北向资金分析工具.py

'''
author by :newhackerman@163.com
申明：根据此程序分析做出的买卖，本人不承担投资损失，投资有风险，买卖需谨慎！！
'''

import sys
import webbrowser  # 打开浏览器
import struct as st #编码解码
import matplotlib.gridspec as gridspec  # 分割子图
import matplotlib.pyplot as plt
import mpl_finance as mpf  # python中可以用来画出蜡烛图、线图的分析工具，目前已经从matplotlib中独立出来，非常适合用来画K线
import numpy as np
import pandas  as pd
import prettytable as pt  # 格式化成表格输出到html文件
from util.WriteToTDX import *
from util.checkStock import * #检查个股风险项
from dateutil.relativedelta import relativedelta
from pyecharts import options as opts
from pyecharts.charts import Page, Line
from optparse import OptionParser
from TradeDay import tradeday
from dboprater import DB as db
'''手动安装 talib 去https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib 下载对应的版本“TA_Lib‑0.4.19‑cp37‑cp37m‑win_amd64.whl”  然后 pip3 install TA_Lib‑0.4.19‑cp37‑cp37m‑win_amd64.whl'''


# import  talib   #Technical Analysis Library”, 即技术分析库 是Python金融量化的高级库，涵盖了150多种股票、期货交易软件中常用的技术分析指标，如MACD、RSI、KDJ、动量指标、布林带等等。
# import numpy as np
# import matplotlib.pyplot as plt
# import matplotlib.gridspec as gridspec#分割子图
# import mpl_finance as mpf        # python中可以用来画出蜡烛图、线图的分析工具，目前已经从matplotlib中独立出来，非常适合用来画K线

class NorthwardAnalysis():
    database = 'stock'
    tablename = 'northdataAnaly'
    configfile = './config/mysqlconfig.json'
    percentDpath = 'C:\\十档行情\\T0002\\signals\\signals_user_9602\\'
    oneTrunDpath='C:\\十档行情\\T0002\\signals\\signals_user_9604\\'
    pro=None
    jsoncontent=None
    stockcode=''
    def __init__(self):
        self.jsoncontent=db.get_config()
        self.pro = ts.pro_api(self.jsoncontent['tushare'])

    #########编码成通达信可识别的数据
    def stockEncode(self,HdDate, SCode):
        seek = 4
        text1 = st.pack('I', int(HdDate))
        # print(text1)
        text2 = st.pack('f', float(SCode))
        # print(text2)
        return text1 + text2

    def get_optparse(self):
        parser = OptionParser()
        parser.add_option("-1", "--updatedata", type='int', dest="1", help="数据更新")
        parser.add_option("-2", "--top10inscrese", type='int', dest="2", help="当日持股变动最大前10股票查询")
        parser.add_option("-3", "--northbuy", type='int', dest="3", help="南资开始净买股票查询")
        parser.add_option("-4", "--stockview", type='int', dest="4", help="个股南资数据展示（输入名称或代码）")
        parser.add_option("-5", "--F10", type='int', dest="5", help="打开个股F0（输入名称代码）")
        parser.add_option("-6", "--stockbuybank", type='int', dest="6", help="个股持股比例Top10经纪商查询")
        parser.add_option("-7", "--7", type='int', dest="7", help="北资一键写通达信")
        parser.add_option("-8", "--8", type='int', dest="8", help="检查个股是否暴雷")
        parser.add_option("-0", "--0", type='int', dest="store", help="退出")
        parser.add_option("-q", "--quiet",action="store_false", dest="verbose", default=True,help="don't print status messages to stdout")
        (options, args) = parser.parse_args()
        return options, args

    def get_proxy(self):
        url='https://ip.jiangxianli.com/api/proxy_ip'
        try:
            r=req.get(url=url)
        except BaseException as b:
            count=0
            while True:
                count += 1
                try:
                    r = req.get(url=url)
                    if r.status_code!=200:
                        continue
                    else:
                        break
                    if count>=3:
                        break
                except BaseException as c:
                    continue
        jsontext = r.json()['data']
        ip = jsontext['ip']
        port = jsontext['port']
        protocol = jsontext['protocol']
        proxy = {str(protocol).lower(): str(protocol).lower() + '://' + ip + ':' + port}
        return proxy

    ###################处理个股北资占比数据写通达信文件
    def writeNorthDataPercentToTdx(self,listdata, percentDpath,SCode):
        #确定要写的目标文件名：
        if SCode[0:2] == '60' or SCode[0:3] == '688' or SCode[0:3] == '880':
            dfilename = percentDpath + '1_' + SCode + '.dat'
        elif SCode[0:3] == '300' or SCode[0:2] == '00':
            dfilename = percentDpath + '0_' + SCode + '.dat'
        fw1 = open(dfilename, 'wb')
        templist=[]
        for tempdata in listdata:
            for row in tempdata:  # 依次获取每一行数据
                jsdata = json.loads(row)
                HdDate = str(jsdata['HDDATE'])[0:10]
                HdDate = datetime.datetime.strptime(HdDate, '%Y-%m-%d').strftime('%Y%m%d')
                SCode = str(jsdata['SCODE'])
                SharesRate = jsdata['SHARESRATE']
                SHAREHOLDPRICEONE=format(jsdata['SHAREHOLDPRICEONE'] / 100000000, '.3f')
                dict={'HdDate':HdDate,'SharesRate':SharesRate,'SHAREHOLDPRICEONE':SHAREHOLDPRICEONE}
                templist.append(dict)
        templist=templist[::-1] #list 反向（由于取的数据默认是降序，但写入通达信需要升序）
        for line in templist:
            HdDate=line['HdDate']
            SharesRate=line['SharesRate']
            fflowdata = self.stockEncode(HdDate, SharesRate)
            fw1.write(fflowdata)
        fw1.close()
        print('文件：%s 写入成功!' %dfilename)

    ###################处理个股北资持股市变到写通达信文件
    def writeNorthDataOneTrunToTdx(self, listdata, oneTrunDpath, SCode):
        # 确定要写的目标文件名：
        if SCode[0:2] == '60' or SCode[0:3] == '688' or SCode[0:3] == '880':
            dfilename = oneTrunDpath + '1_' + SCode + '.dat'
        elif SCode[0:3] == '300' or SCode[0:2] == '00':
            dfilename = oneTrunDpath + '0_' + SCode + '.dat'
        fw1 = open(dfilename, 'wb')
        templist = []
        for tempdata in listdata:
            for row in tempdata:  # 依次获取每一行数据
                jsdata = json.loads(row)
                HdDate = str(jsdata['HDDATE'])[0:10]
                HdDate = datetime.datetime.strptime(HdDate, '%Y-%m-%d').strftime('%Y%m%d')
                SCode = str(jsdata['SCODE'])
                SharesRate = jsdata['SHARESRATE']
                SHAREHOLDPRICEONE = format(jsdata['SHAREHOLDPRICEONE'] / 100000000, '.3f')
                dict = {'HdDate': HdDate, 'SharesRate': SharesRate, 'SHAREHOLDPRICEONE': SHAREHOLDPRICEONE}
                templist.append(dict)
        templist = templist[::-1]  # list 反向（由于取的数据默认是降序，但写入通达信需要升序）
        for line in templist:
            HdDate = line['HdDate']
            SHAREHOLDPRICEONE = line['SHAREHOLDPRICEONE']
            fflowdata = self.stockEncode(HdDate, SHAREHOLDPRICEONE)
            fw1.write(fflowdata)
        fw1.close()
        print('文件：%s 写入成功!' % dfilename)
    # 获取最新的数据日期
    def get_page_newdate(self):
        url = 'http://dcfm.eastmoney.com/em_mutisvcexpandinterface/api/js/get?&type=HSGTTRDT&st=DATE&sr=-1&token=894050c76af8597a853f5b408b759f5d&p=1&ps=1'
        headers = {
            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.111 Safari/537.36'}
        response = req.get(url=url, headers=headers).text
        regx='(\d{4}-\d{2}-\d{2})'
        date = re.findall(regx, response,re.M)[0]
        return str(date)


