mirror of https://github.com/searx/searx
106 lines
3.2 KiB
Python
106 lines
3.2 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-or-later
|
|
"""
|
|
PubMed (Scholar publications)
|
|
"""
|
|
|
|
from flask_babel import gettext
|
|
from lxml import etree
|
|
from datetime import datetime
|
|
from urllib.parse import urlencode
|
|
from searx.network import get
|
|
|
|
# about
|
|
about = {
|
|
"website": 'https://www.ncbi.nlm.nih.gov/pubmed/',
|
|
"wikidata_id": 'Q1540899',
|
|
"official_api_documentation": {
|
|
'url': 'https://www.ncbi.nlm.nih.gov/home/develop/api/',
|
|
'comment': 'More info on api: https://www.ncbi.nlm.nih.gov/books/NBK25501/'
|
|
},
|
|
"use_official_api": True,
|
|
"require_api_key": False,
|
|
"results": 'XML',
|
|
}
|
|
|
|
categories = ['science']
|
|
|
|
base_url = 'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi'\
|
|
+ '?db=pubmed&{query}&retstart={offset}&retmax={hits}'
|
|
|
|
# engine dependent config
|
|
number_of_results = 10
|
|
pubmed_url = 'https://www.ncbi.nlm.nih.gov/pubmed/'
|
|
|
|
|
|
def request(query, params):
|
|
# basic search
|
|
offset = (params['pageno'] - 1) * number_of_results
|
|
|
|
string_args = dict(query=urlencode({'term': query}),
|
|
offset=offset,
|
|
hits=number_of_results)
|
|
|
|
params['url'] = base_url.format(**string_args)
|
|
|
|
return params
|
|
|
|
|
|
def response(resp):
|
|
results = []
|
|
|
|
# First retrieve notice of each result
|
|
pubmed_retrieve_api_url = 'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?'\
|
|
+ 'db=pubmed&retmode=xml&id={pmids_string}'
|
|
|
|
pmids_results = etree.XML(resp.content)
|
|
pmids = pmids_results.xpath('//eSearchResult/IdList/Id')
|
|
pmids_string = ''
|
|
|
|
for item in pmids:
|
|
pmids_string += item.text + ','
|
|
|
|
retrieve_notice_args = dict(pmids_string=pmids_string)
|
|
|
|
retrieve_url_encoded = pubmed_retrieve_api_url.format(**retrieve_notice_args)
|
|
|
|
search_results_xml = get(retrieve_url_encoded).content
|
|
search_results = etree.XML(search_results_xml).xpath('//PubmedArticleSet/PubmedArticle/MedlineCitation')
|
|
|
|
for entry in search_results:
|
|
title = entry.xpath('.//Article/ArticleTitle')[0].text
|
|
|
|
pmid = entry.xpath('.//PMID')[0].text
|
|
url = pubmed_url + pmid
|
|
|
|
try:
|
|
content = entry.xpath('.//Abstract/AbstractText')[0].text
|
|
except:
|
|
content = gettext('No abstract is available for this publication.')
|
|
|
|
# If a doi is available, add it to the snipppet
|
|
try:
|
|
doi = entry.xpath('.//ELocationID[@EIdType="doi"]')[0].text
|
|
content = 'DOI: {doi} Abstract: {content}'.format(doi=doi, content=content)
|
|
except:
|
|
pass
|
|
|
|
if len(content) > 300:
|
|
content = content[0:300] + "..."
|
|
# TODO: center snippet on query term
|
|
|
|
res_dict = {'url': url,
|
|
'title': title,
|
|
'content': content}
|
|
|
|
try:
|
|
publishedDate = datetime.strptime(entry.xpath('.//DateCreated/Year')[0].text
|
|
+ '-' + entry.xpath('.//DateCreated/Month')[0].text
|
|
+ '-' + entry.xpath('.//DateCreated/Day')[0].text, '%Y-%m-%d')
|
|
res_dict['publishedDate'] = publishedDate
|
|
except:
|
|
pass
|
|
|
|
results.append(res_dict)
|
|
|
|
return results
|