A GitHub Action that automatically converts YouTube videos to audio and uploads them as podcast episodes to Spotify.
Y2S (YouTube to Spotify) is a GitHub Action that automates the process of converting YouTube videos to audio files and uploading them as podcast episodes to Spotify. It solves the problem of manually repurposing YouTube content for podcast platforms, streamlining the workflow for creators who maintain both mediums.
Content creators, podcasters, and developers who publish video content on YouTube and want to automatically distribute it as audio podcasts on Spotify via Anchor.fm.
Developers choose this tool because it eliminates manual uploads through seamless automation, offers extensive customization for audio processing and metadata, and integrates directly into GitHub workflows for reliability and version control.
An automation process to convert YouTube video into audio file and uploading it to Anchor.fm podcast
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Seamlessly integrates with GitHub Actions to trigger uploads automatically when the episode.json file is updated, eliminating manual intervention as described in the workflow setup.
Supports custom ffmpeg arguments for audio conversion, enabling fine-tuned control like mono audio, silence removal, and fade-in effects through the POSTPROCESSOR_ARGS environment variable.
Allows managing multiple podcasts from a single repository using separate JSON and workflow files, streamlining content management for creators with several shows.
Can be run locally with Node.js and Python by setting up a .env file, facilitating testing and debugging before deploying to automation, as outlined in the development section.
Relies on Puppeteer to automate Spotify's web interface, which is brittle and prone to breaking if Spotify updates its login or upload pages, as acknowledged in the USER_AGENT documentation.
Requires at least one episode to be manually published on Spotify first, as noted in the README, adding overhead and limiting usability for brand-new podcasts.
Uploading YouTube playlists involves external tools like curl and jq, with warnings about potential violations of GitHub's Terms of Service, making it cumbersome and risky.