    ###获取股票代码
    def get_stockcode(self,stockname):
        if stockname.isdigit():  # 如果输入的是代码
            return stockname
        else:
            stockdata = pd.DataFrame(
                self.pro.stock_basic(exchange='', list_status='L', fields='ts_code,symbol,name,area,industry,list_date'))
            # print(stockdata)
            for stock in stockdata.iterrows():
                # print(stock)
                if stockname == stock[1]['name']:
                    # print(stock[1]['name'])
                    # print(str(stock[1]['ts_code'])[0:6])
                    return str(stock[1]['ts_code'])[0:6]
                else:
                    continue

    # 写文件
    def WriteFile(self, northdataAnalyinfos,Hddate):
        data=str(northdataAnalyinfos)
        southdatafile = '北向资金数据_%s.txt' %Hddate
        with open(southdatafile, 'w', encoding='utf-8') as fw:
            fw.write(data)

    # 获取个股北向资金数据
    def getnorth(self,code):
        url = 'http://dcfm.eastmoney.com//em_mutisvcexpandinterface/api/js/get'
        northdataAnalyinfos = []
        headers = {
            'Accept': '*/*',
            'Accept-Encoding': 'gzip, deflate',
            'Accept-Language': 'zh - CN, zh;    q = 0.9, en;    q = 0.8    ',
            'Connection': 'keep-alive',
            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.111 Safari/537.36',
            'Cookie': 'pgv_pvi=3794568192; _qddaz=QD.6ofmf2.j6jr4m.kat8wucp; ct=u_GCXp_V0BUfw6EE3hFHtqMglz3afgkppJcv5vbFImFCEcWBrdbJ1czxMgSRvdgdMHMxnKracqlOZgxC4VNfwrkiwCCnYCNVFUzHMie-NyeUGcc8-NdJwvaXLimNiEt9gsOQO3q161JU2fTSAHZYRo5byr67JKvMwuA_2qSbhls; ut=FobyicMgeV5ghfUPKWOH5wak5fe7PCdYa2maZFrymrOdfN-wAEFtpNp1MzH070EBSmKRLG6vmIcYwEk2SvuUDiGwHB7BHzpaN3m4xMthhPoNqi89FTByaNH4MkRCfEYW4JX960vY0ITlmRY-cPk1PQzTvxCYnVj0Ey0NtYOnUdj24K9O1_tKWeyEDf1k_bIV6hcX360Qn8yYsWTrETZTzGYR7tn62AgnDFAq58DbSa3StLkggc5c7wB94try8c_WEpaHHyl5rA7BBAJZkje3dZ7Q7pZSUWri; pi=3323115305075326%3bc3323115305075326%3b%e8%82%a1%e5%8f%8bjHWZa22110%3bAc4gMB%2bahzpZU8kVvDCm4%2f9QLFcpRepVrDlj4DSAFvQS9L41u5PjbhW1g0ATNFBs2U6jdaiAi0v97coryIUwYaBWyHAUTbi1GDBZdDmkrBugnCGTBDTgPjXURUbrtmze597viYIL2RjHQTBKDzTIQqxuco%2b4pIMvD3B%2f2gF3Z2HSKCRGXGX%2bMcFxewJmIXD8wOJYtqii%3bM4Rnsdjx0lNLDrlCNBv6VhW13wgvkjpsoKd52WM1JsrPCSqUd%2fySTvks6nwUjCNsGby4fYU2Y%2bbjGtRBVly22B%2bqdAhoqGh6XrZIWQGX4LDnpd4CKtckek2Rlq7r9qjcQSdzcprF%2bmmkr9EqKBQVnmt9ppYRhg%3d%3d; uidal=3323115305075326%e8%82%a1%e5%8f%8bjHWZa22110; sid=126018279; _ga=GA1.2.1363410539.1596117007; em_hq_fls=js; AUTH_FUND.EASTMONEY.COM_GSJZ=AUTH*TTJJ*TOKEN; emshistory=%5B%22%E4%BA%BA%E6%B0%94%E6%8E%92%E8%A1%8C%E6%A6%9C%22%2C%22%E6%AF%94%E4%BA%9A%E8%BF%AA%E4%BA%BA%E6%B0%94%E6%8E%92%E5%90%8D%22%2C%22%E5%9F%BA%E9%87%91%E6%8E%92%E8%A1%8C%22%2C%22%E8%BF%913%E4%B8%AA%E6%9C%88%E8%B7%8C%E5%B9%85%E6%9C%80%E5%A4%A7%E7%9A%84%E5%9F%BA%E9%87%91%22%2C%22%E5%85%BB%E8%80%81%E9%87%91%E6%8C%81%E8%82%A1%E5%8A%A8%E5%90%91%E6%9B%9D%E5%85%89%22%2C%22%E5%A4%96%E7%9B%98%E6%9C%9F%E8%B4%A7%22%2C%22A50%22%2C%22%E6%81%92%E7%94%9F%E6%B2%AA%E6%B7%B1%E6%B8%AF%E9%80%9A%E7%BB%86%E5%88%86%E8%A1%8C%E4%B8%9A%E9%BE%99%E5%A4%B4A%22%2C%22%E7%BB%86%E5%88%86%E8%A1%8C%E4%B8%9A%E9%BE%99%E5%A4%B4%22%5D; vtpst=%7c; HAList=d-hk-00288%2Cd-hk-00772%2Cf-0-399006-%u521B%u4E1A%u677F%u6307%2Ca-sz-002008-%u5927%u65CF%u6FC0%u5149%2Ca-sz-002739-%u4E07%u8FBE%u7535%u5F71%2Cf-0-000001-%u4E0A%u8BC1%u6307%u6570%2Cd-hk-00981%2Ca-sz-002082-%u4E07%u90A6%u5FB7%2Ca-sz-300511-%u96EA%u6995%u751F%u7269; st_si=85201197981579; cowCookie=true; waptgshowtime=2021121; qgqp_b_id=3a2c1ce1f45a81a3fa7cc2fbad8e2a24; st_asi=delete; intellpositionL=581px; st_pvi=03400063938128; st_sp=2020-05-23%2013%3A48%3A35; st_inirUrl=https%3A%2F%2Fwww.baidu.com%2Flink; st_sn=60; st_psi=2021012310245852-113300303605-1019447906; intellpositionT=2133.55px'
        }
        print(code)
        params = {'type': 'HSGTHDSTA',
                  'token': '70f12f2f4f091e459a279469fe49eca5',
                  'filter': ' (SCODE=\'' + code + '\')',
                  'st': 'HDDATE',
                  'sr': -1,
                  'p': 1,
                  'ps': 50,
                  'js': 'var nLvHRzKi={pages:(tp),data:(x)}',
                  'rt': '53732197'}
        # print(params)
        try:
            response = req.get(url=url, headers=headers, params=params)
        except BaseException as BE:
            response = req.get(url=url, headers=headers, params=params,proxies=self.get_proxy())
            if response.status_code!=200:
                print('访问异常，请重试！')
                exit(1)
        response=response.text
        #print(response)
        regex = r'data:\[({.*?)]}'
        jsondata = re.findall(regex, response)
        #print(jsondata)
        data = str(jsondata).replace('[\'','',-1).replace('\']','',-1).replace('},', '}},', -1).split('},',-1)
        northdataAnalyinfos.append(data)
        if northdataAnalyinfos is None:
            return None
        else:
        #self.WriteFile(listdata)
            return northdataAnalyinfos


