AppleMusic-Downloader

repair downloader_song_legacy.py

This conversation tracked the comprehensive refactoring and bug-fixing of the AppleMusic-Downloader project. The work began by diagnosing why CN-region songs failed with a KeyError on extendedAssetUrls — fixed by switching to .get() with a fallback, and adding a webplayback-based stream path for songs without enhancedHls. We then extracted the entire download orchestration from cli.py (a Click-based CLI) into a new core_downloader.py module — a pure Python API with no terminal dependencies — and rewired both cli.py and download_worker.py (the GUI’s QThread) to call it directly, eliminating a class of Windows GUI crashes caused by Click’s stdin/stdout assumptions. We fixed download_worker.py’s variable name bug (remux_path vs remuxed_path) that silently dropped song files, normalized Path/str type handling, added CENC stream support (ISO-23001-7 with data:;base64, KIDs) by reconstructing Widevine PSSH boxes and passing real KIDs to mp4decrypt, switched ffmpeg remux from -f ipod to -f mp4 and added automatic fragmentation detection with fallback to aac_at/aac re-encoding for playable output, and added backward-compatible config migration for the renamed codec_song enum. We also fixed the Windows manifest name, updated the PyInstaller .spec with missing hidden imports, and corrected several type annotation issues across models.py, downloader.py, and downloader_song.py. The result is that both standard Widevine songs (e.g., ROSÉ’s toxic till the end) and CENC-encrypted songs (e.g., Queen’s Under Pressure via the 28:ctrp256 webplayback asset) now download and play correctly across all platforms.

really thanks deepseek help me to rebuild the interface
I updated the regular expression to account for Apple changing the location of the index.js file on the Apple Music web interface following WWDC2026. After removing redundant code, I used AI to add cross-platform compatibility support, moving closer to a full project refactor once the holidays are over. I also revamped the UI, implementing a card-stacking layout to make the logs easier to read. Huge thanks to AI—it has made fixing baffling bugs far more efficient.

Preparing to add new features and migrate the tech stack for cross-platform builds next month. In this update, I leveraged AI to refine part of the code and manually optimized and removed redundant code.