#!/usr/bin/env python3
"""Prepare vocab and normalization stats for HAI-style CSV datasets."""

import argparse
import json
from pathlib import Path
from typing import Optional

from data_utils import compute_cont_stats, build_disc_stats, load_split, choose_cont_transforms
from platform_utils import safe_path, ensure_dir, resolve_path

BASE_DIR = Path(__file__).resolve().parent
REPO_DIR = BASE_DIR.parent.parent


def parse_args():
    parser = argparse.ArgumentParser(description="Prepare vocab and normalization stats.")
    parser.add_argument("--config", default=str(BASE_DIR / "config.json"), help="Path to JSON config")
    parser.add_argument("--max-rows", type=int, default=50000, help="Sample cap for stats; ignored when full_stats=true")
    return parser.parse_args()


def resolve_data_paths(cfg: dict, cfg_path: Path) -> list[str]:
    base_dir = cfg_path.parent
    data_glob = cfg.get("data_glob", "")
    data_path = cfg.get("data_path", "")
    paths = []
    if data_glob:
        resolved_glob = resolve_path(base_dir, data_glob)
        paths = sorted(Path(resolved_glob).parent.glob(Path(resolved_glob).name))
    elif data_path:
        resolved_path = resolve_path(base_dir, data_path)
        if Path(resolved_path).exists():
            paths = [Path(resolved_path)]
    return [safe_path(p) for p in paths]


def main():
    args = parse_args()
    config_path = Path(args.config)
    if not config_path.is_absolute():
        config_path = resolve_path(BASE_DIR, config_path)
    if not config_path.exists():
        raise SystemExit(f"missing config: {config_path}")

    cfg = json.loads(config_path.read_text(encoding="utf-8"))
    use_quantile = bool(cfg.get("use_quantile_transform", False))
    quantile_bins = int(cfg.get("quantile_bins", 0)) if use_quantile else None
    full_stats = bool(cfg.get("full_stats", False))
    max_rows: Optional[int] = args.max_rows

    if full_stats:
        max_rows = None

    split_path = resolve_path(config_path.parent, cfg.get("split_path", "./feature_split.json"))
    split = load_split(safe_path(split_path))
    time_col = split.get("time_column", "time")
    cont_cols = [c for c in split["continuous"] if c != time_col]
    disc_cols = [c for c in split["discrete"] if not c.startswith("attack") and c != time_col]

    data_paths = resolve_data_paths(cfg, config_path)
    if not data_paths:
        raise SystemExit(f"no train files found for config: {config_path}")

    transforms, _ = choose_cont_transforms(data_paths, cont_cols, max_rows=max_rows)
    cont_stats = compute_cont_stats(
        data_paths,
        cont_cols,
        max_rows=max_rows,
        transforms=transforms,
        quantile_bins=quantile_bins,
    )
    vocab, top_token = build_disc_stats(data_paths, disc_cols, max_rows=max_rows)

    out_stats = resolve_path(config_path.parent, cfg.get("stats_path", "./results/cont_stats.json"))
    out_vocab = resolve_path(config_path.parent, cfg.get("vocab_path", "./results/disc_vocab.json"))
    ensure_dir(out_stats.parent)
    ensure_dir(out_vocab.parent)

    with open(safe_path(out_stats), "w", encoding="utf-8") as f:
        json.dump(
            {
                "mean": cont_stats["mean"],
                "std": cont_stats["std"],
                "raw_mean": cont_stats["raw_mean"],
                "raw_std": cont_stats["raw_std"],
                "min": cont_stats["min"],
                "max": cont_stats["max"],
                "int_like": cont_stats["int_like"],
                "max_decimals": cont_stats["max_decimals"],
                "transform": cont_stats["transform"],
                "skew": cont_stats["skew"],
                "max_rows": cont_stats["max_rows"],
                "quantile_probs": cont_stats["quantile_probs"],
                "quantile_values": cont_stats["quantile_values"],
                "quantile_raw_values": cont_stats["quantile_raw_values"],
            },
            f,
            indent=2,
        )

    with open(safe_path(out_vocab), "w", encoding="utf-8") as f:
        json.dump({"vocab": vocab, "top_token": top_token, "max_rows": max_rows}, f, indent=2)


if __name__ == "__main__":
    main()