    # 按条件查询比例与持股市值
    def selectdb(self, **kwords):  # **kwords :表示可以传入多个键值对， *kwords:表示可传入多个参数
        conditions = str(kwords).strip('{').strip('}').replace(':', '=', 1).replace('\'', '', 2)
        print(conditions)
        conn = db.dbconnect()
        cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
        # 执行的sql语句
        sql = '''select HDDATE,SCODE,SNAME,SHAREHOLDSUM,SHARESRATE,CLOSEPRICE,ZDF ,SHAREHOLDPRICE ,SHAREHOLDPRICEONE ,SHAREHOLDPRICEFIVE ,SHAREHOLDPRICETEN from  northdataAnaly  '''
        sql = sql + 'where ' + conditions + '  order by HDDATE '
        print(sql)
        cursor.execute(sql)
        resultset = cursor.fetchall()
        cursor.close()
        conn.close()
        if resultset:
            return resultset
        else:
            print('未查询到数据')
            return None

    # 查询当最后一个交易日净买前10
    def Select_top10(self):  # **kwords :表示可以传入多个键值对， *kwords:表示可传入多个参数
        header = ['日期', '代码','名称','持股数量', '持股占比','收盘价' , '涨跌幅', '持股市值亿', '一日持股变动亿','五日持股变动亿','十日持股变动亿']
        newdate = self.get_page_newdate()
        print (newdate)
        # outdate = datetime.datetime.strptime(newdate, "%Y-%m-%d")
        # yesterday = str((outdate + datetime.timedelta(days=-1)).strftime("%Y-%m-%d"))
        sql = 'select * from northdataAnaly where Hddate=\'' + newdate + '\' order by SHAREHOLDPRICEONE desc limit 10'
        # print(sql)
        conn = db.dbconnect()
        cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
        cursor.execute(sql)
        resultset = cursor.fetchall()
        # print(resultset)
        if resultset:
            return resultset
        else:
            print('数据不是最新，请更新数据！')
            # return None
        cursor.close()
        conn.close()
        return resultset

    # 查询开始净买入个股
    def Select_Netpurchases(self):  # **kwords :表示可以传入多个键值对， *kwords:表示可传入多个参数
        header = ['日期', '代码','名称','持股数量', '持股占比','收盘价' , '涨跌幅', '持股市值亿', '一日持股变动亿','五日持股变动亿','十日持股变动亿']
        newdate = self.get_page_newdate()
        outdate = datetime.datetime.strptime(newdate, "%Y-%m-%d")
        yesterday=tradeday.getyestodayTradeday(outdate)
        sql = 'select * from northdataAnaly where hddate=\'' + newdate + '\'and SHAREHOLDPRICEONE>5 and SHAREHOLDPRICEFIVE>1 and Zdf >-2 and SCode in ( select SCode from northdataAnaly where hddate=\'' + yesterday + '\' and SHAREHOLDPRICEONE<0 )  order by SHAREHOLDPRICEONE desc'
        # print(sql)
        conn = db.dbconnect()
        cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
        # print(sql)
        cursor.execute(sql)
        resultset = cursor.fetchall()
        cursor.close()
        conn.close()
        #print(resultset)
        if resultset:
            return resultset
        else:
            #print('未查询到数据，请更新数据！')
            return None


    def get_stockname(self,stockcode):
        if stockcode.isdigit():  # 如果输入的是代码
            stockdata = pd.DataFrame(
                self.pro.stock_basic(exchange='', list_status='L', fields='ts_code,symbol,name,area,industry,list_date'))
            # print(stockdata)
            for stock in stockdata.iterrows():
                # print(stock)
                if stockcode in stock[1]['ts_code']:
                    print(stock[1]['name'])
                    # print(str(stock[1]['ts_code'])[0:6])
                    return str(stock[1]['name'])
                else:
                    continue
        else:
            return stockcode

    # 获取日线数据
    def get_stock_dateData(self, stockcode, start_date, end_date):
        if stockcode[0:3] == '600' or stockcode[0:2] == '68':
            stockcode = stockcode + '.SH'
        else:
            stockcode = stockcode + '.SZ'
        # 从tushare 获取日线数据
        df = self.pro.daily(ts_code=stockcode, start_date=start_date, end_date=end_date)
        df = df.sort_values(by=['trade_date'], ascending=True)  # 按日期升序
        return df


    # 将查询到的数据分析后输出到html
    def rendertohtml(self, resultset):
        if resultset is None:
            print('无数据')
            return None

        header = ['日期', '股票代码 ', '股票名称 ', '持股数亿', '占比', '收盘价  ', '当日涨跌幅  ', '持股市值亿  ', '一日市值变化亿', '五日市值变化亿', '十日市值变化亿']
        tb = pt.PrettyTable()
        tb.field_names = header  # 设置表头
        tb.align = 'c'  # 对齐方式（c:居中，l居左，r:居右）
        page=Page()
        c = Line()
        x = ['持股占比']
        name = ''
        HDDATELIST = []
        SHAREHOLDSUMlist = []  # 持股数
        SHARESRATElist = []  # 持股占比
        CLOSEPRICElist=[]
        zdflist = []
        SHAREHOLDPRICEONElist = []
        SHAREHOLDPRICEFIVElist = []
        SHAREHOLDPRICETENlsit = []
        # 取出占比数据
        #print(resultset)
        for tempdata in resultset:
            for data in tempdata:
                #print(data+'\n----------------------------------------')
                jsdata = json.loads(data)
                # print(type(jsdata), jsdata)
                HDDATE = str(jsdata['HDDATE'])[0:10]
                HDDATE = datetime.datetime.strptime(HDDATE, '%Y-%m-%d').strftime('%Y%m%d')
                HDDATELIST.append(HDDATE)
                SCODE = jsdata['SCODE']
                SNAME = jsdata['SNAME']
                SHAREHOLDSUM = format(jsdata['SHAREHOLDSUM'] / 100000000, '.3f')
                SHAREHOLDSUMlist.append(SHAREHOLDSUM)
                SHARESRATE = jsdata['SHARESRATE']
                SHARESRATElist.append(SHARESRATE)
                CLOSEPRICE = jsdata['CLOSEPRICE']
                CLOSEPRICElist.append(CLOSEPRICE)
                ZDF = jsdata['ZDF']
                zdflist.append(ZDF)
                SHAREHOLDPRICE = format(jsdata['SHAREHOLDPRICE'] / 100000000, '.3f')
                SHAREHOLDPRICEONE = format(jsdata['SHAREHOLDPRICEONE'] / 100000000, '.3f')
                SHAREHOLDPRICEONElist.append(SHAREHOLDPRICEONE)
                SHAREHOLDPRICEFIVE = format(jsdata['SHAREHOLDPRICEFIVE'] / 100000000, '.3f')
                SHAREHOLDPRICEFIVElist.append(SHAREHOLDPRICEFIVE)
                SHAREHOLDPRICETEN = format(jsdata['SHAREHOLDPRICETEN'] / 100000000, '.3f')
                SHAREHOLDPRICETENlsit.append(SHAREHOLDPRICETEN)

                tb.add_row(
                    [HDDATE, SCODE, SNAME, SHAREHOLDSUM, SHARESRATE, CLOSEPRICE, ZDF, SHAREHOLDPRICE, SHAREHOLDPRICEONE,
                     SHAREHOLDPRICEFIVE, SHAREHOLDPRICETEN])

