"""
general_analysis ground truth 타점 MTF 스냅샷 생성.
"""

from __future__ import annotations

import json
from pathlib import Path
from typing import Any

import pandas as pd

from deepcoin.analysis.general_analysis_align import general_analysis_mtf_scores
from deepcoin.analysis.general_analysis_config import (
    DEFAULT_OUTPUT_CSV,
    DEFAULT_TRADES_FILE,
    GENERAL_ANALYSIS_INTERVALS,
)
from deepcoin.analysis.general_analysis_core import interval_tf_prefix
from deepcoin.analysis.general_analysis_pipeline import general_analysis_enrich_bars, general_analysis_snapshot_at_bar
from deepcoin.ground_truth.ground_truth import load_ground_truth


def _prefixed_snap(snap: dict[str, Any], interval: int) -> dict[str, Any]:
    p = interval_tf_prefix(interval)
    return {f"{p}_{k}": v for k, v in snap.items()}


def build_trade_mtf_snapshots(
    frames: dict[int, pd.DataFrame],
    trades: list[dict[str, Any]],
) -> pd.DataFrame:
    """
    모든 타점에 대해 8개 간격 general_analysis 스냅샷.

    Args:
        frames: interval → OHLCV.
        trades: ground_truth trades.

    Returns:
        wide DataFrame (1 row per trade).
    """
    enriched: dict[int, pd.DataFrame] = {}
    for iv in GENERAL_ANALYSIS_INTERVALS:
        raw = frames.get(iv)
        if raw is None or raw.empty:
            continue
        print(f"  [GA] {interval_tf_prefix(iv)} 봉 지표 계산 ({len(raw)}봉)...")
        enriched[iv] = general_analysis_enrich_bars(raw, iv, full_context=True)

    rows: list[dict[str, Any]] = []
    for i, t in enumerate(sorted(trades, key=lambda x: x["dt"])):
        ts = pd.Timestamp(t["dt"])
        row: dict[str, Any] = {
            "trade_idx": i,
            "dt": t["dt"],
            "action": t["action"],
            "price": t["price"],
            "weight": t.get("weight", 1.0),
            "leg_id": t.get("leg_id", 0),
            "memo": t.get("memo", ""),
        }
        flat: dict[str, Any] = {}
        for iv in GENERAL_ANALYSIS_INTERVALS:
            ef = enriched.get(iv)
            if ef is None:
                continue
            snap = general_analysis_snapshot_at_bar(ef, ts, iv)
            flat.update(_prefixed_snap(snap, iv))
        row.update(flat)
        row.update(general_analysis_mtf_scores(flat))
        rows.append(row)
        if (i + 1) % 50 == 0:
            print(f"  타점 스냅샷 {i + 1}/{len(trades)}")

    return pd.DataFrame(rows)


def export_trade_snapshots(
    frames: dict[int, pd.DataFrame],
    trades_path: Path | str = DEFAULT_TRADES_FILE,
    output_csv: Path | str = DEFAULT_OUTPUT_CSV,
) -> Path:
    """
    CSV로 타점 MTF 스냅샷 저장.

    Returns:
        저장 경로.
    """
    data = load_ground_truth(Path(trades_path))
    if not data:
        raise FileNotFoundError(f"정답 파일 없음: {trades_path}")
    trades = data.get("trades") or []
    print(f"타점 {len(trades)}건 × {len(GENERAL_ANALYSIS_INTERVALS)} TF general_analysis")
    df = build_trade_mtf_snapshots(frames, trades)
    out = Path(output_csv)
    out.parent.mkdir(parents=True, exist_ok=True)
    df.to_csv(out, index=False, encoding="utf-8-sig")
    print(f"저장: {out} ({len(df)}행 × {len(df.columns)}열)")
    return out