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			555 lines
		
	
	
		
			21 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			555 lines
		
	
	
		
			21 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| import re
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| import urllib.parse
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| import xml.etree.ElementTree
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| 
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| from .common import InfoExtractor
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| from ..utils import (
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|     ExtractorError,
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|     int_or_none,
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|     parse_qs,
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|     smuggle_url,
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|     traverse_obj,
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|     unified_timestamp,
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|     update_url_query,
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|     url_or_none,
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|     xpath_text,
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| )
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| 
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| 
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| class SlidesLiveIE(InfoExtractor):
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|     _VALID_URL = r'https?://slideslive\.com/(?:embed/(?:presentation/)?)?(?P<id>[0-9]+)'
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|     _TESTS = [{
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|         # service_name = yoda, only XML slides info
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|         'url': 'https://slideslive.com/38902413/gcc-ia16-backend',
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|         'info_dict': {
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|             'id': '38902413',
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|             'ext': 'mp4',
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|             'title': 'GCC IA16 backend',
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|             'timestamp': 1697793372,
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|             'upload_date': '20231020',
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|             'thumbnail': r're:^https?://.*\.jpg',
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|             'thumbnails': 'count:42',
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|             'chapters': 'count:41',
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|             'duration': 1638,
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|         },
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # service_name = yoda, /v7/ slides
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|         'url': 'https://slideslive.com/38935785',
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|         'info_dict': {
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|             'id': '38935785',
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|             'ext': 'mp4',
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|             'title': 'Offline Reinforcement Learning: From Algorithms to Practical Challenges',
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|             'upload_date': '20231020',
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|             'timestamp': 1697807002,
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|             'thumbnail': r're:^https?://.*\.(?:jpg|png)',
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|             'thumbnails': 'count:640',
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|             'chapters': 'count:639',
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|             'duration': 9832,
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|         },
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # service_name = yoda, /v1/ slides
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|         'url': 'https://slideslive.com/38973182/how-should-a-machine-learning-researcher-think-about-ai-ethics',
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|         'info_dict': {
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|             'id': '38973182',
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|             'ext': 'mp4',
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|             'title': 'How Should a Machine Learning Researcher Think About AI Ethics?',
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|             'upload_date': '20231020',
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|             'thumbnail': r're:^https?://.*\.jpg',
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|             'timestamp': 1697822521,
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|             'thumbnails': 'count:3',
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|             'chapters': 'count:2',
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|             'duration': 5889,
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|         },
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # formerly youtube, converted to native
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|         'url': 'https://slideslive.com/38897546/special-metaprednaska-petra-ludwiga-hodnoty-pro-lepsi-spolecnost',
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|         'md5': '8a79b5e3d700837f40bd2afca3c8fa01',
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|         'info_dict': {
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|             'id': '38897546',
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|             'ext': 'mp4',
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|             'title': 'SPECIÁL: Meta-přednáška Petra Ludwiga - Hodnoty pro lepší společnost',
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|             'thumbnail': r're:^https?://.*\.jpg',
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|             'upload_date': '20231029',
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|             'timestamp': 1698588144,
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|             'thumbnails': 'count:169',
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|             'chapters': 'count:168',
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|             'duration': 6827,
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|         },
