veloura-audio 0.4.0

Reusable Python audio engine with crossfade and beat-aware transition planning.

Veloura

Veloura is a reusable Python audio transition engine for smooth queue playback. It provides FFmpeg-backed PCM decoding, equal-power crossfades, transition analysis, beat-aware planning, and a small CLI for local inspection.

Veloura is framework-agnostic. Use it in streamer tools, radio pipelines, desktop music apps, Discord/Twitch bots, or backend automation without tying your project to one bot implementation.

Features

• Equal-power crossfade mixing for signed 16-bit PCM audio
• Queue/session helpers for buffering, skip, and current-track snapshots
• Smart transition planning based on track duration, silence trim, and loudness
• Beat/BPM analysis with beat-aware transition plans
• Project-local or user-cache transition analysis storage
• Optional yt-dlp stream resolution for URLs and search queries
• Optional Discord audio source compatibility
• Pure-Python PCM fallback for Python builds without audioop

Requirements

• Python 3.12 or newer
• FFmpeg for decoding, playback, silence analysis, loudness analysis, and beat analysis
• yt-dlp only when resolving online stream/search inputs
• discord.py and PyNaCl only when using the Discord audio source directly

Installation

Install the core package:

pip install veloura-audio

Install stream resolution support:

pip install "veloura-audio[stream]"

Install Discord voice support:

pip install "veloura-audio[discord]"

Install every optional integration:

pip install "veloura-audio[all]"

Quick Start

from veloura.audio import AudioTrack, CrossfadeSession, transition_preset

config = transition_preset("streamer")

track = AudioTrack.from_source(
    "/music/current-song.flac",
    title="Artist - Current Song",
    duration=184,
)

session = CrossfadeSession(volume=0.65, crossfade_seconds=config.base_crossfade_seconds)
session.source.enqueue(track)

For online sources, install veloura-audio[stream] and resolve a playable stream:

import asyncio

from veloura.audio import resolve_stream_track, transition_preset


async def main():
    track = await resolve_stream_track(
        "artist song official audio",
        transition_config=transition_preset("streamer"),
    )
    print(track.title, track.stream_url)


asyncio.run(main())

CLI

Veloura exposes the same core tools through python -m veloura or the veloura console script:

python -m veloura presets
python -m veloura prepare ./song.mp3 --preset streamer
python -m veloura analyze ./song.mp3
python -m veloura plan ./current.mp3 ./next.mp3 --preset broadcast

For YouTube/search inputs, install veloura-audio[stream] and add --resolve:

python -m veloura plan "current song" "next song" --preset streamer --resolve

Transition analysis is cached under ~/.cache/veloura by default, or under the directory set in VELOURA_CACHE_DIR. Use --cache-dir for a project-local cache, or --no-cache when comparing fresh analysis.

Presets

• streamer: balanced transitions for livestream/background music
• broadcast: longer, smoother radio-style blends
• low-latency: shorter analysis windows for weaker machines or fast queues
• automix: beat-aware pair planning with conservative tempo matching

Aliases such as streamer-safe, broadcast-smooth, auto-mix, and fast are also available.

For adjacent tracks, call prepare_automix_transition_pair before playback of the next track starts. It analyzes beat windows, applies a pair-specific crossfade length, trims weak intro audio on confident matches, and nudges tempo only within a small safe range.

Standalone Example

The example player resolves local files or stream queries, prepares transition analysis, mixes the queue, and pipes PCM into ffplay:

python examples/streamer_player.py ./song-a.mp3 ./song-b.mp3 --preset streamer
python examples/streamer_player.py ./song-a.mp3 ./song-b.mp3 --cache-dir ./veloura-cache