import core.logger as logging from datetime import datetime from time import sleep import pandas as pd from core.biz.market_data import MarketData from core.trade.ma_break_statistics import MaBreakStatistics from core.db.db_market_data import DBMarketData from core.biz.metrics_calculation import MetricsCalculation from core.utils import ( datetime_to_timestamp, timestamp_to_datetime, transform_date_time_to_timestamp, ) from trade_data_main import TradeDataMain from config import ( API_KEY, SECRET_KEY, PASSPHRASE, SANDBOX, OKX_MONITOR_CONFIG, MYSQL_CONFIG, BAR_THRESHOLD, ) logger = logging.logger class TradeMaStrategyMain: def __init__( self, is_us_stock: bool = False, is_binance: bool = False, commission_per_share: float = 0, ): self.ma_break_statistics = MaBreakStatistics( is_us_stock=is_us_stock, is_binance=is_binance, commission_per_share=commission_per_share, ) def batch_ma_break_statistics(self): """ 批量计算MA突破统计 """ logger.info("开始批量计算MA突破统计") strategy_dict = self.ma_break_statistics.main_strategy account_value_chg_df_list = [] for strategy_name, strategy_info in strategy_dict.items(): if "macd" in strategy_name: # 只计算macd策略 account_value_chg_df = self.ma_break_statistics.batch_statistics( strategy_name=strategy_name ) account_value_chg_df_list.append(account_value_chg_df) total_account_value_chg_df = pd.concat(account_value_chg_df_list) return total_account_value_chg_df def statistics_account_value_chg(self, account_value_chg_df: pd.DataFrame): logger.info("开始统计account_value_chg") if __name__ == "__main__": commission_per_share_list = [0, 0.0008] for commission_per_share in commission_per_share_list: trade_ma_strategy_main = TradeMaStrategyMain( is_us_stock=False, is_binance=True, commission_per_share=commission_per_share, ) trade_ma_strategy_main.batch_ma_break_statistics()