        OUTFILE = '南向资金_' + SNAME + '.html'
        # print(SHARESRATE)
        x1 = HDDATELIST[::-1]
        y1 = SHARESRATElist[::-1]  # 将占比数据设置为y轴
        y2 = SHAREHOLDSUMlist[::-1]
        y3 = zdflist[::-1]
        y4 = SHAREHOLDPRICEONElist[::-1]
        y5 = SHAREHOLDPRICEFIVElist[::-1]
        y6 = SHAREHOLDPRICETENlsit[::-1]
        # y2 = [1000, 300, 500]
        # bar = Bar()
        # 设置x轴
        c.add_xaxis(xaxis_data=x)
        c.add_xaxis(xaxis_data=x1)
        # 设置y轴
        c.add_yaxis(series_name='持股百分比', y_axis=y1)
        c.add_yaxis(series_name='持股数量亿', y_axis=y2)
        # c.add_yaxis(series_name='涨跌幅', y_axis=y3)
        c.add_yaxis(series_name='1日变动亿', y_axis=y4)
        c.add_yaxis(series_name='5日变动亿', y_axis=y5)
        c.add_yaxis(series_name='10日变动亿', y_axis=y6)

        c.set_global_opts(title_opts=opts.TitleOpts(title='北向资金持股分析:  ' + SNAME))
        # 生成html文件
        outfile = '北向资金_' + SNAME + '.html'
        # c.render(path=outfile)
        # 输出K线图
        # 先获取日线历史数据
        date = datetime.date.today() - relativedelta(months=+4)  # 当前日期减2个月
        date = datetime.datetime.strptime(str(date), '%Y-%m-%d').strftime('%Y%m%d')
        # print(date)
        getstockdata = self.get_stock_dateData(SCODE, str(date), x1[-1])
        # getstockdata = pd.DataFrame(getstockdata)
        # print(getstockdata)
        getstockdata['trade_date'] = pd.to_datetime(getstockdata['trade_date'])  # 设置字段trade_date 为datetime
        getstockdata = getstockdata.set_index('trade_date')  # 设置trade_date为索引
        # getstockdata.sort_values(by=['trade_date','close'],ascending=False)
        # 设置四个绘图区域    包括    K线（均线），成交量，MACD
        np.seterr(divide='ignore', invalid='ignore')  # 忽略warning
        plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
        plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
        fig, ax = plt.subplots(figsize=(9, 6))  # 创建fig对象
        # 画绘图区域
        gs = gridspec.GridSpec(2, 1, left=0.08, bottom=0.15, right=0.99, top=0.96, wspace=None, hspace=0,
                               height_ratios=[3.5, 1])
        # 添加指标
        graph_KAV = fig.add_subplot(gs[0, :])  # K线图
        graph_VOL = fig.add_subplot(gs[1, :])
        # graph_MACD = fig.add_subplot(gs[2, :])
        # graph_KDJ = fig.add_subplot(gs[3, :])
        mpf.candlestick2_ochl(graph_KAV, getstockdata.open, getstockdata.close, getstockdata.high, getstockdata.low,
                              width=0.5, colorup='r', colordown='g')  # 绘制K线走势
        # mpf.plot(getstockdata.iloc[:100],type='candle')  # 绘制K线走势
        # 绘制移动平均线图
        getstockdata['Ma5'] = getstockdata.close.rolling(
            window=5).mean()  # pd.rolling_mean(df_stockload.close,window=20)
        getstockdata['Ma10'] = getstockdata.close.rolling(
            window=10).mean()  # pd.rolling_mean(df_stockload.close,window=30)
        getstockdata['Ma20'] = getstockdata.close.rolling(
            window=20).mean()  # pd.rolling_mean(df_stockload.close,window=60)
        # getstockdata['Ma30'] = getstockdata.close.rolling(window=30).mean()  # pd.rolling_mean(df_stockload.close,window=60)
        # getstockdata['Ma60'] = getstockdata.close.rolling(window=60).mean()  # pd.rolling_mean(df_stockload.close,window=60)

        graph_KAV.plot(np.arange(0, len(getstockdata.index)), getstockdata['Ma5'], 'black', label='M5', lw=1.0)
        graph_KAV.plot(np.arange(0, len(getstockdata.index)), getstockdata['Ma10'], 'green', label='M10', lw=1.0)
        graph_KAV.plot(np.arange(0, len(getstockdata.index)), getstockdata['Ma20'], 'blue', label='M20', lw=1.0)
        # graph_KAV.plot(np.arange(0, len(getstockdata.index)), getstockdata['Ma30'], 'pink', label='M30', lw=1.0)
        # graph_KAV.plot(np.arange(0, len(getstockdata.index)), getstockdata['Ma60'], 'yellow', label='M60', lw=1.0)

        # 添加网格
        graph_KAV.grid()
        graph_KAV.legend(loc='best')
        graph_KAV.set_title(SCODE + ' ' + SNAME + '(日线)')
        graph_KAV.set_ylabel(u"价格")
        graph_KAV.set_xlim(0, len(getstockdata.index))  # 设置一下x轴的范围
        # 绘制成交量图
        graph_VOL.bar(np.arange(0, len(getstockdata.index)), getstockdata.vol,
                      color=['g' if getstockdata.open[x] > getstockdata.close[x] else 'r' for x in
                             range(0, len(getstockdata.index))])
        graph_VOL.set_ylabel(u"成交量")
        graph_VOL.set_xlim(0, len(getstockdata.index))  # 设置一下x轴的范围
        graph_VOL.set_xticks(range(0, len(getstockdata.index), 1))  # X轴刻度设定 每1天标一个日期

        # X-轴每个ticker标签都向右倾斜45度
        for label in graph_KAV.xaxis.get_ticklabels():
            label.set_visible(False)

        for label in graph_VOL.xaxis.get_ticklabels():
            label.set_visible(True)
            label.set_fontsize(10)
        plt.savefig('./Kline.jpg')
        page.add(c)
        page.render(path=outfile)
        # 如果要输出柱图
        '''
        bar = Bar()
        然后将c 换成bar
        '''
        # s = tb.sort_key('日期','desc')
        s = tb.get_html_string()  # 格式化成html文件
        print(tb.get_string())
        # 将画的图片输出
        kline = '''<img src=./Kline.jpg />'''
        fw = open(outfile, 'a+', encoding='utf-8')
        fw.write(kline)
        fw.write(s)  # 输出到文件
        fw.close()
        webbrowser.open(outfile)  # 调用浏览器打开文件

