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# -*- coding: utf-8 -*-
import pandas as pd
import tushare as ts
import lxml
from redis import Redis
import hashlib
import pymysql
import time
import datetime
# =============================================================非一字涨停板家数、炸板家数每日涨跌停价格stk_limit、日线行情daily====================================
def zrztCount():
    ‘‘‘
    daily,提供未复权数据，每分钟内最多调取200次，每次4000条数据
    stk_limit单次最多提取4800条记录，可循环调取，总量不限制
    ‘‘‘
    
    # 定义计数器
    success, fail, count = 0, 0, 0
    
    # 定义计数器
    zrzt, zb, zrdt = 0, 0, 0

    # 创建MySQL操作游标
    cursor = conn_mysql.cursor()
    
    # 获取当日市场股票数据
    for offset in range(0, 12000, 3000):
        daily = pro.daily(trade_date=cur_date, fields=‘ts_code,trade_date,open,high,low,close‘, offset=offset,limit=3000)
        limit = pro.stk_limit(trade_date=cur_date,fields=‘trade_date,ts_code,up_limit,down_limit‘, offset=offset,limit=3000)
        df = pd.merge(daily,limit,on=[‘trade_date‘,‘ts_code‘])
        trade_date = df[‘trade_date‘]
        cp_num = df.groupby(‘trade_date‘).count()    # 当天股票总数
        if df[‘open‘]!=df[‘up_limit‘] and df[‘close‘]==df[‘up_limit‘]:
            zrzt +=1    # 自然涨停家数
        elif df[‘high‘]==df[‘up_limit‘] and df[‘close‘]!=df[‘up_limit‘]:
            zb +=1    # 炸板家数
        elif df[‘open‘]!=df[‘down_limit‘] and df[‘close‘]==df[‘down_limit‘]:
            zrdt +=1    # 自然跌停家数
        
        zrzt_bl = zrdt/cp_num
        zb_bl = zb/cp_num
        zrdt_bl = zrdt/cp_num
    
# =============================================================SHIBOR利率数据:shibor=============================================================
def shiborRate():
    ‘‘‘
    单次最大2000，总量不限制
    ‘‘‘
    # 定义计数器
    success, fail, count = 0, 0, 0

    # 创建MySQL操作游标
    cursor = conn_mysql.cursor()
    
    # 获取当天shibor数据
    # ---------------------------------------------------------------------------------------------------------------------------------------------
    shibor = pro.shibor(date=cur_date,fields=‘date,on,1w,3m‘)
    # ---------------------------------------------------------------------------------------------------------------------------------------------
    # 获取历史shibor数据
    # ---------------------------------------------------------------------------------------------------------------------------------------------
    shibor = pro.shibor(start_date=‘20190526‘,end_date=‘20191225‘,fields=‘date,on,1w,3m‘)
    # ---------------------------------------------------------------------------------------------------------------------------------------------
    for index, row in shibor.iterrows()
        trade_date = row[‘date‘]    # 日期
        gy_shibor = row[‘on‘]    # 隔夜hibor
        yz_shibor = row[‘1w‘]    # 1周shibor
        sy_shibor = row[‘3m‘]    # 3个月shibor
        
        try:
            sql = ‘‘‘insert into shibor__data(trade_date,gy_shibor,yz_shibor,sy_shibor) values(‘%s‘,‘%s‘,‘%s‘,‘%s‘)‘‘‘(trade_date,gy_shibor,yz_shibor,sy_shibor)
            cursor.execute(sql)
            conn_mysql.commit()
            # 统计入库成功数量
            success += 1
        except:
            print(trade_date,total_amount)
            conn_mysql.rollback()
            # 统计入库失败数量
            fail += 1

    # 统计请求数据量
    count += 1

    # 关闭MySQL操作游标
    cursor.close()
    print(‘Shibor数据获取完毕，新入库数据：%d条‘ % success)
    print(‘Shibor数据获取完毕，入库失败数据：%d条‘ % fail)
    print(‘Shibor数据获取完毕，本次共请求数据：%d条‘ % count)    

# =============================================================两市成交总额：调用daily=============================================================
def totalTrade(conn_mysql,conn_redis,cur_date):
    ‘‘‘
    交易日每天15点～16点之间更新，每分钟内最多调取200次，每次4000条数据
    ‘‘‘

