)
Theme.add_themes(article, keyword, 'article')
synonyms_list = ck.get('synonyms', [])
for synonym in synonyms_list:
Theme.add_theme_synonym(keyword, normalize_array_str(synonym))
elif isinstance(ck, (str, list)):
keyword = normalize_array_str(ck)
Theme.add_themes(article, keyword, 'article')
for extraction_type, keyword_list in extracted_keywords_map.iteritems():
for keyword in keyword_list:
Theme.add_themes(article, keyword, extraction_type)
return article