    # 获取表中最新的日期
    def getdb_maxdate(self):
        sql = 'select max(HDDATE) as "HDDATE" from northdataAnaly '
        conn = db.dbconnect()
        cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
        cursor.execute(sql)
        result = cursor.fetchall()
        # print(result)
        for data in result:
            data1 = data['HDDATE']
            print(data1)
        cursor.close()
        conn.close()
        if data1 is None:
            print('表中无数据，请更新数据')
            return None
        return str(data1)

    # 获取表中指定的日期
    def getdbdate(self,hddate):
        sql = 'select  HDDATE from northdataAnaly where HDDATE=\''+hddate+'\' limit 1;'
        # print(sql)
        conn = db.dbconnect()
        cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
        cursor.execute(sql)
        result = cursor.fetchall()
        # print(result)
        if result is None:
            print('无数据')
        for data in result:
            data1 = data['HDDATE']
            # print(data1)
            if data1 is None:
                return None
            else:
                return str(data1)
        cursor.close()
        conn.close()



    # 比较数据是否为最新的
    def compare_Date(self):
        isnewdate = True
        pagedate = self.get_page_newdate()
        dbdate = self.getdb_maxdate()
        if dbdate is None:
            return False
        if pagedate > dbdate:
            isnewdate = False
            return isnewdate
        else:
            isnewdate = True
            return isnewdate

    # 格式化成table
    def northdataAnalyFormat(self, resultset):
        # print(resultset)
        if resultset is None:
            print('无数据')
            return None
        header = ['日期', '股票代码 ', '股票名称 ', '持股数亿', '占比', '收盘价  ', '当日涨跌幅  ', '持股市值亿  ', '一日市值变化亿', '五日市值变化亿', '十日市值变化亿']
        tb = pt.PrettyTable()
        tb.field_names = header  # 设置表头
        tb.align = 'c'  # 对齐方式（c:居中，l居左，r:居右）
        for data in resultset:
            HDDATE = data['HDDATE']
            SCODE = data['SCODE']
            SHAREHOLDSUM = data['SHAREHOLDSUM']
            SNAME = data['SNAME']
            SHARESRATE = data['SHARESRATE']
            CLOSEPRICE = data['CLOSEPRICE']
            ZDF = data['ZDF']
            SHAREHOLDPRICE = format(data['SHAREHOLDPRICE'], '.3f')
            SHAREHOLDPRICEONE = format(data['SHAREHOLDPRICEONE'], '.3f')
            SHAREHOLDPRICEFIVE = format(data['SHAREHOLDPRICEFIVE'], '.3f')
            SHAREHOLDPRICETEN = format(data['SHAREHOLDPRICETEN'], '.3f')
            tb.add_row(
                [HDDATE, SCODE, SNAME, SHAREHOLDSUM, SHARESRATE, CLOSEPRICE, ZDF, SHAREHOLDPRICE, SHAREHOLDPRICEONE,
                 SHAREHOLDPRICEFIVE, SHAREHOLDPRICETEN])
        print(tb.get_string())

    ###获取股票代码
    def get_stockcode(self, stockname):
        if stockname.isdigit():  # 如果输入的是代码
            return stockname
        else:
            stockdata = pd.DataFrame(self.pro.stock_basic(exchange='', list_status='L',
                                                          fields='ts_code,symbol,name,area,industry,list_date'))
            # print(stockdata)
            for stock in stockdata.iterrows():
                # print(stock)
                if stockname == stock[1]['name']:
                    # print(stock[1]['name'])
                    # print(str(stock[1]['ts_code'])[0:6])
                    return str(stock[1]['ts_code'])[0:6]
                else:
                    continue

    # 获个股日线数据
    def get_stock_dateData(self,stockcode, start_date, end_date):
        if stockcode[0:2] == '60' or stockcode[0:2] == '68':
            stockcode = stockcode + '.SH'
        else:
            stockcode = stockcode + '.SZ'
        # 从tushare 获取日线数据

        df = self.pro.daily(ts_code=stockcode, start_date=start_date, end_date=end_date)
        df = df.sort_values(by=['trade_date'], ascending=True)  # 按日期升序
        return df