    # 定义计数器
    success, fail, count = 0, 0, 0

    # 创建MySQL操作游标
    cursor = conn_mysql.cursor()
    
    # 创建空的dataframe
    df = pd.DataFrame(columns=(‘trade_date‘,‘amount‘))
    
    # 计算当天沪深两市成交额
    # ---------------------------------------------------------------------------------------------------------------------------------------------
    for offset in range(0, 12000, 3000):
        daily = pro.daily(trade_date=cur_date, fields=‘trade_date,amount‘, offset=offset,limit=3000)
        df = pd.DataFrame([df,daily],axis=0)
    # ---------------------------------------------------------------------------------------------------------------------------------------------
    # 计算历史沪深两市成交额
    for offset in range(0, 900000, 3000):
        daily = pro.daily(start_date=‘20190526‘,end_date=‘20191225‘, fields=‘trade_date,amount‘, offset=offset,limit=3000)
        df = pd.DataFrame([df,daily],axis=0)
    # ---------------------------------------------------------------------------------------------------------------------------------------------    
    
    trade_date = df[‘trade_date‘]    # 交易日期
    total_amount = (df.groupby(‘trade_date‘).sum())/10  # 成交额，原始单位为：千元

    try:
        sql = ‘‘‘insert into total_amount_data(trade_date,total_amount) values(‘%s‘,‘%s‘)‘‘‘ % (trade_date,total_amount)
        cursor.execute(sql)
        conn_mysql.commit()
        # 统计入库成功数量
        success += 1
    except:
        print(trade_date,total_amount)
        conn_mysql.rollback()
        # 统计入库失败数量
        fail += 1

    # 统计请求数据量
    count += 1

    # 关闭MySQL操作游标
    cursor.close()
    print(‘沪深总成交额数据计算完毕，新入库数据：%d条‘ % success)
    print(‘沪深总成交额数据计算完毕，入库失败数据：%d条‘ % fail)
    print(‘沪深总成交额数据计算完毕，本次共请求数据：%d条‘ % count)
    
# =============================================================龙虎榜成交总额:调用top_list龙虎榜每日明细===========================================================
def totalTopinst(conn_mysql,conn_redis,cur_date):
    ‘‘‘
    交易日每天15点～16点之间更新，每分钟内最多调取200次，每次4000条数据
    ‘‘‘

    # 定义计数器
    success, fail, count = 0, 0, 0

    # 创建MySQL操作游标
    cursor = conn_mysql.cursor()
    
    # 计算当天沪深两市龙虎榜成交额
    # ---------------------------------------------------------------------------------------------------------------------------------------------
    total_inst_amount = pro.top_list(trade_date=cur_date，fields=‘trade_date,l_sell,l_buy,net_amount‘)
    total = total_inst_amount.groupby(‘trade_date‘)
    
    trade_date = total_inst_amount[‘trade_date‘]    # 交易日期
    total_l_sell = total_inst_amount.groupby(‘l_sell‘).sum()    # 龙虎榜总卖出额
    total_l_buy = total_inst_amount.groupby(‘l_buy‘).sum()    # 龙虎榜总买入额
    total_net_amount = total_inst_amount.groupby(‘net_amount‘).sum()    # 龙虎榜总净买入额
    try:
        sql = ‘‘‘insert into total_inst_amount_data(trade_date,total_l_sell,total_l_buy,total_net_amount) values(‘%s‘,‘%s‘,‘%s‘,‘%s‘)‘‘‘ %(trade_date,total_l_sell,total_l_buy,total_net_amount)
        cursor.execute(sql)
        conn_mysql.commit()
        # 统计入库成功数量
        success += 1
    except:
        print(trade_date,total_amount)
        conn_mysql.rollback()
        # 统计入库失败数量
        fail += 1

    # 统计请求数据量
    count += 1    
    
    # ---------------------------------------------------------------------------------------------------------------------------------------------
    
    # 计算历史沪深两市龙虎榜成交额
    # ---------------------------------------------------------------------------------------------------------------------------------------------
    start_date = datetime.datetime.strptime(‘20190526‘,‘%Y%m%d‘)
    end_date = datetime.datetime.strptime(‘20191225,‘%Y%m%d‘)
    if start_date <= end_date:
        trade_date = (start_date + datetime.timedelta(days=1)).strftime(‘%Y%m%d‘)
        total_inst_amount = pro.top_list(trade_date=cur_date，fields=‘trade_date,l_sell,l_buy,net_amount‘)
        total = total_inst_amount.groupby(‘trade_date‘)
    