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # embed-only presentation, only XML slides info
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|         'url': 'https://slideslive.com/embed/presentation/38925850',
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|         'info_dict': {
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|             'id': '38925850',
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|             'ext': 'mp4',
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|             'title': 'Towards a Deep Network Architecture for Structured Smoothness',
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|             'thumbnail': r're:^https?://.*\.jpg',
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|             'thumbnails': 'count:8',
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|             'timestamp': 1697803109,
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|             'upload_date': '20231020',
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|             'chapters': 'count:7',
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|             'duration': 326,
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|         },
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # embed-only presentation, only JSON slides info, /v5/ slides (.png)
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|         'url': 'https://slideslive.com/38979920/',
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|         'info_dict': {
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|             'id': '38979920',
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|             'ext': 'mp4',
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|             'title': 'MoReL: Multi-omics Relational Learning',
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|             'thumbnail': r're:^https?://.*\.(?:jpg|png)',
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|             'thumbnails': 'count:7',
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|             'timestamp': 1697824939,
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|             'upload_date': '20231020',
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|             'chapters': 'count:6',
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|             'duration': 171,
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|         },
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # /v2/ slides (.jpg)
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|         'url': 'https://slideslive.com/38954074',
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|         'info_dict': {
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|             'id': '38954074',
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|             'ext': 'mp4',
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|             'title': 'Decentralized Attribution of Generative Models',
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|             'thumbnail': r're:^https?://.*\.jpg',
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|             'thumbnails': 'count:16',
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|             'timestamp': 1697814901,
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|             'upload_date': '20231020',
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|             'chapters': 'count:15',
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|             'duration': 306,
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|         },
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # /v4/ slides (.png)
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|         'url': 'https://slideslive.com/38979570/',
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|         'info_dict': {
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|             'id': '38979570',
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|             'ext': 'mp4',
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|             'title': 'Efficient Active Search for Combinatorial Optimization Problems',
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|             'thumbnail': r're:^https?://.*\.(?:jpg|png)',
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|             'thumbnails': 'count:9',
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|             'timestamp': 1697824757,
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|             'upload_date': '20231020',
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|             'chapters': 'count:8',
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|             'duration': 295,
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|         },
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # /v10/ slides
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|         'url': 'https://slideslive.com/embed/presentation/38979880?embed_parent_url=https%3A%2F%2Fedit.videoken.com%2F',
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|         'info_dict': {
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|             'id': '38979880',
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|             'ext': 'mp4',
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|             'title': 'The Representation Power of Neural Networks',
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|             'timestamp': 1697824919,
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|             'thumbnail': r're:^https?://.*\.(?:jpg|png)',
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|             'thumbnails': 'count:22',
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|             'upload_date': '20231020',
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|             'chapters': 'count:21',
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|             'duration': 294,
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|         },
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # /v7/ slides, 2 video slides
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|         'url': 'https://slideslive.com/embed/presentation/38979682?embed_container_origin=https%3A%2F%2Fedit.videoken.com',
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|         'playlist_count': 3,
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|         'info_dict': {
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|             'id': '38979682-playlist',
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|             'title': 'LoRA: Low-Rank Adaptation of Large Language Models',
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|         },