    #获取当日更新的北向数据
    def getNownorth(self):
        header = ['日期', '股票代码 ', '股票名称 ', '板块', '占流通股%', '最新价  ', '涨跌幅  ', '今日持股股数亿  ', '今日持股市值亿', '占流通股本%', '今日持股占总股本',
                  '市值增幅', '市值增幅%']
        # url='http://data.eastmoney.com/hsgtcg/list.html'
        url = 'http://dcfm.eastmoney.com//em_mutisvcexpandinterface/api/js/get'
        northdataAnalyinfos=[]
        headers = {
            'Accept': '*/*',
            'Accept-Encoding': 'gzip, deflate',
            'Accept-Language': 'zh - CN, zh;    q = 0.9, en;    q = 0.8    ',
            'Connection': 'keep-alive',
            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.111 Safari/537.36',
            'Cookie': 'Cookie: pgv_pvi=3794568192; _qddaz=QD.6ofmf2.j6jr4m.kat8wucp; ct=u_GCXp_V0BUfw6EE3hFHtqMglz3afgkppJcv5vbFImFCEcWBrdbJ1czxMgSRvdgdMHMxnKracqlOZgxC4VNfwrkiwCCnYCNVFUzHMie-NyeUGcc8-NdJwvaXLimNiEt9gsOQO3q161JU2fTSAHZYRo5byr67JKvMwuA_2qSbhls; ut=FobyicMgeV5ghfUPKWOH5wak5fe7PCdYa2maZFrymrOdfN-wAEFtpNp1MzH070EBSmKRLG6vmIcYwEk2SvuUDiGwHB7BHzpaN3m4xMthhPoNqi89FTByaNH4MkRCfEYW4JX960vY0ITlmRY-cPk1PQzTvxCYnVj0Ey0NtYOnUdj24K9O1_tKWeyEDf1k_bIV6hcX360Qn8yYsWTrETZTzGYR7tn62AgnDFAq58DbSa3StLkggc5c7wB94try8c_WEpaHHyl5rA7BBAJZkje3dZ7Q7pZSUWri; pi=3323115305075326%3bc3323115305075326%3b%e8%82%a1%e5%8f%8bjHWZa22110%3bAc4gMB%2bahzpZU8kVvDCm4%2f9QLFcpRepVrDlj4DSAFvQS9L41u5PjbhW1g0ATNFBs2U6jdaiAi0v97coryIUwYaBWyHAUTbi1GDBZdDmkrBugnCGTBDTgPjXURUbrtmze597viYIL2RjHQTBKDzTIQqxuco%2b4pIMvD3B%2f2gF3Z2HSKCRGXGX%2bMcFxewJmIXD8wOJYtqii%3bM4Rnsdjx0lNLDrlCNBv6VhW13wgvkjpsoKd52WM1JsrPCSqUd%2fySTvks6nwUjCNsGby4fYU2Y%2bbjGtRBVly22B%2bqdAhoqGh6XrZIWQGX4LDnpd4CKtckek2Rlq7r9qjcQSdzcprF%2bmmkr9EqKBQVnmt9ppYRhg%3d%3d; uidal=3323115305075326%e8%82%a1%e5%8f%8bjHWZa22110; sid=126018279; _ga=GA1.2.1363410539.1596117007; em_hq_fls=js; AUTH_FUND.EASTMONEY.COM_GSJZ=AUTH*TTJJ*TOKEN; emshistory=%5B%22%E4%BA%BA%E6%B0%94%E6%8E%92%E8%A1%8C%E6%A6%9C%22%2C%22%E6%AF%94%E4%BA%9A%E8%BF%AA%E4%BA%BA%E6%B0%94%E6%8E%92%E5%90%8D%22%2C%22%E5%9F%BA%E9%87%91%E6%8E%92%E8%A1%8C%22%2C%22%E8%BF%913%E4%B8%AA%E6%9C%88%E8%B7%8C%E5%B9%85%E6%9C%80%E5%A4%A7%E7%9A%84%E5%9F%BA%E9%87%91%22%2C%22%E5%85%BB%E8%80%81%E9%87%91%E6%8C%81%E8%82%A1%E5%8A%A8%E5%90%91%E6%9B%9D%E5%85%89%22%2C%22%E5%A4%96%E7%9B%98%E6%9C%9F%E8%B4%A7%22%2C%22A50%22%2C%22%E6%81%92%E7%94%9F%E6%B2%AA%E6%B7%B1%E6%B8%AF%E9%80%9A%E7%BB%86%E5%88%86%E8%A1%8C%E4%B8%9A%E9%BE%99%E5%A4%B4A%22%2C%22%E7%BB%86%E5%88%86%E8%A1%8C%E4%B8%9A%E9%BE%99%E5%A4%B4%22%5D; vtpst=%7c; HAList=d-hk-00288%2Cd-hk-00772%2Cf-0-399006-%u521B%u4E1A%u677F%u6307%2Ca-sz-002008-%u5927%u65CF%u6FC0%u5149%2Ca-sz-002739-%u4E07%u8FBE%u7535%u5F71%2Cf-0-000001-%u4E0A%u8BC1%u6307%u6570%2Cd-hk-00981%2Ca-sz-002082-%u4E07%u90A6%u5FB7%2Ca-sz-300511-%u96EA%u6995%u751F%u7269; cowCookie=true; st_si=40836386960323; waptgshowtime=2021126; qgqp_b_id=3a2c1ce1f45a81a3fa7cc2fbad8e2a24; intellpositionL=345px; st_asi=delete; st_pvi=03400063938128; st_sp=2020-05-23%2013%3A48%3A35; st_inirUrl=https%3A%2F%2Fwww.baidu.com%2Flink; st_sn=48; st_psi=20210126213702703-113300303605-1327257583; intellpositionT=1940.09px'
        }
        # date1 =time.strftime("%Y-%m-%d", time.localtime())
        # 从东方财富网获取要取数据的日期
        date1 =self.get_page_newdate()
        params = {'type': 'HSGTHDSTA',
                  'token': '70f12f2f4f091e459a279469fe49eca5',
                  'st': 'HDDATE,SHAREHOLDPRICE',
                  'sr': 3,
                  'p': 1,
                  'ps': 50,
                  'js': 'var vaNPyqhg={pages:(tp),data:(x)}',
                  'filter': '(MARKET in (\'001\',\'003\'))(HDDATE=^' + date1 + '^)',
                  'rt': '53759764'}
        #print(params)
        content=req.get(url=url, headers=headers, params=params).text
        #print(content)
        regex1 = 'pages:(\d{0,2})'
        maxpage=int(re.findall(regex1, content, re.M)[0])
        print('共有  %d  页数据需要更新，请稍等......'%maxpage)

        for i in range(1, maxpage+1, 1):  # 北向资金数据每天有30页

            params = {'type': 'HSGTHDSTA',
                      'token': '70f12f2f4f091e459a279469fe49eca5',
                      'st': 'SHAREHOLDPRICEONE',
                      'sr': -1,
                      'p': i,
                      'ps': 50,
                      'js': 'var TpSlNIMe={pages:(tp),data:(x)}',
                      'filter': '(MARKET in (\'001\',\'003\'))(HDDATE=^' + date1 + '^)',
                      'rt': '53722283'}
                # print(params)
            try:
                response = req.get(url=url, headers=headers, params=params)
            except BaseException as BE:
                time.sleep(2)
                count=0
                while count<3:
                    response = req.get(url=url, headers=headers, params=params,proxies=self.get_proxy())
                    if response.status_code!=200:

                        count+=1
                        print('第%s 次 第%s 页数据获取异常,重试中！！！' %(count,i))
                        time.sleep(2)
                    else:
                        break

            bstext = bs4.BeautifulSoup(response.content, 'lxml')
            tempdata = bstext.find_all('p')
            temp = str(tempdata)
            regex = 'data:(.*?)}</p>'
            jsondata = str(re.findall(regex, temp, re.M))
            data = jsondata.replace('\\r\\n', '', -1).replace('},', '}},', -1).replace('[\'[', '', -1).replace(
                ']\']', '', -1)
            listdata = data.split('},', -1)[::]
            #print(listdata)
            northdataAnalyinfos.append(listdata)
            time.sleep(1)
        return northdataAnalyinfos

