mirror of https://github.com/yt-dlp/yt-dlp.git
[extractor/slideslive] Support embeds and slides (#5784)
Authored by: bashonly, Grub4K, pukkandan
This commit is contained in:
bashonly
GitHub
parent
9a9006ba20
commit
3d667e0047
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@ -1,16 +1,24 @@
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import re
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import urllib.parse
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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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class SlidesLiveIE(InfoExtractor):
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_VALID_URL = r'https?://slideslive\.com/(?P<id>[0-9]+)'
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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
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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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@ -19,12 +27,14 @@ class SlidesLiveIE(InfoExtractor):
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'timestamp': 1648189972,
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'upload_date': '20220325',
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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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},
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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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# 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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@ -32,13 +42,15 @@ class SlidesLiveIE(InfoExtractor):
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'title': 'Offline Reinforcement Learning: From Algorithms to Practical Challenges',
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'upload_date': '20211115',
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'timestamp': 1636996003,
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'thumbnail': r're:^https?://.*\.jpg',
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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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},
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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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# 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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@ -47,12 +59,14 @@ class SlidesLiveIE(InfoExtractor):
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'upload_date': '20220201',
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'thumbnail': r're:^https?://.*\.jpg',
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'timestamp': 1643728135,
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'thumbnails': 'count:3',
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'chapters': 'count:2',
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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 = youtube
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# service_name = youtube, only XML slides info
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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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@ -76,26 +90,253 @@ class SlidesLiveIE(InfoExtractor):
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'comment_count': int,
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'channel_follower_count': int,
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'age_limit': 0,
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'thumbnail': r're:^https?://.*\.jpg',
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'thumbnail': r're:^https?://.*\.(?:jpg|webp)',
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'thumbnails': 'count:169',
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'playable_in_embed': True,
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'availability': 'unlisted',
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'tags': [],
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'categories': ['People & Blogs'],
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'chapters': 'count:168',
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},
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}, {
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# service_name = youtube
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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': 1629671508,
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'upload_date': '20210822',
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'chapters': 'count:7',
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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': 1654714970,
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'upload_date': '20220608',
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'chapters': 'count:6',
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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': 1622806321,
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'upload_date': '20210604',
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'chapters': 'count:15',
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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': 1654714896,
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'upload_date': '20220608',
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'chapters': 'count:8',
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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': 1654714962,
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'thumbnail': r're:^https?://.*\.(?:jpg|png)',
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'thumbnails': 'count:22',
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'upload_date': '20220608',
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'chapters': 'count:21',
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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': 1654714920,
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'thumbnail': r're:^https?://.*\.(?:jpg|png)',
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'thumbnails': 'count:30',
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'upload_date': '20220608',
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'chapters': 'count:31',
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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': 1654714920,
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'upload_date': '20220608',
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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': 1654714920,
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'upload_date': '20220608',
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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': 1654714877,
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'thumbnail': r're:^https?://.*\.(?:jpg|png)',
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'thumbnails': 'count:43',
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'upload_date': '20220608',
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'chapters': 'count:43',
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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': 1654714877,
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'upload_date': '20220608',
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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': 'UC62SdArr41t_-_fX40QCLRw',
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'uploader_url': 'http://www.youtube.com/channel/UC62SdArr41t_-_fX40QCLRw',
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'upload_date': '20200903',
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'timestamp': 1602599092,
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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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# 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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# service_name = url
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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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# service_name = vimeo
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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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_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': 1629671508,
