调整py脚本

PyModel/batch_predict_betting_v8.py

@@ -0,0 +1,114 @@
+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') 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'])
+
+    print(main(next_period_time, df))
+
+