import json
import os
import sys
import pandas as pd
import numpy as np
from datetime import datetime, timedelta

current_dir = os.path.dirname(os.path.abspath(__file__))
# 如果当前目录不在sys.path中，就添加进去（避免重复添加）
if current_dir not in sys.path:
    sys.path.append(current_dir)
import argparse


from predict_model_v14_profit_maximizer import LotteryPredictorV14Profit

SUM12_ODDS = {
    3: 41.9, 4: 41.9, 18: 41.9, 19: 41.9,
    5: 20.38, 6: 20.38, 16: 20.38, 17: 20.38,
    7: 13.51, 8: 13.51, 14: 13.51, 15: 13.51,
    9: 9.7, 10: 9.7, 12: 9.7, 13: 9.7,
    11: 8.1
}
# 玩法1.1 赔率映射
SIZE_ODDS = {"冠亚大": 2.1, "冠亚小": 1.7}
ODD_EVEN_ODDS = {"冠亚单": 1.7, "冠亚双": 2.1}
NUM_DETAIL_ODDS = 1.9199 * 20
# NUM_DETAIL_ODDS = {"大": 1.9199, "小": 1.9199, "单": 1.9199, "双": 1.9199}
# 玩法2.1/2.2/3 固定赔率
RANK_GLH_ODDS = 1.9199 * 10  # 玩法2.2
NUM_POS_ODDS = 9.599 * 10  # 玩法3

# 总赔率
TOTAL_ODDS = 0
SUM12_ODDS_TOTAL = sum(SUM12_ODDS.values())
SIZE_ODDS_TOTAL = sum(SIZE_ODDS.values())
ODD_EVEN_ODDS_TOTAL = sum(ODD_EVEN_ODDS.values())

TOTAL_ODDS += SUM12_ODDS_TOTAL + SIZE_ODDS_TOTAL + ODD_EVEN_ODDS_TOTAL
TOTAL_ODDS += round(NUM_DETAIL_ODDS + RANK_GLH_ODDS + NUM_POS_ODDS, 4)
# TOTAL_ODDS += round(NUM_DETAIL_ODDS * 20 + RANK_GLH_ODDS * 10 + NUM_POS_ODDS * 10, 4)

EMPTY_TIME_WINDOWS = [
    "06:05:00", "06:10:00", "06:15:00", "06:20:00", "06:25:00", "06:30:00", "06:35:00", "06:40:00", "06:45:00",
    "06:50:00", "06:55:00", "07:00:00",
]
# print(f"总赔率: {TOTAL_ODDS}")
# 1. 加载数据

def get_history_records(data_dirs):
    all_records = []
    for d in data_dirs:
        if not os.path.exists(d): continue
        for f in os.listdir(d):
            if f.endswith('.json') and f != 'stat_result.json':
                with open(os.path.join(d, f), 'r', encoding='utf-8') as file:
                    try:
                        content = json.load(file)
                        if isinstance(content, list):
                            all_records.extend([item for item in content if isinstance(item, dict)])
                    except:
                        continue
    return all_records


def main(next_period_time, df):
    entry = {
        "id": next_period_time.strftime('%Y%m%d%H%M'),
        "time": next_period_time.strftime('%Y-%m-%d %H:%M:%S'),
        "result": {i: {n: None for n in range(1, 11)} for i in range(10)},
        "result_detail": {i: {"单": None, "双": None, "大": None, "小": None} for i in range(10)},
        "winner": {},
        "GD1": {"冠亚大": None, "冠亚小": None},
        "GD2": {"冠亚单": None, "冠亚双": None},
        "GLH_result": {}
    }
    if next_period_time.strftime('%H:%M:%S') in EMPTY_TIME_WINDOWS:
        return entry

    predictor = LotteryPredictorV14Profit()

    next_period_time = pd.to_datetime(next_period_time)
    recent_x = df[df['time'] < next_period_time].tail(10000)
    predictor.check_init_daily_pnl_tracker(next_period_time)
    predictions = predictor.predict(next_period_time, recent_x)

    for pos, nums_bet in predictions.items():
        if not nums_bet:
            continue
        entry['result'][pos] = nums_bet

    last_result = df[df['time'] == next_period_time]
    if last_result.size != 0:
        predictor.update_result(last_result, entry)
    return entry


if __name__ == "__main__":

    data_dirs = ["./history_data", "./current_data"]
    all_records = get_history_records(data_dirs)
    parser = argparse.ArgumentParser(description="下一期时间 next_period_time, 例: 2026-01-02 06:00:00")
    # 必选位置参数（直接传入值，无需前缀）
    parser.add_argument("--next_period_time", type=str, help="下一期时间, 例: 2026-01-02 06:00:00", default="2026-01-02 06:00:00")
    args = parser.parse_args()
    fmt = "%Y-%m-%d %H:%M:%S"
    next_period_time = datetime.strptime(args.next_period_time, fmt)

    df = pd.DataFrame(all_records).drop_duplicates(subset=['id']).sort_values('time')
    df['time'] = pd.to_datetime(df['time'])

    result = main(next_period_time, df)
    print(json.dumps(result, ensure_ascii=False))