Akshare 获取日线策略并发送邮件

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import akshare as ak import time # import datetime import numpy as np from datetime import datetime, timedelta import smtplib from email.mime.text import MIMEText from email.utils import formataddr from email.message import EmailMessage import logging import os   nowtime = datetime.now()     day_nums = 1  # 使用前一天的收盘价数据做信号判断 stock_num = 1  # 买入评分最高的前stock_num只股票 可以修改 momentum_day = 20  # 最新动量参考最近momentum_day的 ref_stock = 'sh000300'  # 用ref_stock做择时计算的基础数据 N = 18  # 计算最新斜率slope，拟合度r2参考最近N天 M = 600  # 计算最新标准分zscore，rsrs_score参考最近M天 score_threshold = 0.7  # rsrs标准分指标阈值       def get_index_list(index_symbol='sh000068'):     stocks2 = []     stocks = ak.index_stock_hist(index_symbol).stock_code     for stock in stocks[:]:         if int(stock) < 100000:             stock = 'sz' + stock         else:             stock = 'sh' + stock         stocks2.append(stock)     return stocks2     stock_pool = get_index_list()     # 找到有交易信号的股票，为之后交易进行准备     # 动量因子：由收益率动量改为相对MA90均线的乖离动量 def get_rank(stock_pool):     rank, biasN = [], 90     for stock in stock_pool:         # print(stock)         from_date = '2010-01-01'         from_date = datetime.strptime(from_date, "%Y-%m-%d")         day_nums = 1         current_dt = time.strftime("%Y-%m-%d", time.localtime())         current_dt = datetime.strptime(current_dt, '%Y-%m-%d')         previous_date = current_dt - timedelta(days=day_nums)         #         data = jq.get_price(stock, end_date=previous_date, count=biasN +         #                             momentum_day, frequency='daily', fields=['close'])         try:             data = ak.stock_zh_a_daily(symbol=stock, start_date=from_date, end_date=previous_date)         except:             pass         # print('2222',data.head())         bias = np.array((data.close / data.close.rolling(biasN).mean())[-momentum_day:])  # 乖离因子         #         print(bias)         #         print(bias[0])         score = np.polyfit(np.arange(momentum_day), bias / bias[0], 1)[0].real  # 乖离动量拟合         rank.append([stock, score])     rank.sort(key=lambda x: x[-1], reverse=True)     return rank[0]     # 线性回归：复现statsmodels的get_OLS函数 def get_ols(x, y):     slope, intercept = np.polyfit(x, y, 1)     r2 = 1 - (sum((y - (slope * x + intercept)) ** 2) / ((len(y) - 1) * np.var(y, ddof=1)))     return (intercept, slope, r2)     def get_zscore(slope_series):     mean = np.mean(slope_series)     std = np.std(slope_series)     return (slope_series[-1] - mean) / std     # 择时过程 ----->-------------------------------------------- def initial_slope_series():     current_dt = time.strftime("%Y-%m-%d", time.localtime())     current_dt = datetime.strptime(current_dt, '%Y-%m-%d')     from_date = '2010-01-01'     from_date = datetime.strptime(from_date, "%Y-%m-%d")     previous_date = current_dt - timedelta(days=day_nums)     data = ak.stock_zh_index_daily(symbol=ref_stock)     data['date'] = data['date'].apply(lambda x: str(x))     data['date'] = data['date'].apply(lambda x: datetime.strptime(str(x), '%Y-%m-%d'))     data = data[(data['date'] >= from_date) & (data['date'] <= previous_date)]     return [get_ols(data.low[i:i + N], data.high[i:i + N])[1] for i in range(M)]     # 只看RSRS因子值作为买入、持有和清仓依据，前版本还加入了移动均线的上行作为条件 def get_timing_signal(stock):     current_dt = time.strftime("%Y-%m-%d", time.localtime())     current_dt = datetime.strptime(current_dt, '%Y-%m-%d')     previous_date = current_dt - timedelta(days=day_nums)     from_date = '2010-01-01'     from_date = datetime.strptime(from_date, "%Y-%m-%d")     data = ak.stock_zh_index_daily(symbol=ref_stock)     data['date'] = data['date'].apply(lambda x: str(x))     data['date'] = data['date'].apply(lambda x: datetime.strptime(x, '%Y-%m-%d'))     data['date'] = data['date'].apply(lambda x: x.to_pydatetime())     # data = data[data['date']>=from_date & data['date']<= previous_date]     data = data[(data['date'] >= from_date) & (data['date'] <= previous_date)]     intercept, slope, r2 = get_ols(data.low, data.high)     slope_series.append(slope)     rsrs_score = get_zscore(slope_series[-M:]) * r2     print('rsrs_score {:.3f}'.format(rsrs_score))     if (rsrs_score > score_threshold):         return "BUY"     elif (rsrs_score < -score_threshold):         return "SELL"     else:         return "KEEP"     # slope_series = initial_slope_series()[:-1]  # 除去回测第一天的 slope ，避免运行时重复加入 slope_series = initial_slope_series()[:-1]     def my_trade():     # print(stock_pool)     # print(get_rank(stock_pool))     check_out_list = get_rank(stock_pool)     timing_signal = get_timing_signal(ref_stock)     message = ""     if len(check_out_list) > 0:         each_check_out = check_out_list[0]         #         security_info = jq.get_security_info(each_check_out)         #         stock_name = security_info.display_name         #         stock_code = each_check_out         print('今日自选股:{}({})'.format(each_check_out, each_check_out))         if timing_signal == 'SELL':             #             for stock in list(positions.keys()):             #                 close_position(stock)             #                 message = '清仓！卖卖卖！'             #                 message += "\r\n\r\n".join(positions.keys())             #                 positions.clear()             #                 print('今日择时信号:{}'.format(timing_signal))             pass         else:             message = "今日自选股:{}({})".format(each_check_out, each_check_out)             # adjust_position([each_check_out])         print(message)         sendMail(message)     def mail(message):     ret = True       try:           # 定义SMTP邮件服务器地址         smtp_server = 'smtp.qq.com'         # 邮件发送人邮箱         from_addr = 'x x x x x x x@qq.com'  # 自己的邮想         # 邮件发送人邮箱密码         password = 'xxxxxxxx  # 邮箱密码         # 邮件接收人         to_addr = 'xxxxxxxxxx@qq.com'  # 测试接收邮件地址邮箱           # 创建SMTP连接         conn = smtplib.SMTP_SSL(smtp_server, 465)         # 设计调试级别         conn.set_debuglevel(1)         # 登录邮箱         conn.login(from_addr, password)         # 创建邮件内容对象         msg = EmailMessage()         # 设置邮件内容         msg.set_content('{}'.format(message), 'plain', 'utf-8')         msg['Subject'] = '现在时间为：{}'.format(nowtime)         msg['From'] = '星涅'         msg['To'] = '我挚爱的朋友'         # 发送邮件         conn.sendmail(from_addr, [to_addr], msg.as_string())         # 退出连接         conn.quit()           except Exception as e:  # 如果 try 中的语句没有执行，则会执行下面的 ret = False         ret = False         print(e)       return ret     def sendMail(message):     ret = 0     for _ in range(10):         if ret:             # 邮件发送成功推出             break         else:             # 没有发送成功或失败继续             ret = mail(message)             time.sleep(1)     if __name__ == '__main__':     # positions["159928.XSHE"] = 100     my_trade()