from __future__ import annotations

import json
import subprocess
from pathlib import Path

MAX_SECONDS = 120


def chromaprint(path: Path) -> str | None:
    try:
        p = subprocess.run(
            ["fpcalc", "-length", str(MAX_SECONDS), "-json", str(path)],
            capture_output=True, text=True, timeout=180, check=True,
        )
        return json.loads(p.stdout).get("fingerprint")
    except (OSError, subprocess.SubprocessError, ValueError, json.JSONDecodeError):
        return None


def similarity(a: str, b: str) -> float:
    """Conservative normalized positional similarity for equal-length prefixes."""
    if not a or not b:
        return 0.0
    n = min(len(a), len(b))
    if not n:
        return 0.0
    # Chromaprint JSON fingerprints are comma-separated integer features.
    try:
        aa, bb = [int(x) for x in a.split(",")], [int(x) for x in b.split(",")]
    except ValueError:
        return 0.0
    n = min(len(aa), len(bb))
    if not n:
        return 0.0
    # Feature-wise equality is intentionally conservative. A future backend
    # can replace this with a library-specific fingerprint distance.
    return sum(x == y for x, y in zip(aa[:n], bb[:n])) / n