Anime downloader for aniwaves.ru — search, browse, HLS download with resume. Works on ARM7 Termux.
Project description
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
- 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. - Episodes — Fetches the episode list from
aniwaves.ru/ajax/episode/list/{id}. - Servers — Fetches available stream servers (Vidplay, BYFMS, DGHG) for each episode.
- Stream — Resolves the HLS
.m3u8URL 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
Project details
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