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|         'playlist': [{
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|             'info_dict': {
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|                 'id': '38979682',
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|                 'ext': 'mp4',
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|                 'title': 'LoRA: Low-Rank Adaptation of Large Language Models',
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|                 'timestamp': 1697824815,
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|                 'thumbnail': r're:^https?://.*\.(?:jpg|png)',
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|                 'thumbnails': 'count:30',
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|                 'upload_date': '20231020',
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|                 'chapters': 'count:31',
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|                 'duration': 272,
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|             },
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|         }, {
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|             'info_dict': {
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|                 'id': '38979682-021',
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|                 'ext': 'mp4',
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|                 'title': 'LoRA: Low-Rank Adaptation of Large Language Models - Slide 021',
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|                 'duration': 3,
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|                 'timestamp': 1697824815,
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|                 'upload_date': '20231020',
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|             },
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|         }, {
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|             'info_dict': {
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|                 'id': '38979682-024',
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|                 'ext': 'mp4',
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|                 'title': 'LoRA: Low-Rank Adaptation of Large Language Models - Slide 024',
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|                 'duration': 4,
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|                 'timestamp': 1697824815,
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|                 'upload_date': '20231020',
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|             },
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|         }],
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # /v6/ slides, 1 video slide, edit.videoken.com embed
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|         'url': 'https://slideslive.com/38979481/',
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|         'playlist_count': 2,
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|         'info_dict': {
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|             'id': '38979481-playlist',
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|             'title': 'How to Train Your MAML to Excel in Few-Shot Classification',
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|         },
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|         'playlist': [{
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|             'info_dict': {
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|                 'id': '38979481',
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|                 'ext': 'mp4',
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|                 'title': 'How to Train Your MAML to Excel in Few-Shot Classification',
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|                 'timestamp': 1697824716,
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|                 'thumbnail': r're:^https?://.*\.(?:jpg|png)',
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|                 'thumbnails': 'count:43',
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|                 'upload_date': '20231020',
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|                 'chapters': 'count:43',
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|                 'duration': 315,
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|             },
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|         }, {
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|             'info_dict': {
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|                 'id': '38979481-013',
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|                 'ext': 'mp4',
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|                 'title': 'How to Train Your MAML to Excel in Few-Shot Classification - Slide 013',
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|                 'duration': 3,
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|                 'timestamp': 1697824716,
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|                 'upload_date': '20231020',
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|             },
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|         }],
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # /v3/ slides, .jpg and .png, service_name = youtube
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|         'url': 'https://slideslive.com/embed/38932460/',
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|         'info_dict': {
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|             'id': 'RTPdrgkyTiE',
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|             'display_id': '38932460',
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|             'ext': 'mp4',
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|             'title': 'Active Learning for Hierarchical Multi-Label Classification',
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|             'description': 'Watch full version of this video at https://slideslive.com/38932460.',
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|             'channel': 'SlidesLive Videos - A',
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|             'channel_id': 'UC62SdArr41t_-_fX40QCLRw',
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|             'channel_url': 'https://www.youtube.com/channel/UC62SdArr41t_-_fX40QCLRw',
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|             'uploader': 'SlidesLive Videos - A',
