"""분봉 OHLCV → 5-level 모멘텀 분류."""
from __future__ import annotations
from collections import deque

# 분류 카테고리
STRONG_UP = "strong_up"
WEAK_UP = "weak_up"
NEUTRAL = "neutral"
WEAK_DOWN = "weak_down"
STRONG_DOWN = "strong_down"

_BARS_PER_5MIN = 5
_LOOKBACK_5MIN_BARS = 5
_VOLUME_AVG_WINDOW = 12  # 60분 = 5분봉 12개


def aggregate_1min_to_5min(minute_bars: list[dict]) -> list[dict]:
    """1분봉 N개 → 5분봉 floor(N/5) 개. 시간 오름차순.

    각 5분봉: open=첫 1분봉 open, high=max, low=min, close=마지막 close, volume=sum.
    """
    bars_5min = []
    chunks = len(minute_bars) // _BARS_PER_5MIN
    for i in range(chunks):
        chunk = minute_bars[i * _BARS_PER_5MIN : (i + 1) * _BARS_PER_5MIN]
        bars_5min.append({
            "datetime": chunk[0]["datetime"],
            "open": chunk[0]["open"],
            "high": max(b["high"] for b in chunk),
            "low": min(b["low"] for b in chunk),
            "close": chunk[-1]["close"],
            "volume": sum(b["volume"] for b in chunk),
        })
    return bars_5min


def classify_minute_momentum(minute_bars: deque) -> str:
    """1분봉 deque → 5-level 모멘텀 분류.

    Returns: STRONG_UP / WEAK_UP / NEUTRAL / WEAK_DOWN / STRONG_DOWN
    """
    minute_list = list(minute_bars)
    if len(minute_list) < _BARS_PER_5MIN * _LOOKBACK_5MIN_BARS:
        return NEUTRAL  # 데이터 부족

    bars_5min = aggregate_1min_to_5min(minute_list)
    if len(bars_5min) < _LOOKBACK_5MIN_BARS:
        return NEUTRAL

    recent = bars_5min[-_LOOKBACK_5MIN_BARS:]
    up_count = sum(1 for b in recent if b["close"] > b["open"])

    # 거래량 multiplier: recent 5 avg vs 60분 avg
    recent_vol_avg = sum(b["volume"] for b in recent) / len(recent)
    long_window = bars_5min[-_VOLUME_AVG_WINDOW:]
    long_vol_avg = sum(b["volume"] for b in long_window) / len(long_window)
    vol_mult = recent_vol_avg / long_vol_avg if long_vol_avg > 0 else 1.0

    # 5-level 분류
    if up_count == 5 and vol_mult >= 1.5:
        return STRONG_UP
    elif up_count >= 3 and vol_mult >= 1.0:
        return WEAK_UP
    elif up_count == 0 and vol_mult >= 1.5:
        return STRONG_DOWN
    elif up_count <= 2 and vol_mult < 1.0:
        return WEAK_DOWN
    else:
        return NEUTRAL
