"""Waveform peak extraction for timeline display (AUD-05)."""
import subprocess
from pathlib import Path

import numpy as np
import soundfile as sf


def extract_peaks(path: str, num_peaks: int = 1000) -> list[float]:
    """Extract downsampled peak amplitudes from audio file.

    Returns a list of floats (0.0-1.0) representing peak amplitude per chunk.
    Handles MP3 via ffmpeg subprocess (libsndfile doesn't support MP3).

    Args:
        path: Absolute path to audio file
        num_peaks: Number of peak samples to return (default 1000)

    Returns:
        List of float peak values, length <= num_peaks
    """
    p = Path(path)
    if p.suffix.lower() == ".mp3":
        return _extract_peaks_mp3(path, num_peaks)
    return _extract_peaks_soundfile(path, num_peaks)


def _extract_peaks_soundfile(path: str, num_peaks: int) -> list[float]:
    """Extract peaks using soundfile (WAV, FLAC, OGG)."""
    data, _ = sf.read(path, always_2d=True)
    mono = np.mean(data, axis=1)
    return _downsample_peaks(mono, num_peaks)


def _extract_peaks_mp3(path: str, num_peaks: int) -> list[float]:
    """Extract peaks from MP3 via ffmpeg pipe to float32 PCM."""
    cmd = [
        "ffmpeg", "-i", path,
        "-f", "f32le", "-ar", "44100", "-ac", "1",
        "pipe:1", "-loglevel", "quiet",
    ]
    result = subprocess.run(cmd, capture_output=True, timeout=60)
    if result.returncode != 0:
        raise RuntimeError(f"ffmpeg failed for {path}: exit code {result.returncode}")
    mono = np.frombuffer(result.stdout, dtype=np.float32)
    return _downsample_peaks(mono, num_peaks)


def _downsample_peaks(mono: np.ndarray, num_peaks: int) -> list[float]:
    """Downsample mono audio to peak amplitude array."""
    if len(mono) == 0:
        return []
    chunk_size = max(1, len(mono) // num_peaks)
    peaks = []
    for i in range(0, len(mono), chunk_size):
        chunk = mono[i : i + chunk_size]
        peaks.append(float(np.max(np.abs(chunk))))
    return peaks[:num_peaks]