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pkg-anime-wave-1

Anime downloader for aniwaves.ru (the engine behind wcostream.one).
Works on ARM7 Termux (2 GB phones), pure Python — zero Rust, zero native extensions required.

Install

pip install -U pkg-anime-wave-1
pkg install ffmpeg        # required for muxing segments

Usage

wave                          # fully interactive
wave "naruto"                 # search then pick episodes interactively
wave "naruto" -e 1-26         # episodes 1–26
wave "naruto" --all           # every episode
wave "naruto" -e 1,3,7        # specific episodes
wave "naruto" -r 720 -l dub   # 720p dub
wave "one piece" -e 1-100 -r 1080 -d /sdcard/Anime

wave --set-dir /sdcard/Anime  # save default download folder
wave --refresh-index          # force-rebuild the local title index

Options

Flag Default Description
-e, --episodes interactive Episode spec: 1-12, all, 1,3,7, combinations
--all — Download every episode
-r, --resolution 1080 Preferred quality: 1080, 720, 480, best
-l, --lang sub sub | dub | all
-d, --dir ~/Downloads/aniwaves Download directory
-t, --threads 4 Parallel segment threads
--set-dir DIR — Persist download directory to config
--refresh-index — Rebuild local title cache from sitemaps

Resume

If a download is interrupted, re-run the exact same command.
Completed segments are cached in /tmp/aniwave_segs/ and skipped.
A .done marker file is written only when an episode finishes completely.

How it works

  1. Search — Downloads the site's sitemaps (9,600+ titles) on first run and caches them in ~/.aniwave_index.json. Subsequent searches are instant fuzzy-matches against the local index.
  2. Episodes — Fetches the episode list from aniwaves.ru/ajax/episode/list/{id}.
  3. Servers — Fetches available stream servers (Vidplay, BYFMS, DGHG) for each episode.
  4. Stream — Resolves the HLS .m3u8 URL from the embed player and downloads segments in parallel.

No Cloudflare challenge needed for any of these steps.

ARM7 Termux notes

All dependencies are pure Python — no Rust toolchain needed.
Optional: install yt-dlp for better embed extraction fallback.

pip install yt-dlp   # optional but recommended

License

MIT

Metadata

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