"""Audio alarm functions — WAV loading and PCM streaming."""

import array
import asyncio
import json
import logging
import math
import wave
from pathlib import Path

log = logging.getLogger(__name__)

CHUNK_SIZE = 4096
AUDIO_DIR = Path(__file__).parent / "assets" / "alarm"


def find_wav(path: Path | None = None) -> Path:
    """Return a WAV file path.

    If *path* is given and points to an existing file, use it directly.
    Otherwise fall back to the first .wav found in the alarm assets directory.
    """
    if path is not None:
        p = Path(path)
        if p.is_file():
            log.info("Using audio file: %s", p)
            return p
        log.warning("Specified audio path not found: %s — falling back to glob", p)

    wavs = list(AUDIO_DIR.glob("*.wav"))
    if not wavs:
        raise FileNotFoundError(f"No .wav files found in {AUDIO_DIR}")
    log.info("Using audio file: %s", wavs[0].name)
    return wavs[0]


def _normalize_pcm(pcm: bytes, bits: int) -> bytes:
    """Peak-normalize PCM data to 0 dBFS.

    Supports 8-bit (unsigned) and 16-bit (signed) PCM.
    Returns the original bytes unchanged if already at 0 dB or silent.
    """
    if bits == 16:
        samples = array.array("h", pcm)          # signed 16-bit
        peak = max(abs(s) for s in samples) if samples else 0
        if peak == 0 or peak == 32767:
            return pcm
        scale = 32767 / peak
        samples = array.array("h", (min(32767, max(-32768, int(s * scale))) for s in samples))
    elif bits == 8:
        samples = array.array("B", pcm)          # unsigned 8-bit, center=128
        peak = max(abs(s - 128) for s in samples) if samples else 0
        if peak == 0 or peak == 127:
            return pcm
        scale = 127 / peak
        samples = array.array("B", (max(0, min(255, int((s - 128) * scale) + 128)) for s in samples))
    else:
        log.warning("Normalization not supported for %d-bit audio, skipping", bits)
        return pcm

    gain_db = 20 * __import__("math").log10(scale) if scale > 0 else 0
    log.info("Normalized: peak %d → 0 dBFS (gain %.1f dB)", peak, gain_db)
    return samples.tobytes()


def read_wav(path: Path) -> tuple[bytes, int, int, int]:
    """Read WAV file, normalize to 0 dBFS, return (pcm_data, sample_rate, channels, bits)."""
    try:
        wf = wave.open(str(path), "rb")
    except wave.Error as e:
        raise ValueError(
            f"{path.name}: unsupported WAV format ({e}). "
            "Only 8/16-bit integer PCM is supported — no 32-bit float."
        ) from e
    with wf:
        sr = wf.getframerate()
        ch = wf.getnchannels()
        bits = wf.getsampwidth() * 8
        pcm = wf.readframes(wf.getnframes())
    log.info("WAV loaded: %dHz %dch %dbit, %.1fs, %d bytes",
             sr, ch, bits, len(pcm) / (sr * ch * (bits // 8)), len(pcm))
    pcm = _normalize_pcm(pcm, bits)
    return pcm, sr, ch, bits


def chunk_bytes(data: bytes, size: int):
    """Yield data in fixed-size chunks."""
    for i in range(0, len(data), size):
        yield data[i : i + size]


async def stream_alarm(ws, pcm: bytes, sr: int, ch: int, bits: int):
    """Stream one alarm cycle to the connected client."""
    bytes_per_sec = sr * ch * (bits // 8)
    chunk_duration = CHUNK_SIZE / bytes_per_sec
    pace_delay = chunk_duration * 0.9  # 90% real-time to avoid underrun

    total_chunks = (len(pcm) + CHUNK_SIZE - 1) // CHUNK_SIZE

    start_msg = json.dumps({
        "type": "alarm_start",
        "sample_rate": sr,
        "channels": ch,
        "bits": bits,
    })
    await ws.send(start_msg)
    log.info("Sent alarm_start (%d chunks, pace %.1fms)", total_chunks, pace_delay * 1000)

    for i, chunk in enumerate(chunk_bytes(pcm, CHUNK_SIZE)):
        await ws.send(chunk)
        await asyncio.sleep(pace_delay)

    await ws.send(json.dumps({"type": "alarm_stop"}))
    log.info("Sent alarm_stop")