mirror of
https://github.com/searxng/searxng.git
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217 lines
6.5 KiB
Python
217 lines
6.5 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-or-later
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"""This is the implementation of the Google Scholar engine.
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Compared to other Google services the Scholar engine has a simple GET REST-API
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and there does not exists `async` API. Even though the API slightly vintage we
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can make use of the :ref:`google API` to assemble the arguments of the GET
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request.
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"""
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from typing import TYPE_CHECKING
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from typing import Optional
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from urllib.parse import urlencode
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from datetime import datetime
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from lxml import html
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from searx.utils import (
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eval_xpath,
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eval_xpath_getindex,
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eval_xpath_list,
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extract_text,
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)
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from searx.exceptions import SearxEngineCaptchaException
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from searx.engines.google import fetch_traits # pylint: disable=unused-import
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from searx.engines.google import (
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get_google_info,
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time_range_dict,
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)
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from searx.enginelib.traits import EngineTraits
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if TYPE_CHECKING:
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import logging
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logger: logging.Logger
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traits: EngineTraits
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# about
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about = {
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"website": 'https://scholar.google.com',
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"wikidata_id": 'Q494817',
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"official_api_documentation": 'https://developers.google.com/custom-search',
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"use_official_api": False,
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"require_api_key": False,
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"results": 'HTML',
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}
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# engine dependent config
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categories = ['science', 'scientific publications']
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paging = True
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max_page = 50
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language_support = True
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time_range_support = True
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safesearch = False
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send_accept_language_header = True
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def time_range_args(params):
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"""Returns a dictionary with a time range arguments based on
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``params['time_range']``.
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Google Scholar supports a detailed search by year. Searching by *last
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month* or *last week* (as offered by SearXNG) is uncommon for scientific
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publications and is not supported by Google Scholar.
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To limit the result list when the users selects a range, all the SearXNG
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ranges (*day*, *week*, *month*, *year*) are mapped to *year*. If no range
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is set an empty dictionary of arguments is returned. Example; when
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user selects a time range (current year minus one in 2022):
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.. code:: python
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{ 'as_ylo' : 2021 }
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"""
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ret_val = {}
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if params['time_range'] in time_range_dict:
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ret_val['as_ylo'] = datetime.now().year - 1
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return ret_val
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def detect_google_captcha(dom):
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"""In case of CAPTCHA Google Scholar open its own *not a Robot* dialog and is
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not redirected to ``sorry.google.com``.
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"""
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if eval_xpath(dom, "//form[@id='gs_captcha_f']"):
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raise SearxEngineCaptchaException()
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def request(query, params):
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"""Google-Scholar search request"""
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google_info = get_google_info(params, traits)
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# subdomain is: scholar.google.xy
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google_info['subdomain'] = google_info['subdomain'].replace("www.", "scholar.")
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args = {
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'q': query,
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**google_info['params'],
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'start': (params['pageno'] - 1) * 10,
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'as_sdt': '2007', # include patents / to disable set '0,5'
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'as_vis': '0', # include citations / to disable set '1'
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}
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args.update(time_range_args(params))
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params['url'] = 'https://' + google_info['subdomain'] + '/scholar?' + urlencode(args)
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params['cookies'] = google_info['cookies']
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params['headers'].update(google_info['headers'])
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return params
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def parse_gs_a(text: Optional[str]):
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"""Parse the text written in green.
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Possible formats:
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* "{authors} - {journal}, {year} - {publisher}"
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* "{authors} - {year} - {publisher}"
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* "{authors} - {publisher}"
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"""
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if text is None or text == "":
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return None, None, None, None
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s_text = text.split(' - ')
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authors = s_text[0].split(', ')
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publisher = s_text[-1]
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if len(s_text) != 3:
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return authors, None, publisher, None
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# the format is "{authors} - {journal}, {year} - {publisher}" or "{authors} - {year} - {publisher}"
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# get journal and year
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journal_year = s_text[1].split(', ')
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# journal is optional and may contains some coma
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if len(journal_year) > 1:
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journal = ', '.join(journal_year[0:-1])
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if journal == '…':
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journal = None
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else:
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journal = None
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# year
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year = journal_year[-1]
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try:
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publishedDate = datetime.strptime(year.strip(), '%Y')
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except ValueError:
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publishedDate = None
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return authors, journal, publisher, publishedDate
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def response(resp): # pylint: disable=too-many-locals
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"""Parse response from Google Scholar"""
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results = []
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# convert the text to dom
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dom = html.fromstring(resp.text)
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detect_google_captcha(dom)
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# parse results
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for result in eval_xpath_list(dom, '//div[@data-rp]'):
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title = extract_text(eval_xpath(result, './/h3[1]//a'))
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if not title:
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# this is a [ZITATION] block
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continue
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pub_type = extract_text(eval_xpath(result, './/span[@class="gs_ctg2"]'))
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if pub_type:
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pub_type = pub_type[1:-1].lower()
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url = eval_xpath_getindex(result, './/h3[1]//a/@href', 0)
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content = extract_text(eval_xpath(result, './/div[@class="gs_rs"]'))
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authors, journal, publisher, publishedDate = parse_gs_a(
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extract_text(eval_xpath(result, './/div[@class="gs_a"]'))
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)
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if publisher in url:
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publisher = None
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# cited by
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comments = extract_text(eval_xpath(result, './/div[@class="gs_fl"]/a[starts-with(@href,"/scholar?cites=")]'))
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# link to the html or pdf document
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html_url = None
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pdf_url = None
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doc_url = eval_xpath_getindex(result, './/div[@class="gs_or_ggsm"]/a/@href', 0, default=None)
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doc_type = extract_text(eval_xpath(result, './/span[@class="gs_ctg2"]'))
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if doc_type == "[PDF]":
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pdf_url = doc_url
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else:
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html_url = doc_url
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results.append(
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{
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'template': 'paper.html',
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'type': pub_type,
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'url': url,
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'title': title,
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'authors': authors,
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'publisher': publisher,
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'journal': journal,
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'publishedDate': publishedDate,
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'content': content,
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'comments': comments,
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'html_url': html_url,
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'pdf_url': pdf_url,
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}
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)
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# parse suggestion
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for suggestion in eval_xpath(dom, '//div[contains(@class, "gs_qsuggest_wrap")]//li//a'):
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# append suggestion
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results.append({'suggestion': extract_text(suggestion)})
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for correction in eval_xpath(dom, '//div[@class="gs_r gs_pda"]/a'):
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results.append({'correction': extract_text(correction)})
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return results
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