mirror of
https://github.com/searxng/searxng.git
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138 lines
4 KiB
Python
138 lines
4 KiB
Python
"""
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Wikipedia (Web)
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@website https://{language}.wikipedia.org
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@provide-api yes
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@using-api yes
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@results JSON
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@stable yes
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@parse url, infobox
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"""
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from json import loads
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from lxml.html import fromstring
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from searx.url_utils import quote, urlencode
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from searx.utils import match_language
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# search-url
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base_url = u'https://{language}.wikipedia.org/'
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search_url = base_url + u'w/api.php?'\
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'action=query'\
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'&format=json'\
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'&{query}'\
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'&prop=extracts|pageimages|pageprops'\
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'&ppprop=disambiguation'\
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'&exintro'\
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'&explaintext'\
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'&pithumbsize=300'\
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'&redirects'
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supported_languages_url = 'https://meta.wikimedia.org/wiki/List_of_Wikipedias'
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# set language in base_url
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def url_lang(lang):
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lang_pre = lang.split('-')[0]
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if lang_pre == 'all' or lang_pre not in supported_languages and lang_pre not in language_aliases:
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return 'en'
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return match_language(lang, supported_languages, language_aliases).split('-')[0]
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# do search-request
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def request(query, params):
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if query.islower():
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query = u'{0}|{1}'.format(query.decode('utf-8'), query.decode('utf-8').title()).encode('utf-8')
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params['url'] = search_url.format(query=urlencode({'titles': query}),
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language=url_lang(params['language']))
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return params
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# get first meaningful paragraph
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# this should filter out disambiguation pages and notes above first paragraph
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# "magic numbers" were obtained by fine tuning
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def extract_first_paragraph(content, title, image):
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first_paragraph = None
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failed_attempts = 0
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for paragraph in content.split('\n'):
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starts_with_title = paragraph.lower().find(title.lower(), 0, len(title) + 35)
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length = len(paragraph)
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if length >= 200 or (starts_with_title >= 0 and (image or length >= 150)):
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first_paragraph = paragraph
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break
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failed_attempts += 1
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if failed_attempts > 3:
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return None
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return first_paragraph
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# get response from search-request
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def response(resp):
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results = []
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search_result = loads(resp.text)
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# wikipedia article's unique id
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# first valid id is assumed to be the requested article
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if 'pages' not in search_result['query']:
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return results
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for article_id in search_result['query']['pages']:
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page = search_result['query']['pages'][article_id]
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if int(article_id) > 0:
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break
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if int(article_id) < 0 or 'disambiguation' in page.get('pageprops', {}):
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return []
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title = page.get('title')
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image = page.get('thumbnail')
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if image:
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image = image.get('source')
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extract = page.get('extract')
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summary = extract_first_paragraph(extract, title, image)
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summary = summary.replace('() ', '')
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# link to wikipedia article
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wikipedia_link = base_url.format(language=url_lang(resp.search_params['language'])) \
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+ 'wiki/' + quote(title.replace(' ', '_').encode('utf8'))
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results.append({'url': wikipedia_link, 'title': title})
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results.append({'infobox': title,
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'id': wikipedia_link,
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'content': summary,
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'img_src': image,
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'urls': [{'title': 'Wikipedia', 'url': wikipedia_link}]})
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return results
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# get supported languages from their site
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def _fetch_supported_languages(resp):
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supported_languages = {}
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dom = fromstring(resp.text)
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tables = dom.xpath('//table[contains(@class,"sortable")]')
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for table in tables:
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# exclude header row
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trs = table.xpath('.//tr')[1:]
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for tr in trs:
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td = tr.xpath('./td')
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code = td[3].xpath('./a')[0].text
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name = td[2].xpath('./a')[0].text
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english_name = td[1].xpath('./a')[0].text
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articles = int(td[4].xpath('./a/b')[0].text.replace(',', ''))
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# exclude languages with too few articles
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if articles >= 100:
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supported_languages[code] = {"name": name, "english_name": english_name, "articles": articles}
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return supported_languages
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