        trade_date = total_inst_amount[‘trade_date‘]    # 交易日期
        total_l_sell = total_inst_amount.groupby(‘l_sell‘).sum()    # 龙虎榜总卖出额
        total_l_buy = total_inst_amount.groupby(‘l_buy‘).sum()    # 龙虎榜总买入额
        total_net_amount = total_inst_amount.groupby(‘net_amount‘).sum()    # 龙虎榜总净买入额
    
        try:
            sql = ‘‘‘insert into total_inst_amount_data(trade_date,total_l_sell,total_l_buy,total_net_amount) values(‘%s‘,‘%s‘,‘%s‘,‘%s‘)‘‘‘ %(trade_date,total_l_sell,total_l_buy,total_net_amount)
            cursor.execute(sql)
            conn_mysql.commit()
            # 统计入库成功数量
            success += 1
        except:
            print(trade_date,total_amount)
            conn_mysql.rollback()
            # 统计入库失败数量
            fail += 1

        # 统计请求数据量
        count += 1
    # ---------------------------------------------------------------------------------------------------------------------------------------------

    # 关闭MySQL操作游标
    cursor.close()
    print(‘沪深龙虎榜总成交额数据计算完毕，新入库数据：%d条‘ % success)
    print(‘沪深龙虎榜总成交额数据计算完毕，入库失败数据：%d条‘ % fail)
    print(‘沪深龙虎榜总成交额数据计算完毕，本次共请求数据：%d条‘ % count)
    

# =============================================================沪深港通资金流向：moneyflow_hsgt=============================================================
def moneyflowHsgt(conn_mysql,conn_redis,cur_date):
    ‘‘‘
    每次最多返回300条记录，总量不限制
    ‘‘‘
    # 定义计数器
    success, fail, count = 0, 0, 0

    # 创建MySQL操作游标
    cursor = conn_mysql.cursor()
    
    # 获取当天数据
    # ---------------------------------------------------------------------------------------------------------------------------------------------
    for offset in range(0, 12000, 300):
        hsgt = pro.moneyflow_hsgt(trade_date=cur_date, fields=‘trade_date,hgt,sgt,north_money‘, offset=offset,limit=300)
        
    # ---------------------------------------------------------------------------------------------------------------------------------------------
    
    # 获取历史数据
    # ---------------------------------------------------------------------------------------------------------------------------------------------
    for offset in range(0, 12000, 300):
        hsgt = pro.moneyflow_hsgt(start_date=‘20190526‘,end_date=‘20191225‘,fields=‘trade_date,hgt,sgt,north_money‘, offset=offset,limit=300)
        
    # ---------------------------------------------------------------------------------------------------------------------------------------------
        for index, row in hsgt.iterrows():
            trade_date = row[‘trade_date‘]  # 交易日期
            hgt = row[‘hgt‘] * 100  # 沪股通（百万元）
            sgt = row[‘sgt‘] * 100  # 深股通（百万元）
            north_money = row[‘north_money‘] * 100  # 北向资金（百万元）

            try:
                sql = ‘‘‘insert into hsgt_data(trade_date,hgt,sgt,north_money) values(‘%s‘,‘%s‘,‘%s‘,‘%s‘)‘‘‘ % (trade_date, hgt, sgt, north_money)
                cursor.execute(sql)
                conn_mysql.commit()
                # 统计入库成功数量
                success += 1
            except:
                print(trade_date, hgt, sgt, north_money)
                conn_mysql.rollback()
                # 统计入库失败数量
                fail += 1

            # 统计请求数据量
            count += 1

    # 关闭MySQL操作游标
    cursor.close()
    print(‘沪深港通资金数据获取完毕，新入库数据：%d条‘ % success)
    print(‘沪深港通资金数据获取完毕，入库失败数据：%d条‘ % fail)
    print(‘沪深港通资金数据获取完毕，本次共请求数据：%d条‘ % count)

# ================================================================主函数================================================================
if __name__ == ‘__main__‘:
    # 初始化tushare.pro接口
    pro = ts.pro_api(‘ac16b470869c5d82db5033ae9288f77b282d2b5519507d6d2c72fdd7‘)

    # 获取当天日期
    cur_date = time.strftime("%Y%m%d", time.localtime())

    # 创建MySQL连接对象
    conn_mysql = pymysql.connect(user=‘root‘, password=‘123456‘, database=‘stock‘, charset=‘utf8‘)

    # 创建Redis链接对象
    conn_redis = Redis(host=‘127.0.0.1‘, port=6379)

    moneyflowHsgt(conn_mysql,conn_redis,cur_date)

    tradeTotalamount(conn_mysql, conn_redis, cur_date)

    conn_mysql.close()