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import pandas as pdimport numpy as np# 创建BOLL线def get_high_low(df: pd.DataFrame) -> list:# 用最高价和最低价构建新的数据，用于显示和判断是否突破BOLL线支撑位、压力位high_low = []for i in df.index:if df['High'][i] > df['阻力线'][i]:hi
import osimport pandas as pdfrom pandas import Timedeltafrom stock_c.csv2dataframe import import_csv# 用通达信小周期，生成大周期数据def csv_resample(df, rule) -> pd.DataFrame:# 重新采样Open列数据df_open = round(df['Open
import numpy as npimport pandas as pd# 期货策略类，包括开仓、买入、止盈、止损方法与策略执行主函数class StockStrategy:df = Noneopen_offset_num = 5buy_in_offset_num = 0stop_win_offset_num = 0stop_lose_num = 0price_list = []price_st
import structimport datetimeimport mathimport time# 根据二进制前两段拿到日期分时def get_date_str(H1, H2):year = math.floor(H1 / 2048) + 2004month = math.floor(H1 % 2048 / 100)day = H1 % 2048 % 100hour = math.floor(
import structimport datetimeimport mathimport time# 根据二进制前两段拿到日期分时def get_date_str(H1, H2):year = math.floor(H1 / 2048) + 2004month = math.floor(H1 % 2048 / 100)day = H1 % 2048 % 100hour = math.floor(
import structimport datetimeimport mathimport time# 根据二进制前两段拿到日期分时def get_date_str(H1, H2):year = math.floor(H1 / 2048) + 2004month = math.floor(H1 % 2048 / 100)day = H1 % 2048 % 100hour = math.floor(