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StreamSnapper is an intuitive library designed to simplify, improve, and organize YouTube and Youtube Music media streams. It offers scraping functions with higher speed extraction and efficiency with the latest tools to perform such processes.
StreamSnapper is an intuitive library designed to simplify, improve, and organize YouTube and Youtube Music media streams. It offers scraping functions with higher speed extraction and efficiency with the latest tools to perform such processes.
# Install the stable version of StreamSnapper from PyPI (recommended)
pip install --upgrade streamsnapper
# Install the development version of StreamSnapper from GitHub
pip install --upgrade git+https://github.com/henrique-coder/streamsnapper.git@main
[!Note] If you already have a version installed and want to switch to a different branch (for example, to test new features or fix bugs), you will need to use the
--force-reinstall
parameter to ensure the upgrade occurs correctly.
from streamsnapper import YouTube
youtube = YouTube(logging=False)
youtube.extract(url="https://www.youtube.com/watch?v=***********", ytdlp_data=None)
youtube.analyze(check_thumbnails=False, retrieve_dislike_count=False)
youtube.analyze_video_streams(preferred_quality="all")
youtube.analyze_audio_streams(preferred_language="source")
youtube.analyze_subtitle_streams()
from streamsnapper import YouTubeExtractor
youtube_extractor = YouTubeExtractor()
print(youtube_extractor.identify_platform(url="https://music.youtube.com/watch?v=***********"))
print(youtube_extractor.extract_video_id(url="https://www.youtube.com/watch?v=***********"))
print(
youtube_extractor.extract_playlist_id(
url="https://www.youtube.com/playlist?list=**********************************", include_private=False
)
)
print(youtube_extractor.search(query="A cool music name", sort_by="relevance", results_type="video", limit=1))
print(
youtube_extractor.get_playlist_videos(
url="https://www.youtube.com/playlist?list=**********************************", limit=None
)
)
print(
youtube_extractor.get_channel_videos(
channel_id="************************",
channel_url="https://www.youtube.com/@********",
channel_username="********",
sort_by="newest",
content_type="videos",
limit=None,
)
)
# All functions are documented and have detailed typings, use your development IDE to learn more.
from streamsnapper import Merger
merger = Merger(
logging=False
)
merger.merge(
video_path='path/to/video',
audio_path='path/to/audio',
output_path='path/to/output',
ffmpeg_path='local'
)
# All functions are documented and have detailed typings, use your development IDE to learn more.
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, fork the repository and create a pull request. You can also simply open an issue and describe your ideas or report bugs. Don't forget to give the project a star if you like it!
git checkout -b feature/{feature_name}
;git commit -m "{commit_message}"
;git push origin feature/{feature_name}
;Please note that downloading copyrighted content from some media services may be illegal in your country. This tool is designed for educational purposes only. Use at your own risk.
FAQs
StreamSnapper is an intuitive library designed to simplify, improve, and organize YouTube and Youtube Music media streams. It offers scraping functions with higher speed extraction and efficiency with the latest tools to perform such processes.
We found that streamsnapper demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Product
Socket now supports Scala and Kotlin, bringing AI-powered threat detection to JVM projects with easy manifest generation and fast, accurate scans.
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