"""
铝金属价格数据服务

提供铝金属的当前价格和历史价格走势数据。
数据来源优先级：
1. 外部API（预留接口）
2. 模拟真实走势数据（当前使用）

数据基于上海期货交易所(SHFE)铝期货价格走势特征生成。
"""
import random
import hashlib
from datetime import datetime, timedelta
from typing import List, Dict, Optional


BASE_PRICE = 18950.0
PRICE_VOLATILITY = 120.0
TREND_DRIFT = 0.3


def _daily_seed(date_str: str) -> float:
    h = hashlib.md5(date_str.encode()).hexdigest()
    seed = int(h[:8], 16) / (16 ** 8)
    return seed


def get_aluminum_current_price() -> Dict:
    today = datetime.now().strftime("%Y-%m-%d")
    seed = _daily_seed(today)
    random.seed(int(seed * 1_000_000))

    price = BASE_PRICE + (seed - 0.5) * PRICE_VOLATILITY * 2
    price = round(price, 0)

    yesterday = (datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d")
    prev_seed = _daily_seed(yesterday)
    prev_price = BASE_PRICE + (prev_seed - 0.5) * PRICE_VOLATILITY * 2
    prev_price = round(prev_price, 0)

    change = price - prev_price
    change_percent = round((change / prev_price) * 100, 2)

    week_ago = (datetime.now() - timedelta(days=7)).strftime("%Y-%m-%d")
    week_seed = _daily_seed(week_ago)
    week_price = BASE_PRICE + (week_seed - 0.5) * PRICE_VOLATILITY * 2

    random.seed()

    return {
        "price": price,
        "unit": "元/吨",
        "currency": "CNY",
        "date": today,
        "change": round(change, 0),
        "change_percent": change_percent,
        "open": round(price - random.uniform(10, 50), 0),
        "high": round(price + random.uniform(10, 60), 0),
        "low": round(price - random.uniform(10, 60), 0),
        "prev_close": prev_price,
        "week_ago_price": round(week_price, 0),
    }


def get_aluminum_price_history(days: int = 30) -> List[Dict]:
    history = []
    random.seed(42)

    price_line = BASE_PRICE
    for i in range(days, -1, -1):
        date = (datetime.now() - timedelta(days=i)).strftime("%Y-%m-%d")
        date_seed = _daily_seed(date)

        drift = (date_seed - 0.5) * TREND_DRIFT
        noise = (date_seed - 0.5) * PRICE_VOLATILITY * 1.5
        price_line = price_line + drift + noise * 0.3
        price_line = max(18200, min(19800, price_line))

        open_price = round(price_line + (date_seed - 0.5) * 80, 0)
        high_price = round(open_price + abs(date_seed - 0.5) * 160, 0)
        low_price = round(open_price - abs(date_seed - 0.5) * 140, 0)
        close_price = round(price_line, 0)

        history.append({
            "date": date,
            "open": open_price,
            "high": high_price,
            "low": low_price,
            "close": close_price,
        })

    random.seed()
    return history