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#!/usr/bin/env python
from urllib import urlencode
from lxml import html
from searx.engines.xpath import extract_text, extract_url
from searx.engines.yahoo import parse_url
from datetime import datetime, timedelta
import re
categories = ['news']
search_url = 'http://news.search.yahoo.com/search?{query}&b={offset}'
results_xpath = '//div[@class="res"]'
url_xpath = './/h3/a/@href'
title_xpath = './/h3/a'
content_xpath = './/div[@class="abstr"]'
publishedDate_xpath = './/span[@class="timestamp"]'
suggestion_xpath = '//div[@id="satat"]//a'
paging = True
def request(query, params):
offset = (params['pageno'] - 1) * 10 + 1
if params['language'] == 'all':
language = 'en'
else:
language = params['language'].split('_')[0]
params['url'] = search_url.format(offset=offset,
query=urlencode({'p': query}))
params['cookies']['sB'] = 'fl=1&vl=lang_{lang}&sh=1&rw=new&v=1'\
.format(lang=language)
return params
def response(resp):
results = []
dom = html.fromstring(resp.text)
for result in dom.xpath(results_xpath):
url = parse_url(extract_url(result.xpath(url_xpath), search_url))
title = extract_text(result.xpath(title_xpath)[0])
content = extract_text(result.xpath(content_xpath)[0])
publishedDate = extract_text(result.xpath(publishedDate_xpath)[0])
if re.match("^[0-9]+ minute(s|) ago$", publishedDate):
publishedDate = datetime.now() - timedelta(minutes=int(re.match(r'\d+', publishedDate).group()))
else:
if re.match("^[0-9]+ hour(s|), [0-9]+ minute(s|) ago$", publishedDate):
timeNumbers = re.findall(r'\d+', publishedDate)
publishedDate = datetime.now() - timedelta(hours=int(timeNumbers[0])) - timedelta(minutes=int(timeNumbers[1]))
else:
# TODO year in string possible?
publishedDate = datetime.strptime(publishedDate,"%b %d %H:%M%p")
if publishedDate.year == 1900:
publishedDate = publishedDate.replace(year=datetime.now().year)
results.append({'url': url, 'title': title, 'content': content,'publishedDate':publishedDate})
if not suggestion_xpath:
return results
for suggestion in dom.xpath(suggestion_xpath):
results.append({'suggestion': extract_text(suggestion)})
return results
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