freemusic

This project is a music downloader utility built to explore asynchronous Python, web scraping, and API integration. It fetches metadata from Spotify, retrieves audio via YouTube, and injects ID3 tags into the resulting MP3 files.

Note: This is an educational project for portfolio purposes. It is not intended for deployment or piracy.

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freemusic.mp4

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Tech Stack

• Backend: Django
• APIs: Spotipy (Spotify Web API)
• Audio Engine: yt-dlp
• Metadata: eyed3
• Concurrency: asyncio & asgiref
• Frontend: Django Templates + Tailwind

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Technical Logic

1. Asynchronous API Wrapper

Since the standard Spotify library is synchronous, I implemented an AsyncSpotify class. By wrapping calls in sync_to_async, the application handles data fetching (playlists, tracks, top artists) without blocking the event loop.

2. Authentication Flow

The app utilizes Spotify OAuth to access user-specific data. Session tokens are managed to allow browsing of private libraries, recently played tracks, and personalized playlists.

3. Download & Metadata Pipeline

The core logic resides in the download view, which follows a strict pipeline:

• Metadata Extraction: Pulls track titles, artists, and high-res album art from Spotify.
• Sanitization: Cleans strings to ensure filesystem compatibility across different OS environments.
• Download: Uses fetched metadata from Spotify to query YouTube and download audio with yt-dlp. FFMPEG converts the audio to MP3.
• Concurrent Execution: Uses asyncio.gather with defined chunk sizes to download audio while managing rate limits and system resources.
• Tagging: Files are processed via eyed3 to embed cover art and metadata directly into the MP3.
• Cleanup: The system bundles files into a ZIP archive for the user and performs an immediate cleanup of the local server storage.

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Future Improvements

• Robust Error Handling: Replacing generic try/except blocks with specific exception logging to better track failed downloads or tagging errors.
• Task Queuing: Migrating long-running download tasks from the request-response cycle to a worker-based system like Celery.
• Dynamic Throttling: Implementing a more sophisticated rate-limiting algorithm to better navigate external site protections.