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|             'uploader_id': '@slideslivevideos-a6075',
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|             'uploader_url': 'https://www.youtube.com/@slideslivevideos-a6075',
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|             'upload_date': '20200903',
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|             'timestamp': 1697805922,
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|             'duration': 942,
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|             'age_limit': 0,
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|             'live_status': 'not_live',
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|             'playable_in_embed': True,
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|             'availability': 'unlisted',
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|             'categories': ['People & Blogs'],
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|             'tags': [],
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|             'channel_follower_count': int,
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|             'like_count': int,
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|             'view_count': int,
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|             'thumbnail': r're:^https?://.*\.(?:jpg|png|webp)',
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|             'thumbnails': 'count:21',
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|             'chapters': 'count:20',
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|         },
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # /v3/ slides, .png only, service_name = yoda
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|         'url': 'https://slideslive.com/38983994',
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|         'info_dict': {
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|             'id': '38983994',
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|             'ext': 'mp4',
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|             'title': 'Zero-Shot AutoML with Pretrained Models',
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|             'timestamp': 1697826708,
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|             'upload_date': '20231020',
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|             'thumbnail': r're:^https?://.*\.(?:jpg|png)',
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|             'thumbnails': 'count:23',
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|             'chapters': 'count:22',
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|             'duration': 295,
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|         },
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }, {
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|         # service_name = yoda
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|         'url': 'https://slideslive.com/38903721/magic-a-scientific-resurrection-of-an-esoteric-legend',
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|         'only_matching': True,
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|     }, {
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|         # dead link, service_name = url
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|         'url': 'https://slideslive.com/38922070/learning-transferable-skills-1',
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|         'only_matching': True,
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|     }, {
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|         # dead link, service_name = vimeo
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|         'url': 'https://slideslive.com/38921896/retrospectives-a-venue-for-selfreflection-in-ml-research-3',
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|         'only_matching': True,
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|     }]
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| 
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|     _WEBPAGE_TESTS = [{
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|         # only XML slides info
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|         'url': 'https://iclr.cc/virtual_2020/poster_Hklr204Fvr.html',
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|         'info_dict': {
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|             'id': '38925850',
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|             'ext': 'mp4',
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|             'title': 'Towards a Deep Network Architecture for Structured Smoothness',
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|             'thumbnail': r're:^https?://.*\.jpg',
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|             'thumbnails': 'count:8',
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|             'timestamp': 1697803109,
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|             'upload_date': '20231020',
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|             'chapters': 'count:7',
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|             'duration': 326,
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|         },
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|         'params': {
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|             'skip_download': 'm3u8',
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|         },
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|     }]
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| 
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|     @classmethod
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|     def _extract_embed_urls(cls, url, webpage):
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|         # Reference: https://slideslive.com/embed_presentation.js
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|         for embed_id in re.findall(r'(?s)new\s+SlidesLiveEmbed\s*\([^)]+\bpresentationId:\s*["\'](\d+)["\']', webpage):
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|             url_parsed = urllib.parse.urlparse(url)
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|             origin = f'{url_parsed.scheme}://{url_parsed.netloc}'
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|             yield update_url_query(
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|                 f'https://slideslive.com/embed/presentation/{embed_id}', {
