Source code for searx.engines.google_scholar

# SPDX-License-Identifier: AGPL-3.0-or-later
# lint: pylint
"""This is the implementation of the Google Scholar engine.

Compared to other Google services the Scholar engine has a simple GET REST-API
and there does not exists `async` API.  Even though the API slightly vintage we
can make use of the :ref:`google API` to assemble the arguments of the GET

from typing import TYPE_CHECKING
from typing import Optional

from urllib.parse import urlencode
from datetime import datetime
from lxml import html

from searx.utils import (

from searx.exceptions import SearxEngineCaptchaException

from import fetch_traits  # pylint: disable=unused-import
from import (
from searx.enginelib.traits import EngineTraits

    import logging

    logger: logging.Logger

traits: EngineTraits

# about
about = {
    "website": '',
    "wikidata_id": 'Q494817',
    "official_api_documentation": '',
    "use_official_api": False,
    "require_api_key": False,
    "results": 'HTML',

# engine dependent config
categories = ['science', 'scientific publications']
paging = True
max_page = 50
language_support = True
time_range_support = True
safesearch = False
send_accept_language_header = True

[docs] def time_range_args(params): """Returns a dictionary with a time range arguments based on ``params['time_range']``. Google Scholar supports a detailed search by year. Searching by *last month* or *last week* (as offered by SearXNG) is uncommon for scientific publications and is not supported by Google Scholar. To limit the result list when the users selects a range, all the SearXNG ranges (*day*, *week*, *month*, *year*) are mapped to *year*. If no range is set an empty dictionary of arguments is returned. Example; when user selects a time range (current year minus one in 2022): .. code:: python { 'as_ylo' : 2021 } """ ret_val = {} if params['time_range'] in time_range_dict: ret_val['as_ylo'] = - 1 return ret_val
[docs] def detect_google_captcha(dom): """In case of CAPTCHA Google Scholar open its own *not a Robot* dialog and is not redirected to ````. """ if eval_xpath(dom, "//form[@id='gs_captcha_f']"): raise SearxEngineCaptchaException()
[docs] def request(query, params): """Google-Scholar search request""" google_info = get_google_info(params, traits) # subdomain is: google_info['subdomain'] = google_info['subdomain'].replace("www.", "scholar.") args = { 'q': query, **google_info['params'], 'start': (params['pageno'] - 1) * 10, 'as_sdt': '2007', # include patents / to disable set '0,5' 'as_vis': '0', # include citations / to disable set '1' } args.update(time_range_args(params)) params['url'] = 'https://' + google_info['subdomain'] + '/scholar?' + urlencode(args) params['cookies'] = google_info['cookies'] params['headers'].update(google_info['headers']) return params
[docs] 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
[docs] def response(resp): # pylint: disable=too-many-locals """Parse response from Google Scholar""" results = [] # convert the text to dom dom = html.fromstring(resp.text) detect_google_captcha(dom) # parse results for result in eval_xpath_list(dom, '//div[@data-rp]'): 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_ctg2"]')) 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