怎么使用Joinquant做实盘行情数据

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如下图，如果运行行情数据下载时候，是在交易日中的话比如2点半或者上午8点，如果填写的endDate是当天或者之后的日期，那么返回数据会自动填充到下午3点交易时候。此时之后的数据都是交易量为0，价格就是2点半时候价格。

所以在用作实盘数据分析时候，必须要填入endDate的分钟时间为当前时间，才可以确保不会出现控制。整体代码更新如下：

# encoding: UTF-8 from __future__ import print_functionimport sysimport jsonfrom datetime import datetime,date,timedeltafrom time import time, sleep from pymongo import MongoClient, ASCENDINGimport pandas as pd from vnpy.trader.vtObject import VtBarData, VtTickDatafrom vnpy.trader.app.ctaStrategy.ctaBase import (MINUTE_DB_NAME,                                                 DAILY_DB_NAME,                                                 TICK_DB_NAME) import jqdatasdk as jq # 加载配置config = open('config.json')setting = json.load(config) mc = MongoClient()  # Mongo连接dbMinute = mc[MINUTE_DB_NAME]  # 数据库# dbDaily = mc[DAILY_DB_NAME]# dbTick = mc[TICK_DB_NAME] USERNAME = setting['Username']PASSWORD = setting['Password']jq.auth(USERNAME, PASSWORD) FIELDS = ['open', 'high', 'low', 'close', 'volume']  # ----------------------------------------------------------------------def generateVtBar(row, symbol):    """生成K线"""    bar = VtBarData()     bar.symbol = symbol    bar.exchange = "SHFE"    bar.vtSymbol = bar.vtSymbol = '.'.join([bar.symbol, bar.exchange])    bar.open = row['open']    bar.high = row['high']    bar.low = row['low']    bar.close = row['close']    bar.volume = row['volume']    bardatetime = row.name    bar.date = bardatetime.strftime("%Y%m%d")     bar.time = bardatetime.strftime("%H%M%S")    # 将bar的时间改成提前一分钟    hour = bar.time[0:2]    minute = bar.time[2:4]    sec = bar.time[4:6]    if minute == "00":        minute = "59"         h = int(hour)        if h == 0:            h = 24         hour = str(h - 1).rjust(2, '0')    else:        minute = str(int(minute) - 1).rjust(2, '0')    bar.time = hour + minute + sec     bar.datetime = datetime.strptime(' '.join([bar.date, bar.time]), '%Y%m%d %H%M%S')    return bar  # ----------------------------------------------------------------------def jqdownloadMinuteBarBySymbol(symbol,startDate,endDate):    """下载某一合约的分钟线数据"""    start = time()     cl = dbMinute[symbol]    cl.ensure_index([('datetime', ASCENDING)], unique=True)  # 添加索引     df = jq.get_price(setting[symbol],start_date = startDate,end_date = endDate, frequency='1m', fields=FIELDS,skip_paused = True)    for ix, row in df.iterrows():        bar = generateVtBar(row, symbol)        d = bar.__dict__        flt = {'datetime': bar.datetime}        cl.replace_one(flt, d, True)     end = time()    cost = (end - start) * 1000     print(u'合约%s的分钟K线数据下载完成%s - %s，耗时%s毫秒' % (symbol, df.index[0], df.index[-1], cost))    print(jq.get_query_count()) def jqdownloadMappingExcel(exportpath = "C:\Project\\"):    getfuture = jq.get_all_securities(types=['futures'], date=None)    # list: 用来过滤securities的类型, list元素可选: 'stock', 'fund', 'index', 'futures', 'etf', 'lof', 'fja', 'fjb'.types为空时返回所有股票, 不包括基金, 指数和期货    getfuture.to_excel(                    exportpath + "Mapping" + str(date.today())  + "futures.xls",                    index=True, header=True)  # ----------------------------------------------------------------------def downloadAllMinuteBar(days=10):    """下载所有配置中的合约的分钟线数据"""    print('-' * 50)    print(u'开始下载合约分钟线数据')    print('-' * 50)     startDt = datetime.today() - days * timedelta(1)    startDate = startDt.strftime('%Y-%m-%d')     # 添加下载任务    enddt = datetime.today()    endDate = enddt.strftime('%Y-%m-%d %H:%M:%S')      jqdownloadMinuteBarBySymbol('rb1910', startDate, endDate)     print('-' * 50)    print    u'合约分钟线数据下载完成'    print('-' * 50) if __name__ == '__main__':    # jqdownloadMappingExcel()    #下载主力合约     downloadAllMinuteBar(days=10)    #下载单个品种    # jqdownloadMinuteBarBySymbol('510050.XSHG',startDate,endDate)

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