streamrip is a CLI application that downloads music tracks, albums, playlists, and artist discographies from Qobuz, Tidal, Deezer, and SoundCloud. It operates as an async pipeline: user input (URLs, IDs, or search queries) is parsed into pending items, resolved into metadata-rich media objects, and then concurrently downloaded with rate limiting. The system handles audio conversion (via ffmpeg), metadata tagging (via mutagen), artwork embedding, and maintains a SQLite database to avoid re-downloading known tracks. The codebase is modular with separate client classes for each streaming service, media abstraction layers, and a config system based on TOML. It uses rich for console output and progress bars.
Spleeter is a Python library and CLI tool for music source separation, providing pretrained models to decompose audio tracks into stems (e.g., vocals, drums, bass, piano). The codebase is structured around a core Separator class backed by TensorFlow estimation, with abstract audio adapters (default FFMPEG), model providers (GitHub releases), and configuration loading from embedded or file-based JSON. The architecture supports both inference and training, with a well-defined pipeline for waveform loading, STFT computation, U-Net-based separation, and output saving. The library is designed for production use with multiprocessing support and Docker deployment. However, it relies heavily on deprecated TensorFlow 1.x APIs (tf.compat.v1, tf.estimator), indicating technical drift. The code is well-organized with clear separation of concerns, reusable components (audio adapter, model provider, utilities), and comprehensive test coverage.