import math
import requests

import pandas as pd
import yfinance as yf
import matplotlib.pyplot as plt
plt.rcParams['font.family'] ='AppleGothic'
plt.rcParams['axes.unicode_minus'] =False

from config import *
from stock_monitor import calculate_technical_indicators, detect_turnaround_signal

# 비트/알트코인 KRW 마켓 식별: 문자열 "-KRW" 포함 여부로 간단 구분

INTERVAL_MAP = {
    60: "60m",  # 1시간 (yfinance)
    240: "4h",  # 4시간 (yfinance)
}

BITHUMB_MAX_COUNT = 3000  # API 최대 3000 캔들


def fetch_coin_history_bithumb(symbol: str, interval_minutes: int, days: int) -> pd.DataFrame:
    """빗썸 API를 이용해 최근 `days`일 코인 데이터 수집 (interval 60 / 240)"""
    if interval_minutes not in (60, 240):
        raise ValueError("Bithumb API only supports 60 or 240 minutes in this helper")

    minutes = interval_minutes
    count = int(math.ceil(days * 24 * 60 / minutes)) + 10  # 여유분 10 캔들
    count = min(count, BITHUMB_MAX_COUNT)

    url = f"https://api.bithumb.com/v1/candles/minutes/{minutes}?market=KRW-{symbol}&count={count}"
    res = requests.get(url, timeout=5)
    res.raise_for_status()
    raw = res.json()

    if not isinstance(raw, list) or len(raw) == 0:
        raise RuntimeError("Empty response from Bithumb API")

    df_temp = pd.DataFrame(raw)
    # API 반환: [timestamp, open, close, high, low, volume] 순
    df_temp = df_temp.sort_index(ascending=False)  # 최신순, 뒤집어서 역순 전달

    data = pd.DataFrame()
    # data.columns = ['datetime', 'open', 'close', 'high', 'low', 'volume']
    # data['datetime'] = pd.to_datetime(data_temp['candle_date_time_kst'])
    data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
    data['Open'] = df_temp['opening_price']
    data['Close'] = df_temp['trade_price']
    data['High'] = df_temp['high_price']
    data['Low'] = df_temp['low_price']
    data['Volume'] = df_temp['candle_acc_trade_volume']
    data = data.set_index('datetime')
    data = data.astype(float)
    data["datetime"] = data.index

    data = data.set_index("datetime").sort_index()  # 시간 오름차순
    return data


def fetch_price_history(symbol: str, interval_minutes: int, days: int = 7) -> pd.DataFrame:
    """최근 `days`일 데이터(캔들)를 가져온다. 코인(-KRW)은 빗썸, 그 외 yfinance."""
    if symbol in KR_COINS:
        base_symbol = symbol.replace("-KRW", "")
        return fetch_coin_history_bithumb(base_symbol, interval_minutes, days)

    # -------- 주식/ETF/해외코인 (yfinance) --------
    if interval_minutes not in INTERVAL_MAP:
        raise ValueError("interval must be 60 or 240")

    interval_str = INTERVAL_MAP[interval_minutes]

    df = yf.download(
        tickers=symbol,
        period=f"{days}d",
        interval=interval_str,
        progress=False,
    )

    if df.empty:
        raise RuntimeError("No data fetched. Check symbol or interval support.")

    return df


def run_simulation(symbol: str, interval_minutes: int, days: int = 7):
    data = fetch_price_history(symbol, interval_minutes, days)
    data = calculate_technical_indicators(data)

    alerts = []  # (timestamp, price)
    # 시계열 순회하며 알림 조건 체크
    for i in range(len(data)):
        slice_df = data.iloc[: i + 1]
        info = detect_turnaround_signal(symbol, slice_df, interval=interval_minutes)
        if info and info["alert"]:
            alerts.append((slice_df.index[-1], slice_df["Close"].iloc[-1]))

    # 모든 매수 신호를 표시
    # 기존 필터 제거하여 전체 기간 매수 신호 사용

    # Plot
    plt.figure(figsize=(12, 6))
    plt.plot(data.index, data["Close"], label="종가", color="black")
    plt.plot(data.index, data["MA5"], label="MA5", color="orange", linewidth=1)
    plt.plot(data.index, data["MA20"], label="MA20", color="blue", linewidth=1)
    plt.plot(data.index, data["MA40"], label="MA40", color="green", linewidth=1)
    # Bollinger Bands
    plt.plot(data.index, data["Upper"], label="볼린저 Upper", color="grey", linestyle="--", linewidth=1)
    plt.plot(data.index, data["Lower"], label="볼린저 Lower", color="grey", linestyle="--", linewidth=1)
    plt.fill_between(data.index, data["Lower"], data["Upper"], color="grey", alpha=0.1)

    if alerts:
        times, prices = zip(*alerts)
        plt.scatter(times, prices, facecolors='none', edgecolors='red', linewidths=2, s=150, zorder=6, label='매수신호')

    plt.title(f"{symbol} – 시뮬레이션 {interval_minutes}분봉 (최근 {days}일)")
    plt.xlabel("날짜")
    plt.ylabel("가격")
    plt.legend()
    plt.grid(True)
    plt.tight_layout()
    plt.show()


if __name__ == "__main__":
    symbol = 'WLD'
    interval = 60
    days = 7
    run_simulation(symbol, interval, days)