    # 获取指定日期的北向数据
    def getDesignatedDateData(self,date1):

        url = 'http://dcfm.eastmoney.com//em_mutisvcexpandinterface/api/js/get'
        northdataAnalyinfos = []
        headers = {
            'Accept': '*/*',
            'Accept-Encoding': 'gzip, deflate',
            'Accept-Language': 'zh - CN, zh;    q = 0.9, en;    q = 0.8    ',
            'Connection': 'keep-alive',
            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.111 Safari/537.36',
            'Cookie': 'Cookie: pgv_pvi=3794568192; _qddaz=QD.6ofmf2.j6jr4m.kat8wucp; ct=u_GCXp_V0BUfw6EE3hFHtqMglz3afgkppJcv5vbFImFCEcWBrdbJ1czxMgSRvdgdMHMxnKracqlOZgxC4VNfwrkiwCCnYCNVFUzHMie-NyeUGcc8-NdJwvaXLimNiEt9gsOQO3q161JU2fTSAHZYRo5byr67JKvMwuA_2qSbhls; ut=FobyicMgeV5ghfUPKWOH5wak5fe7PCdYa2maZFrymrOdfN-wAEFtpNp1MzH070EBSmKRLG6vmIcYwEk2SvuUDiGwHB7BHzpaN3m4xMthhPoNqi89FTByaNH4MkRCfEYW4JX960vY0ITlmRY-cPk1PQzTvxCYnVj0Ey0NtYOnUdj24K9O1_tKWeyEDf1k_bIV6hcX360Qn8yYsWTrETZTzGYR7tn62AgnDFAq58DbSa3StLkggc5c7wB94try8c_WEpaHHyl5rA7BBAJZkje3dZ7Q7pZSUWri; pi=3323115305075326%3bc3323115305075326%3b%e8%82%a1%e5%8f%8bjHWZa22110%3bAc4gMB%2bahzpZU8kVvDCm4%2f9QLFcpRepVrDlj4DSAFvQS9L41u5PjbhW1g0ATNFBs2U6jdaiAi0v97coryIUwYaBWyHAUTbi1GDBZdDmkrBugnCGTBDTgPjXURUbrtmze597viYIL2RjHQTBKDzTIQqxuco%2b4pIMvD3B%2f2gF3Z2HSKCRGXGX%2bMcFxewJmIXD8wOJYtqii%3bM4Rnsdjx0lNLDrlCNBv6VhW13wgvkjpsoKd52WM1JsrPCSqUd%2fySTvks6nwUjCNsGby4fYU2Y%2bbjGtRBVly22B%2bqdAhoqGh6XrZIWQGX4LDnpd4CKtckek2Rlq7r9qjcQSdzcprF%2bmmkr9EqKBQVnmt9ppYRhg%3d%3d; uidal=3323115305075326%e8%82%a1%e5%8f%8bjHWZa22110; sid=126018279; _ga=GA1.2.1363410539.1596117007; em_hq_fls=js; AUTH_FUND.EASTMONEY.COM_GSJZ=AUTH*TTJJ*TOKEN; emshistory=%5B%22%E4%BA%BA%E6%B0%94%E6%8E%92%E8%A1%8C%E6%A6%9C%22%2C%22%E6%AF%94%E4%BA%9A%E8%BF%AA%E4%BA%BA%E6%B0%94%E6%8E%92%E5%90%8D%22%2C%22%E5%9F%BA%E9%87%91%E6%8E%92%E8%A1%8C%22%2C%22%E8%BF%913%E4%B8%AA%E6%9C%88%E8%B7%8C%E5%B9%85%E6%9C%80%E5%A4%A7%E7%9A%84%E5%9F%BA%E9%87%91%22%2C%22%E5%85%BB%E8%80%81%E9%87%91%E6%8C%81%E8%82%A1%E5%8A%A8%E5%90%91%E6%9B%9D%E5%85%89%22%2C%22%E5%A4%96%E7%9B%98%E6%9C%9F%E8%B4%A7%22%2C%22A50%22%2C%22%E6%81%92%E7%94%9F%E6%B2%AA%E6%B7%B1%E6%B8%AF%E9%80%9A%E7%BB%86%E5%88%86%E8%A1%8C%E4%B8%9A%E9%BE%99%E5%A4%B4A%22%2C%22%E7%BB%86%E5%88%86%E8%A1%8C%E4%B8%9A%E9%BE%99%E5%A4%B4%22%5D; vtpst=%7c; HAList=d-hk-00288%2Cd-hk-00772%2Cf-0-399006-%u521B%u4E1A%u677F%u6307%2Ca-sz-002008-%u5927%u65CF%u6FC0%u5149%2Ca-sz-002739-%u4E07%u8FBE%u7535%u5F71%2Cf-0-000001-%u4E0A%u8BC1%u6307%u6570%2Cd-hk-00981%2Ca-sz-002082-%u4E07%u90A6%u5FB7%2Ca-sz-300511-%u96EA%u6995%u751F%u7269; cowCookie=true; st_si=40836386960323; waptgshowtime=2021126; qgqp_b_id=3a2c1ce1f45a81a3fa7cc2fbad8e2a24; intellpositionL=345px; st_asi=delete; st_pvi=03400063938128; st_sp=2020-05-23%2013%3A48%3A35; st_inirUrl=https%3A%2F%2Fwww.baidu.com%2Flink; st_sn=48; st_psi=20210126213702703-113300303605-1327257583; intellpositionT=1940.09px'
        }
        # date1 =time.strftime("%Y-%m-%d", time.localtime())

        params = {'type': 'HSGTHDSTA',
                  'token': '70f12f2f4f091e459a279469fe49eca5',
                  'st': 'HDDATE,SHAREHOLDPRICE',
                  'sr': 3,
                  'p': 1,
                  'ps': 50,
                  'js': 'var vaNPyqhg={pages:(tp),data:(x)}',
                  'filter': '(MARKET in (\'001\',\'003\'))(HDDATE=^' + date1 + '^)',
                  'rt': '53759764'}
        # print(params)
        content = req.get(url=url, headers=headers, params=params).text  #获取数据总页数
        # print(content)
        regex1 = 'pages:(\d{0,2})'
        maxpage = int(re.findall(regex1, content, re.M)[0])
        print('共有  %d  页数据需要更新，请稍等......' % maxpage)

        for i in range(1, maxpage + 1, 1):  # 北向资金数据每天有30页
            try:
                params = {'type': 'HSGTHDSTA',
                          'token': '70f12f2f4f091e459a279469fe49eca5',
                          'st': 'SHAREHOLDPRICEONE',
                          'sr': -1,
                          'p': i,
                          'ps': 50,
                          'js': 'var TpSlNIMe={pages:(tp),data:(x)}',
                          'filter': '(MARKET in (\'001\',\'003\'))(HDDATE=^' + date1 + '^)',
                          'rt': '53722283'}
                # print(params)
                response = req.get(url=url, headers=headers, params=params)
                bstext = bs4.BeautifulSoup(response.content, 'lxml')
                tempdata = bstext.find_all('p')
                temp = str(tempdata)
                regex = 'data:(.*?)}</p>'
                jsondata = str(re.findall(regex, temp, re.M))
                data = jsondata.replace('\\r\\n', '', -1).replace('},', '}},', -1).replace('[\'[', '', -1).replace(
                    ']\']', '', -1)
                listdata = data.split('},', -1)[::]
                # print(listdata)
                northdataAnalyinfos.append(listdata)
                time.sleep(1)
            except BaseException as be:
                # print(be)
                time.sleep(5)
                continue
        return northdataAnalyinfos
    # 将当日获取的数据插入表
    def insertNowdata(self, northdataAnalyinfos):
        if len(northdataAnalyinfos) == 0:
            return
        #print(northdataAnalyinfos)
        conn = db.dbconnect()
        cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
        # 执行的sql语句
        sql = '''insert into northdataanaly (HDDATE,SCODE,SNAME,SHAREHOLDSUM,SHARESRATE,CLOSEPRICE,ZDF,SHAREHOLDPRICE,SHAREHOLDPRICEONE,SHAREHOLDPRICEFIVE,SHAREHOLDPRICETEN) values (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)'''
        for datalist in northdataAnalyinfos:
            for row in datalist:  # 依次获取每一行数据
                try:
                    jsdata = json.loads(row)
                    HDDATE = str(jsdata['HDDATE'])[0:10]
                    SCODE = jsdata['SCODE']
                    SNAME = jsdata['SNAME']
                    SHAREHOLDSUM = format(jsdata['SHAREHOLDSUM'] / 100000000, '.3f')
                    SHARESRATE = jsdata['SHARESRATE']
                    CLOSEPRICE = jsdata['CLOSEPRICE']
                    ZDF = jsdata['ZDF']
                    SHAREHOLDPRICE = format(jsdata['SHAREHOLDPRICE'] / 100000000, '.3f')
                    SHAREHOLDPRICEONE = format(jsdata['SHAREHOLDPRICEONE'] / 100000000, '.3f')
                    SHAREHOLDPRICEFIVE = format(jsdata['SHAREHOLDPRICEFIVE'] / 100000000, '.3f')
                    SHAREHOLDPRICETEN = format(jsdata['SHAREHOLDPRICETEN'] / 100000000, '.3f')
                    values = (
                        HDDATE, SCODE, SNAME, SHAREHOLDSUM, SHARESRATE, CLOSEPRICE, ZDF, SHAREHOLDPRICE,
                        SHAREHOLDPRICEONE,
                        SHAREHOLDPRICEFIVE, SHAREHOLDPRICETEN)
                    cursor.execute(sql, values)
                    # print(values,sql)
                except BaseException as be:
                    print(be)
                    continue
            conn.commit()
        conn.commit()
        conn.close()

