def QA_fetch_stock_full(date, format='numpy', collections=DATABASE.stock_day):
    '获取全市场的某一日的数据'
    Date = str(date)[0:10]
    if QA_util_date_valid(Date) is True:

        __data = []
        for item in collections.find({
                "date_stamp": QA_util_date_stamp(Date)}, batch_size=10000):
            __data.append([str(item['code']), float(item['open']), float(item['high']), float(
                item['low']), float(item['close']), float(item['vol']), item['date']])
        # 多种数据格式
        if format in ['n', 'N', 'numpy']:
            __data = numpy.asarray(__data)
        elif format in ['list', 'l', 'L']:
            __data = __data
        elif format in ['P', 'p', 'pandas', 'pd']:
            __data = DataFrame(__data, columns=[
                'code', 'open', 'high', 'low', 'close', 'volume', 'date'])
            __data['date'] = pd.to_datetime(__data['date'])
            __data = __data.set_index('date', drop=False)
        else:
            print("QA Error QA_fetch_stock_full format parameter %s is none of  \"P, p, pandas, pd , json, dict , n, N, numpy, list, l, L, !\" " % format)

        return __data
    else:
        QA_util_log_info(
            'QA Error QA_fetch_stock_full data parameter date=%s not right' % date)
获取全市场的某一日的数据