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|                     'embed_parent_url': url,
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|                     'embed_container_origin': origin,
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|                 })
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| 
 | |
|     def _download_embed_webpage_handle(self, video_id, headers):
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|         return self._download_webpage_handle(
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|             f'https://slideslive.com/embed/presentation/{video_id}', video_id,
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|             headers=headers, query=traverse_obj(headers, {
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|                 'embed_parent_url': 'Referer',
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|                 'embed_container_origin': 'Origin',
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|             }))
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| 
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|     def _extract_custom_m3u8_info(self, m3u8_data):
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|         m3u8_dict = {}
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| 
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|         lookup = {
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|             'PRESENTATION-TITLE': 'title',
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|             'PRESENTATION-UPDATED-AT': 'timestamp',
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|             'PRESENTATION-THUMBNAIL': 'thumbnail',
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|             'PLAYLIST-TYPE': 'playlist_type',
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|             'VOD-VIDEO-SERVICE-NAME': 'service_name',
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|             'VOD-VIDEO-ID': 'service_id',
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|             'VOD-VIDEO-SERVERS': 'video_servers',
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|             'VOD-SUBTITLES': 'subtitles',
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|             'VOD-SLIDES-JSON-URL': 'slides_json_url',
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|             'VOD-SLIDES-XML-URL': 'slides_xml_url',
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|         }
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| 
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|         for line in m3u8_data.splitlines():
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|             if not line.startswith('#EXT-SL-'):
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|                 continue
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|             tag, _, value = line.partition(':')
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|             key = lookup.get(tag[8:])
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|             if not key:
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|                 continue
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|             m3u8_dict[key] = value
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| 
 | |
|         # Some values are stringified JSON arrays
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|         for key in ('video_servers', 'subtitles'):
 | |
|             if key in m3u8_dict:
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|                 m3u8_dict[key] = self._parse_json(m3u8_dict[key], None, fatal=False) or []
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| 
 | |
|         return m3u8_dict
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| 
 | |
|     def _extract_formats_and_duration(self, cdn_hostname, path, video_id, skip_duration=False):
 | |
|         formats, duration = [], None
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| 
 | |
|         hls_formats = self._extract_m3u8_formats(
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|             f'https://{cdn_hostname}/{path}/master.m3u8',
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|             video_id, 'mp4', m3u8_id='hls', fatal=False, live=True)
 | |
|         if hls_formats:
 | |
|             if not skip_duration:
 | |
|                 duration = self._extract_m3u8_vod_duration(
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|                     hls_formats[0]['url'], video_id, note='Extracting duration from HLS manifest')
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|             formats.extend(hls_formats)
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| 
 | |
|         dash_formats = self._extract_mpd_formats(
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|             f'https://{cdn_hostname}/{path}/master.mpd', video_id, mpd_id='dash', fatal=False)
 | |
|         if dash_formats:
 | |
|             if not duration and not skip_duration:
 | |
|                 duration = self._extract_mpd_vod_duration(
 | |
|                     f'https://{cdn_hostname}/{path}/master.mpd', video_id,
 | |
|                     note='Extracting duration from DASH manifest')
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|             formats.extend(dash_formats)
 | |
| 
 | |
|         return formats, duration
 | |
| 
 | |
|     def _real_extract(self, url):
 | |
|         video_id = self._match_id(url)
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|         webpage, urlh = self._download_embed_webpage_handle(
 | |
|             video_id, headers=traverse_obj(parse_qs(url), {
 | |
|                 'Referer': ('embed_parent_url', -1),
 | |
|                 'Origin': ('embed_container_origin', -1)}))
 | |
|         redirect_url = urlh.url
 | |
|         if 'domain_not_allowed' in redirect_url:
 | |
|             domain = traverse_obj(parse_qs(redirect_url), ('allowed_domains[]', ...), get_all=False)
 | |
|             if not domain:
 | |
|                 raise ExtractorError(
 | |
|                     'This is an embed-only presentation. Try passing --referer', expected=True)
 | |
|             webpage, _ = self._download_embed_webpage_handle(video_id, headers={
 | |
|                 'Referer': f'https://{domain}/',
 | |
|                 'Origin': f'https://{domain}',
 | |
|             })
 | |
| 
 | |
|         player_token = self._search_regex(r'data-player-token="([^"]+)"', webpage, 'player token')
 | |
|         player_data = self._download_webpage(
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|             f'https://ben.slideslive.com/player/{video_id}', video_id,