    def openF10(self,SNAME):
        url='http://basic.10jqka.com.cn/%s/finance.html'
        url=url %SNAME
        webbrowser.open(url)

    def mainMemu(self):
        print(
            '*****************************************************************************************************\r\n')
        print('\t 1。数据入库')
        print('\t 2。当日持股变动最大前10股票查询')
        print('\t 3。北资开始净买股票查询 ')
        print('\t 4。个股数据展示（输入名称或代码）')
        print('\t 5。打开个股F0（输入名称代码）')
        print('\t 6。手动补齐数据')
        print('\t 7。北资一键写通达信')
        print('\t 8。检查个股是否暴雷')
        print('\t 0。退出\n')
        print(
            '*****************************************************************************************************\r\n')
    #流程控制
    def main(self):
        SNAME = '建设银行'
        SNAME = '小米集团 - W'
        options, args=self.get_optparse()
        var = sys.argv  # 可以接收从外部传入参数
        while True:
            if len(var) > 1:
                var1 = str(var[1]).strip(' ')
                if var1=='1':
                    isnew = self.compare_Date()  # 判断是否要更新数据
                    if isnew:
                        print('数据已是最新')
                        break
                    else:
                        print('数据更新中！')
                        northdataAnalyinfos = self.getNownorth()
                        self.insertNowdata(northdataAnalyinfos)
                        print('数据更新成功！！！')
                        break
                code = self.get_stockcode(var1)
                listdata = self.getnorth(code)  # 实时查询北向资金
                self.rendertohtml(listdata)
            else:
                self.mainMemu() #显示主菜单
                try:
                    choise = int(input('请输入：'))
                except BaseException as BE:
                    choise = int(input('输入错误，请重新输入 ：'))
                if choise in range(9):
                    try:
                        if choise == 1:
                            isnew = self.compare_Date()  # 判断是否要更新数据
                            if isnew:
                                print('数据已是最新')
                            else:
                                print('数据更新中！')
                                northdataAnalyinfos = self.getNownorth()
                                self.insertNowdata(northdataAnalyinfos)
                                print('数据更新成功！！！')
                        elif choise == 2:
                            resultset = self.Select_top10()
                            self.northdataAnalyFormat(resultset)
                        elif choise == 3:
                            resultset = self.Select_Netpurchases()  # 查询南资开始净买的股票
                            if resultset is None:
                                print('无满足条件的数据！')
                            else:
                                self.northdataAnalyFormat(resultset)

                        elif choise == 4:
                            SNAME = str(input('请输入股票名称或代码:\t')).strip()
                            if SNAME =='' :
                                SNAME = str(input('请输入股票名称或代码:\t')).strip()
                                if SNAME.isdigit():
                                    if len(SNAME)<6:
                                        print('代码输入错误')
                                        SNAME = str(input('请输入股票名称或代码:\t')).strip()
                                else:
                                    if SNAME =='':
                                        continue
                                    SNAME = self.get_stockcode(SNAME)

                            resultset = self.getnorth(SNAME)   # 按名称查询北向资金占比
                            if resultset is None:
                                print('无北向数据......')
                            else:
                                # print(resultset)
                                self.rendertohtml(resultset)
                        elif choise==5:
                            SNAME = str(input('请输入股票名称或代码:\t'))
                            if SNAME.isdigit():
                                # code = self.get_stockname(SNAME)
                                pass
                            else:
                                SNAME = self.get_stockcode(SNAME)
                                if SNAME is None:
                                    print('没有该股！！')

                            self.openF10(SNAME)  # 打开F10
                        elif choise == 6:
                            Hddate=str(input('请输入要补齐的数据日期，Ex: 2021-02-10\t')).strip()
                            try:
                                if ":" in Hddate:
                                    time.strptime(Hddate, "%Y-%m-%d")
                                else:
                                    time.strptime(Hddate, "%Y-%m-%d")
                            except:
                                print('日期输入错误！')
                                continue
                            dbdate = self.getdbdate(Hddate)
                            # print('db—date:'+str(dbdate))
                            if dbdate ==Hddate:
                                print('表中已有数据！！！')
                            else:
                                northdataAnalyinfos = self.getDesignatedDateData(Hddate)
                                self.insertNowdata(northdataAnalyinfos)
                                print('入库成功！！！')
                                select = str(input('是否要保存到本地文件（Y/）N： '))
                                if select =='Y' or select=='y':
                                    self.WriteFile(northdataAnalyinfos, Hddate)
                                else:
                                    pass
                        elif choise == 7:
                            writefile = writeToTdx()
                            writefile.FullDataWritetoFile()
                        elif choise == 8:
                            stockcode = str(input('请输入股票名称或代码:\t'))
                            if stockcode.isdigit():
                                # code = self.get_stockname(SNAME)
                                pass
                            else:
                                stockcode = self.get_stockcode(stockcode)
                            checkStock.baolei(stockcode)

                        elif choise == 0 or choise=='quit' or choise=='exit' or choise=='q':
                            exit(0)
                    except BaseException as e:
                        if choise == 0 or choise=='quit' or choise=='exit' or choise=='q':
                            exit(0)
                        continue
                else:
                    print('输入错误\n')
                    choise = int(input('请输入：'))


if __name__ == '__main__':
    Analys = NorthwardAnalysis()
    Analys.main()

#表结构信息
'''
CREATE TABLE IF NOT EXISTS `northdataAnaly`( 
HDDATE date,
SCODE varchar(8),
SNAME varchar(20),
SHAREHOLDSUM float,  持股数量
SHARESRATE float,  持股占比
CLOSEPRICE float,  收盘价
ZDF float,
SHAREHOLDPRICE float, 持股市值亿
SHAREHOLDPRICEONE float,  一日持股变动亿
SHAREHOLDPRICEFIVE float, 五日持股变动亿
SHAREHOLDPRICETEN float  十日持股变动亿
)ENGINE=InnoDB DEFAULT CHARSET=utf8;

create index northdataAnalycode on northdataAnaly(SCODE);
create index northdataAnalyHdDate on northdataAnaly(HDDATE);
create index nnorthdataAnalySName on northdataAnaly(SNAME);
'''
'''
              {
                  "DateType": "1",
                  "HdDate": "2021-01-20",
                  "Hkcode": "1000002452",
                  "SCode": "600036",
                  "SName": "招商银行",
                  "HYName": "银行",
                  "HYCode": "016029",
                  "ORIGINALCODE": "475",
                  "DQName": "广东板块",
                  "DQCode": "020005",
                  "ORIGINALCODE_DQ": "153",
                  "JG_SUM": 70.0,
                  "SharesRate": 5.67,
                  "NewPrice": 51.72,
                  "Zdf": -0.2507,
                  "Market": "001",
                  "ShareHold": 1171539916.0,
                  "ShareSZ": 60592044455.52,
                  "LTZB": 0.0567910743097964,
                  "ZZB": 0.0464530962851552,
                  "LTSZ": 1066929005867.88,
                  "ZSZ": 1304370414483.72,
                  "ShareHold_Before_One": 0.0,
                  "ShareSZ_Before_One": 0.0,
                  "ShareHold_Chg_One": 10862250.0,
                  "ShareSZ_Chg_One": 561795570.0,
                  "ShareSZ_Chg_Rate_One": 0.00933507737095592,
                  "LTZB_One": 0.000525233651781947,
                  "ZZB_One": 0.000429622606984593
                },'''