import numpy as npimport pandas as pdfrom pylab import pltplt.style.use('seaborn')%matplotlib inlineimport pandas_datareader as pdrstart = '2015-01-01'end = '2019-12-31'data = pdr.get_data_yahoo('6000

先从深交所开始：直接上传源码：from bs4 import BeautifulSoupfrom lxml import etreeimport pandas as pdimport akshare as akimport datetimeimport requestsimport csvfrom contextlib import closingimport timefrom urllib.re

之前直接用pandas库，然后to_excel（），结果直接将原始数据直接覆盖，幸亏有备份。（友善提醒，做数据处理之前，先将数据本地备份一份，确认完全没有问题，然后还是备份一份 ，再进行实盘操作,否则…）import pandas as pdimport numpy as npimport akshare as akfrom openpyxl import load_workbook,Workbo

导入包，获取日期数据import pandas as pdimport numpy as npimport akshare as ak#画图import matplotlib.pyplot as plt#正确显示中文和负号plt.rcParams['font.sans-serif']=['SimHei']plt.rcParams['axes.unicode_minus']=False#处理时间fr

import matplotlib.pyplot as pltfrom pandas import read_excelimport numpy as npimport tushare as tsimport pandas as pdimport datetimetoken=''pro=ts.pro_api(token)获取财务数据#获取财务数据ticker_list = ['601318.SH'

import datetimeimport pandas as pdimport backtrader as btfrom datetime import datetimeimport matplotlibimport akshare as ak%matplotlib inlineclass SmaCross(bt.Strategy):# 全局设定交易策略的参数params = (('pfast'

因为证监会的监管，之前聚宽使用的券商通道被禁止，我们这些技术韭菜不得不寻找其他出路，解决这个重大难题。在和蒋老师深入交流后，终于成功搭建好了聚宽对接qmt的全流程服务。可以提供QMT，Ptrade等专业辅导，交流技术，发送学习礼包。

借助akshare数据源，通过numpy.where函数进行量化回测。

# -*- coding: utf-8 -*-"""Created on Tue Aug4 16:52:23 2020@author: 四屏"""from datetime import datetime%matplotlib inlineimport backtrader as btimport matplotlib.pyplot as pltimport akshare as akplt.rc

链接：https://pan.baidu.com/s/1luBDfprJStMTbBaaojTqBQ?先简单说一下工具，相关代码会在后面免费提供。（如果有别的需要，如技术交流，或者其他的，可以加我微信沟通。使用jqktrader包，然后对于同花顺下单的烦人的验证码，采用Tesseract进行模拟破译。