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Source channel @githubtrending · Post #15092 · Aug 25

#python#download_music#hacktoberfest#mp3#music#playlists#python#song#song_lyrics#spotdl#spotdl_cli#spotify#youtube_music spotDL is a fast, easy tool that downloads songs from Spotify playlists by finding them on YouTube, including album art, lyrics, and metadata. You install it via Python’s pip and need FFmpeg for audio processing. It works mainly through the command line and supports batch downloads, syncing playlists, and updating metadata. Audio quality is up to 128 kbps for free users and 256 kbps for YouTube Music Premium users. This tool helps you get your Spotify music offline with metadata, but the quality depends on YouTube sources. It’s great if you want a free, quick way to save Spotify songs with details included. https://github.com/spotDL/spotify-downloader

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Interesting Planet 🌍

@interesting_planet_facts · Post #1053 · 11/19/2025, 06:11 PM

🌎 In 1977, the Soviet Venera 14 probe recorded mysterious low-frequency “thunder”-like sounds on Venus. Scientists now attribute these to seismic activity or wind interacting with the planet’s dense atmosphere. Venus’s surface winds move slowly, but thick air carries sound much farther than on Earth. ✨ #Venus⚡#sounds⚡#space 👉subscribe Interesting Planet 👉more Channels ​

djangoproject

@djangoproject · Post #255 · 02/02/2017, 06:57 PM

https://github.com/tyiannak/pyAudioAnalysis #pyAudioAnalysis is a Python library covering a wide range of audio analysis tasks. Through pyAudioAnalysis you can: Extract #audio features and representations (e.g. mfccs, spectrogram, chromagram) Classify unknown #sounds Train, parameter tune and evaluate classifiers of audio segments Detect audio events and exclude silence periods from long recordings Perform supervised segmentation (joint segmentation - classification) Perform unsupervised segmentation (e.g. speaker diarization) Extract audio thumbnails Train and use audio regression models (example application: emotion recognition) Apply dimensionality reduction to visualize audio data and content similarities