#!/usr/bin/env python3
"""1단계: 연속 매수·매도 클러스터별 매수·매도 비율 튜닝 (타점 고정)."""

from __future__ import annotations

import argparse
import json
import logging
import sys
from pathlib import Path

ROOT = Path(__file__).resolve().parents[1]
SRC = ROOT / "src"
if str(SRC) not in sys.path:
    sys.path.insert(0, str(SRC))

from bithumb.config import load_settings
from bithumb.ground_truth.sizing_rules import save_sizing_rules
from bithumb.ground_truth.sizing_tune import tune_sizing_rules
from bithumb.operations.signal_pipeline import run_signal_pipeline


def _configure_logging(verbose: bool) -> None:
    level = logging.DEBUG if verbose else logging.INFO
    logging.basicConfig(
        level=level,
        format="%(asctime)s [%(levelname)s] %(message)s",
        datefmt="%Y-%m-%d %H:%M:%S",
    )


def main() -> int:
    """CLI 진입점."""
    parser = argparse.ArgumentParser(
        description="연속 매수·매도 클러스터 상태별 사이징 비율 학습",
    )
    parser.add_argument(
        "-o",
        "--output",
        type=str,
        default=None,
        help="규칙 JSON 경로 (기본: OPS_SIZING_RULES_JSON)",
    )
    parser.add_argument(
        "--min-bucket-samples",
        type=int,
        default=5,
        help="클러스터 버킷별 최소 샘플 수",
    )
    parser.add_argument("-v", "--verbose", action="store_true")
    args = parser.parse_args()
    _configure_logging(args.verbose)

    settings = load_settings()
    output_path = Path(args.output) if args.output else settings.ops_sizing_rules_json
    if not output_path.is_absolute():
        output_path = ROOT / output_path

    print("\n=== 매수·매도 비율 튜닝 (타점 고정) ===", flush=True)
    print(
        f"기법: {settings.ops_technique_id} · sim {settings.gt_sim_lookback_days}일 · "
        f"기본 {settings.ops_buy_cash_pct:.0%}/{settings.ops_sell_coin_pct:.0%}",
        flush=True,
    )

    pipeline = run_signal_pipeline(settings, use_cache=True)
    rules, final_sim = tune_sizing_rules(
        settings,
        pipeline["kept"],
        data_end=pipeline["data_end"],
        last_mark_price=pipeline["last_price"],
        technique_id=pipeline["technique_id"],
        min_bucket_samples=args.min_bucket_samples,
    )
    save_sizing_rules(rules, output_path)

    tuning = rules.get("tuning") or {}
    print(f"\n기준(고정 10%): {tuning.get('baseline_return_pct'):+.2f}%")
    print(
        f"학습 후: {final_sim.get('total_return_pct'):+.2f}% · "
        f"매수/매도 {final_sim.get('buys_executed')}/{final_sim.get('sells_executed')}"
    )
    print(
        f"전역 비율: 매수 {rules.get('default_buy_cash_pct', 0):.0%} · "
        f"매도 {rules.get('default_sell_coin_pct', 0):.0%}"
    )
    by_cluster = rules.get("by_cluster") or {}
    if by_cluster.get("buy") or by_cluster.get("sell"):
        print("클러스터별:")
        print(json.dumps(by_cluster, ensure_ascii=False, indent=2))
    print(f"\n규칙 JSON: {output_path}")
    return 0


if __name__ == "__main__":
    raise SystemExit(main())