# SPDX-License-Identifier: AGPL-3.0-or-later
"""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
request.
"""
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 (
eval_xpath,
eval_xpath_getindex,
eval_xpath_list,
extract_text,
)
from searx.exceptions import SearxEngineCaptchaException
from searx.engines.google import fetch_traits # pylint: disable=unused-import
from searx.engines.google import (
get_google_info,
time_range_dict,
)
from searx.enginelib.traits import EngineTraits
if TYPE_CHECKING:
import logging
logger: logging.Logger
traits: EngineTraits
# 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
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'] = datetime.now().year - 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 ``sorry.google.com``.
"""
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: scholar.google.xy
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
