searxng/google_scholar.py at 72f6367e2323b2c57b2bb479dbadccd5b690a986

 # SPDX-License-Identifier: AGPL-3.0-or-later
 # lint: pylint
 """Google (Scholar)
 For detailed description of the *REST-full* API see: `Query Parameter
 Definitions`_.
 .. _Query Parameter Definitions:
    https://developers.google.com/custom-search/docs/xml_results#WebSearch_Query_Parameter_Definitions
 """
 # pylint: disable=invalid-name
 from urllib.parse import urlencode
 from datetime import datetime
 from typing import Optional
 from lxml import html
 from searx.utils import (
     eval_xpath,
     eval_xpath_getindex,
     eval_xpath_list,
     extract_text,
 )
 from searx.engines.google import (
     get_lang_info,
     time_range_dict,
     detect_google_sorry,
 )
 # pylint: disable=unused-import
 from searx.engines.google import (
     supported_languages_url,
     _fetch_supported_languages,
 )
 # pylint: enable=unused-import
 # about
 about = {
     "website": 'https://scholar.google.com',
     "wikidata_id": 'Q494817',
     "official_api_documentation": 'https://developers.google.com/custom-search',
     "use_official_api": False,
     "require_api_key": False,
     "results": 'HTML',
 }
 # engine dependent config
 categories = ['science', 'scientific publications']
 paging = True
 language_support = True
 use_locale_domain = True
 time_range_support = True
 safesearch = False
 send_accept_language_header = True
 def time_range_url(params):
     """Returns a URL query component for a google-Scholar time range based on
     ``params['time_range']``.  Google-Scholar does only support ranges in years.
     To have any effect, all the Searx ranges (*day*, *week*, *month*, *year*)
     are mapped to *year*.  If no range is set, an empty string is returned.
     Example::
         &as_ylo=2019
     """
     # as_ylo=2016&as_yhi=2019
     ret_val = ''
     if params['time_range'] in time_range_dict:
         ret_val = urlencode({'as_ylo': datetime.now().year - 1})
     return '&' + ret_val
 def request(query, params):
     """Google-Scholar search request"""
     offset = (params['pageno'] - 1) * 10
     lang_info = get_lang_info(params, supported_languages, language_aliases, False)
     # subdomain is: scholar.google.xy
     lang_info['subdomain'] = lang_info['subdomain'].replace("www.", "scholar.")
     query_url = (
         'https://'
         + lang_info['subdomain']
         + '/scholar'
         + "?"
         + urlencode({'q': query, **lang_info['params'], 'ie': "utf8", 'oe': "utf8", 'start': offset})
     )
     query_url += time_range_url(params)
     params['url'] = query_url
     params['cookies']['CONSENT'] = "YES+"
     params['headers'].update(lang_info['headers'])
     params['headers']['Accept'] = 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8'
     # params['google_subdomain'] = subdomain
     return params
 def parse_gs_a(text: Optional[str]):
     """Parse the text written in green.
     Possible formats:
     * "{authors} - {journal}, {year} - {publisher}"
     * "{authors} - {year} - {publisher}"
     * "{authors} - {publisher}"
     """
     if text is None or text == "":
         return None, None, None, None
     s_text = text.split(' - ')
     authors = s_text[0].split(', ')
     publisher = s_text[-1]
     if len(s_text) != 3:
         return authors, None, publisher, None
     # the format is "{authors} - {journal}, {year} - {publisher}" or "{authors} - {year} - {publisher}"
     # get journal and year
     journal_year = s_text[1].split(', ')
     # journal is optional and may contains some coma
     if len(journal_year) > 1:
         journal = ', '.join(journal_year[0:-1])
         if journal == '…':
             journal = None
     else:
         journal = None
     # year
     year = journal_year[-1]
     try:
         publishedDate = datetime.strptime(year.strip(), '%Y')
     except ValueError:
         publishedDate = None
     return authors, journal, publisher, publishedDate
 def response(resp):  # pylint: disable=too-many-locals
     """Get response from google's search request"""
     results = []
     detect_google_sorry(resp)
     # which subdomain ?
     # subdomain = resp.search_params.get('google_subdomain')
     # convert the text to dom
     dom = html.fromstring(resp.text)
     # parse results
     for result in eval_xpath_list(dom, '//div[@data-cid]'):
         title = extract_text(eval_xpath(result, './/h3[1]//a'))
         if not title:
             # this is a [ZITATION] block
             continue
         pub_type = extract_text(eval_xpath(result, './/span[@class="gs_ct1"]'))
         if pub_type:
             pub_type = pub_type[1:-1].lower()
         url = eval_xpath_getindex(result, './/h3[1]//a/@href', 0)
         content = extract_text(eval_xpath(result, './/div[@class="gs_rs"]'))
         authors, journal, publisher, publishedDate = parse_gs_a(
             extract_text(eval_xpath(result, './/div[@class="gs_a"]'))
         )
         if publisher in url:
             publisher = None
         # cited by
         comments = extract_text(eval_xpath(result, './/div[@class="gs_fl"]/a[starts-with(@href,"/scholar?cites=")]'))
         # link to the html or pdf document
         html_url = None
         pdf_url = None
         doc_url = eval_xpath_getindex(result, './/div[@class="gs_or_ggsm"]/a/@href', 0, default=None)
         doc_type = extract_text(eval_xpath(result, './/span[@class="gs_ctg2"]'))
         if doc_type == "[PDF]":
             pdf_url = doc_url
         else:
             html_url = doc_url
         results.append(
             {
                 'template': 'paper.html',
                 'type': pub_type,
                 'url': url,
                 'title': title,
                 'authors': authors,
                 'publisher': publisher,
                 'journal': journal,
                 'publishedDate': publishedDate,
                 'content': content,
                 'comments': comments,
                 'html_url': html_url,
                 'pdf_url': pdf_url,
             }
         )
     # parse suggestion
     for suggestion in eval_xpath(dom, '//div[contains(@class, "gs_qsuggest_wrap")]//li//a'):
         # append suggestion
         results.append({'suggestion': extract_text(suggestion)})
     for correction in eval_xpath(dom, '//div[@class="gs_r gs_pda"]/a'):
         results.append({'correction': extract_text(correction)})
     return results