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|             note='Downloading player info', query={'player_token': player_token})
 | |
|         player_info = self._extract_custom_m3u8_info(player_data)
 | |
| 
 | |
|         service_name = player_info['service_name'].lower()
 | |
|         assert service_name in ('url', 'yoda', 'vimeo', 'youtube')
 | |
|         service_id = player_info['service_id']
 | |
| 
 | |
|         slide_url_template = 'https://slides.slideslive.com/%s/slides/original/%s%s'
 | |
|         slides, slides_info = {}, []
 | |
| 
 | |
|         if player_info.get('slides_json_url'):
 | |
|             slides = self._download_json(
 | |
|                 player_info['slides_json_url'], video_id, fatal=False,
 | |
|                 note='Downloading slides JSON', errnote=False) or {}
 | |
|             slide_ext_default = '.png'
 | |
|             slide_quality = traverse_obj(slides, ('slide_qualities', 0))
 | |
|             if slide_quality:
 | |
|                 slide_ext_default = '.jpg'
 | |
|                 slide_url_template = f'https://cdn.slideslive.com/data/presentations/%s/slides/{slide_quality}/%s%s'
 | |
|             for slide_id, slide in enumerate(traverse_obj(slides, ('slides', ...), expected_type=dict), 1):
 | |
|                 slides_info.append((
 | |
|                     slide_id, traverse_obj(slide, ('image', 'name')),
 | |
|                     traverse_obj(slide, ('image', 'extname'), default=slide_ext_default),
 | |
|                     int_or_none(slide.get('time'), scale=1000)))
 | |
| 
 | |
|         if not slides and player_info.get('slides_xml_url'):
 | |
|             slides = self._download_xml(
 | |
|                 player_info['slides_xml_url'], video_id, fatal=False,
 | |
|                 note='Downloading slides XML', errnote='Failed to download slides info')
 | |
|             if isinstance(slides, xml.etree.ElementTree.Element):
 | |
|                 slide_url_template = 'https://cdn.slideslive.com/data/presentations/%s/slides/big/%s%s'
 | |
|                 for slide_id, slide in enumerate(slides.findall('./slide')):
 | |
|                     slides_info.append((
 | |
|                         slide_id, xpath_text(slide, './slideName', 'name'), '.jpg',
 | |
|                         int_or_none(xpath_text(slide, './timeSec', 'time'))))
 | |
| 
 | |
|         chapters, thumbnails = [], []
 | |
|         if url_or_none(player_info.get('thumbnail')):
 | |
|             thumbnails.append({'id': 'cover', 'url': player_info['thumbnail']})
 | |
|         for slide_id, slide_path, slide_ext, start_time in slides_info:
 | |
|             if slide_path:
 | |
|                 thumbnails.append({
 | |
|                     'id': f'{slide_id:03d}',
 | |
|                     'url': slide_url_template % (video_id, slide_path, slide_ext),
 | |
|                 })
 | |
|             chapters.append({
 | |
|                 'title': f'Slide {slide_id:03d}',
 | |
|                 'start_time': start_time,
 | |
|             })
 | |
| 
 | |
|         subtitles = {}
 | |
|         for sub in traverse_obj(player_info, ('subtitles', ...), expected_type=dict):
 | |
|             webvtt_url = url_or_none(sub.get('webvtt_url'))
 | |
|             if not webvtt_url:
 | |
|                 continue
 | |
|             subtitles.setdefault(sub.get('language') or 'en', []).append({
 | |
|                 'url': webvtt_url,
 | |
|                 'ext': 'vtt',
 | |
|             })
 | |
| 
 | |
|         info = {
 | |
|             'id': video_id,
 | |
|             'title': player_info.get('title') or self._html_search_meta('title', webpage, default=''),
 | |
|             'timestamp': unified_timestamp(player_info.get('timestamp')),
 | |
|             'is_live': player_info.get('playlist_type') != 'vod',
 | |
|             'thumbnails': thumbnails,
 | |
|             'chapters': chapters,
 | |
|             'subtitles': subtitles,
 | |
|         }
 | |
| 
 | |
|         if service_name == 'url':
 | |
|             info['url'] = service_id
 | |
|         elif service_name == 'yoda':
 | |
|             formats, duration = self._extract_formats_and_duration(
 | |
|                 player_info['video_servers'][0], service_id, video_id)
 | |
|             info.update({
 | |
|                 'duration': duration,
 | |
|                 'formats': formats,
 | |
|             })
 | |
|         else:
 | |
|             info.update({
 | |
|                 '_type': 'url_transparent',
 | |
|                 'url': service_id,
 | |
|                 'ie_key': service_name.capitalize(),
 | |
|                 'display_id': video_id,
 | |
|             })
 | |
|             if service_name == 'vimeo':
 | |
|                 info['url'] = smuggle_url(
 | |
|                     f'https://player.vimeo.com/video/{service_id}',
 | |
|                     {'referer': url})
 | |
| 
 | |
|         video_slides = traverse_obj(slides, ('slides', ..., 'video', 'id'))
 | |
|         if not video_slides:
 | |
|             return info
 | |
| 
 | |
|         def entries():
 | |
|             yield info
 | |
| 
 | |
|             service_data = self._download_json(
 | |
|                 f'https://ben.slideslive.com/player/{video_id}/slides_video_service_data',
 | |
|                 video_id, fatal=False, query={
 | |
|                     'player_token': player_token,
 | |
|                     'videos': ','.join(video_slides),
 | |
|                 }, note='Downloading video slides info', errnote='Failed to download video slides info') or {}
 | |
| 
 | |
|             for slide_id, slide in enumerate(traverse_obj(slides, ('slides', ...)), 1):
 | |
|                 if not traverse_obj(slide, ('video', 'service')) == 'yoda':
 | |
|                     continue
 | |
|                 video_path = traverse_obj(slide, ('video', 'id'))
 | |
|                 cdn_hostname = traverse_obj(service_data, (
 | |
|                     video_path, 'video_servers', ...), get_all=False)
 | |
|                 if not cdn_hostname or not video_path:
 | |
|                     continue
 | |
|                 formats, _ = self._extract_formats_and_duration(
 | |
|                     cdn_hostname, video_path, video_id, skip_duration=True)
 | |
|                 if not formats:
 | |
|                     continue
 | |
|                 yield {
 | |
|                     'id': f'{video_id}-{slide_id:03d}',
 | |
|                     'title': f'{info["title"]} - Slide {slide_id:03d}',
 | |
|                     'timestamp': info['timestamp'],
 | |
|                     'duration': int_or_none(traverse_obj(slide, ('video', 'duration_ms')), scale=1000),
 | |
|                     'formats': formats,
 | |
|                 }
 | |
| 
 | |
|         return self.playlist_result(entries(), f'{video_id}-playlist', info['title'])
 | 
