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81 lines
3.0 KiB
Python
81 lines
3.0 KiB
Python
from __future__ import unicode_literals
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import re
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from .common import InfoExtractor
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from ..utils import (
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ExtractorError,
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unified_strdate
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)
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class JoveIE(InfoExtractor):
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_VALID_URL = r'https?://(?:www\.)?jove\.com/video/(?P<id>[0-9]+)'
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_CHAPTERS_URL = 'http://www.jove.com/video-chapters?videoid={video_id:}'
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_TESTS = [
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{
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'url': 'http://www.jove.com/video/2744/electrode-positioning-montage-transcranial-direct-current',
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'md5': '93723888d82dbd6ba8b3d7d0cd65dd2b',
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'info_dict': {
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'id': '2744',
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'ext': 'mp4',
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'title': 'Electrode Positioning and Montage in Transcranial Direct Current Stimulation',
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'description': 'md5:015dd4509649c0908bc27f049e0262c6',
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'thumbnail': r're:^https?://.*\.png$',
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'upload_date': '20110523',
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}
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},
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{
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'url': 'http://www.jove.com/video/51796/culturing-caenorhabditis-elegans-axenic-liquid-media-creation',
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'md5': '914aeb356f416811d911996434811beb',
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'info_dict': {
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'id': '51796',
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'ext': 'mp4',
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'title': 'Culturing Caenorhabditis elegans in Axenic Liquid Media and Creation of Transgenic Worms by Microparticle Bombardment',
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'description': 'md5:35ff029261900583970c4023b70f1dc9',
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'thumbnail': r're:^https?://.*\.png$',
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'upload_date': '20140802',
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}
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},
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]
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def _real_extract(self, url):
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mobj = re.match(self._VALID_URL, url)
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video_id = mobj.group('id')
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webpage = self._download_webpage(url, video_id)
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chapters_id = self._html_search_regex(
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r'/video-chapters\?videoid=([0-9]+)', webpage, 'chapters id')
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chapters_xml = self._download_xml(
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self._CHAPTERS_URL.format(video_id=chapters_id),
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video_id, note='Downloading chapters XML',
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errnote='Failed to download chapters XML')
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video_url = chapters_xml.attrib.get('video')
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if not video_url:
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raise ExtractorError('Failed to get the video URL')
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title = self._html_search_meta('citation_title', webpage, 'title')
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thumbnail = self._og_search_thumbnail(webpage)
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description = self._html_search_regex(
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r'<div id="section_body_summary"><p class="jove_content">(.+?)</p>',
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webpage, 'description', fatal=False)
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publish_date = unified_strdate(self._html_search_meta(
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'citation_publication_date', webpage, 'publish date', fatal=False))
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comment_count = self._html_search_regex(
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r'<meta name="num_comments" content="(\d+) Comments?"',
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webpage, 'comment count', fatal=False)
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return {
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'id': video_id,
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'title': title,
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'url': video_url,
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'thumbnail': thumbnail,
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'description': description,
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'upload_date': publish_date,
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'comment_count': comment_count,
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}
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