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'upload_date': '20210822',
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'chapters': 'count:7',
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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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@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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def _extract_custom_m3u8_info(self, m3u8_data):
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m3u8_dict = {}
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@ -108,6 +349,8 @@ class SlidesLiveIE(InfoExtractor):
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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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for line in m3u8_data.splitlines():
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@ -126,9 +369,33 @@ class SlidesLiveIE(InfoExtractor):
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return m3u8_dict
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def _extract_formats(self, cdn_hostname, path, video_id):
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formats = []
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formats.extend(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))
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formats.extend(self._extract_mpd_formats(
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f'https://{cdn_hostname}/{path}/master.mpd',
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video_id, mpd_id='dash', fatal=False))
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return formats
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def _real_extract(self, url):
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video_id = self._match_id(url)
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webpage = self._download_webpage(url, video_id)
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webpage, urlh = self._download_embed_webpage_handle(
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video_id, headers=traverse_obj(parse_qs(url), {
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'Referer': ('embed_parent_url', -1),
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'Origin': ('embed_container_origin', -1)}))
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redirect_url = urlh.geturl()
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if 'domain_not_allowed' in redirect_url:
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domain = traverse_obj(parse_qs(redirect_url), ('allowed_domains[]', ...), get_all=False)
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if not domain:
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raise ExtractorError(
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'This is an embed-only presentation. Try passing --referer', expected=True)
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webpage, _ = self._download_embed_webpage_handle(video_id, headers={
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'Referer': f'https://{domain}/',
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'Origin': f'https://{domain}',
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})
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player_token = self._search_regex(r'data-player-token="([^"]+)"', webpage, 'player token')
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player_data = self._download_webpage(
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f'https://ben.slideslive.com/player/{video_id}', video_id,
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@ -139,6 +406,50 @@ class SlidesLiveIE(InfoExtractor):
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assert service_name in ('url', 'yoda', 'vimeo', 'youtube')
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service_id = player_info['service_id']
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slides_info_url = None
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slides, slides_info = [], []
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if player_info.get('slides_json_url'):
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slides_info_url = player_info['slides_json_url']
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slides = traverse_obj(self._download_json(
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slides_info_url, video_id, fatal=False,
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note='Downloading slides JSON', errnote=False), 'slides', expected_type=list) or []
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for slide_id, slide in enumerate(slides, start=1):
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slides_info.append((
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slide_id, traverse_obj(slide, ('image', 'name')),
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int_or_none(slide.get('time'), scale=1000)))
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if not slides and player_info.get('slides_xml_url'):
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slides_info_url = player_info['slides_xml_url']
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slides = self._download_xml(
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slides_info_url, video_id, fatal=False,
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note='Downloading slides XML', errnote='Failed to download slides info')
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for slide_id, slide in enumerate(slides.findall('./slide'), start=1):
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slides_info.append((
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slide_id, xpath_text(slide, './slideName', 'name'),
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int_or_none(xpath_text(slide, './timeSec', 'time'))))
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slides_version = int(self._search_regex(
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r'https?://slides\.slideslive\.com/\d+/v(\d+)/\w+\.(?:json|xml)',
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slides_info_url, 'slides version', default=0))
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if slides_version < 4:
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slide_url_template = 'https://cdn.slideslive.com/data/presentations/%s/slides/big/%s.jpg'
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else:
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slide_url_template = 'https://slides.slideslive.com/%s/slides/original/%s.png'
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|
||||
chapters, thumbnails = [], []
|
||||
if url_or_none(player_info.get('thumbnail')):
|
||||
thumbnails.append({'id': 'cover', 'url': player_info['thumbnail']})
|
||||
for slide_id, slide_path, start_time in slides_info:
|
||||
if slide_path:
|
||||
thumbnails.append({
|
||||
'id': f'{slide_id:03d}',
|
||||
'url': slide_url_template % (video_id, slide_path),
|
||||
})
|
||||
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'))
|
||||
|
|
@ -154,25 +465,15 @@ class SlidesLiveIE(InfoExtractor):
|
|||
'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',
|
||||
'thumbnail': url_or_none(player_info.get('thumbnail')),
|
||||
'thumbnails': thumbnails,
|
||||
'chapters': chapters,
|
||||
'subtitles': subtitles,
|
||||
}
|
||||
|
||||
if service_name in ('url', 'yoda'):
|
||||
if service_name == 'url':
|
||||
info['url'] = service_id
|
||||
else:
|
||||
cdn_hostname = player_info['video_servers'][0]
|
||||
formats = []
|
||||
formats.extend(self._extract_m3u8_formats(
|
||||
f'https://{cdn_hostname}/{service_id}/master.m3u8',
|
||||
video_id, 'mp4', m3u8_id='hls', fatal=False, live=True))
|
||||
formats.extend(self._extract_mpd_formats(
|
||||
f'https://{cdn_hostname}/{service_id}/master.mpd',
|
||||
video_id, mpd_id='dash', fatal=False))
|
||||
info.update({
|
||||
'formats': formats,
|
||||
})
|
||||
if service_name == 'url':
|
||||
info['url'] = service_id
|
||||
elif service_name == 'yoda':
|
||||
info['formats'] = self._extract_formats(player_info['video_servers'][0], service_id, video_id)
|
||||
else:
|
||||
info.update({
|
||||
'_type': 'url_transparent',
|
||||
|
|
@ -185,4 +486,37 @@ class SlidesLiveIE(InfoExtractor):
|
|||
f'https://player.vimeo.com/video/{service_id}',
|
||||
{'http_headers': {'Referer': url}})
|
||||
|
||||
return info
|
||||
video_slides = traverse_obj(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(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(cdn_hostname, video_path, video_id)
|
||||
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'])
|
||||
|
|
|
|||
Loading…
Reference in New Issue