def getTradeday(start, end, fre='month'):
trade_day = DataAPI.TradeCalGet(exchangeCD=u"XSHG",
beginDate=start,
endDate=end,
field=u"",
pandas="1")
trade_day = trade_day[trade_day.isOpen == 1][[
'calendarDate', 'isWeekEnd', 'isMonthEnd'
]]
if fre == 'month':
df = trade_day[trade_day.isMonthEnd == 1]['calendarDate']
elif fre == 'week':
df = trade_day[trade_day.isWeekEnd == 1]['calendarDate']
elif fre == 'day':
df = trade_day['calendarDate']
elif fre == '2week':
df = trade_day[trade_day.isWeekEnd == 1][['calendarDate', 'isWeekEnd']]
df = df[1::2]
df = df['calendarDate']
else:
print 'change fre parameter'
raise ValueError
df.index = range(len(df))
df = pd.DataFrame(df)
df['calendarDate'] = pd.to_datetime(df['calendarDate'], format='%Y-%m-%d')
df['calendarDate'] = df['calendarDate'].apply(
lambda x: x.strftime("%Y%m%d"))
df = df['calendarDate']
return df
def get_features(security_id='', start_date='', end_date='', min_unit="5"):
df = DataAPI.TradeCalGet(exchangeCD=u"XSHG,XSHE",
beginDate=start_date.replace('-', ''),
endDate=end_date.replace('-', ''),
isOpen=u"1",
field=u"calendarDate",
pandas="1")
t_dates = list(df['calendarDate'])
df_min = DataAPI.MktBarHistDateRangeGet(securityID=security_id,
startDate=start_date.replace(
'-', ''),
endDate=end_date.replace('-', ''),
unit=min_unit,
field=u"",
pandas="1")
df_min['vwap'] = df_min['totalValue'] / df_min['totalVolume']
# TODO normally it should be closePrice
df_min['ret'] = df_min[['vwap'
]].rolling(2).apply(lambda x: x[-1] / x[0] - 1)
df_min['label'] = [
1 if item >= 0.0 else 0 for item in (([0.0] + list(df_min['ret']))[1:])
]
# df_min['dealPrice'] = (df_min['openPrice'] + df_min['vwap'])/2
df_min['dealPrice'] = df_min['vwap']
return df_min
def get_trading_day_list(self, start, end, frequency, exchange_cd='XSHG'):
"""
输入起始日期和频率，即可获得日期列表（daily包括起始日，其余的都是位于起始日中间的）
输入：
start，开始日期，'YYYYMMDD'形式
end，截止日期，'YYYYMMDD'形式
frequency，频率，day为所有交易日，week为每周最后一个交易日，month为每月最后一个交易日，quarter为每季最后一个交易日
返回：
获得list型日期列表，以'YYYYMMDD'形式存储
"""
df = DataAPI.TradeCalGet(exchangeCD=exchange_cd,
beginDate=start,
endDate=end,
field=u"",
pandas="1")
df['calendarDate'] = df['calendarDate'].apply(
lambda x: x.replace('-', ''))
if frequency == 'quarter':
res = df.query('isQuarterEnd==1')
elif frequency == 'semi':
res = df.query('isQuarterEnd==1')
res = res.reset_index()
res = res.loc[res['calendarDate'].apply(
lambda x: (x[4:6] == '06' or x[4:6] == '12'))]
elif frequency == 'month':
res = df.query('isMonthEnd==1')
elif frequency == 'week':
res = df.query('isWeekEnd==1')
elif frequency == 'day':
res = df.query('isOpen==1')
else:
raise ValueError('调仓频率必须为day/week/month/quarter/semi！！！')
return list(res['calendarDate'])
def get_features(security_id=u"300634.XSHE", start_date='20191202', end_date='20191206', min_unit="1", tick=False,
bc='', win_len=20):
df = DataAPI.TradeCalGet(exchangeCD=u"XSHG,XSHE", beginDate=start_date.replace('-', ''),
endDate=end_date.replace('-', ''), isOpen=u"1",
field=u"calendarDate", pandas="1")
t_dates = list(set(df['calendarDate']))
df_min = DataAPI.MktBarHistDateRangeGet(securityID=security_id, startDate=start_date.replace('-', ''),
endDate=end_date.replace('-', ''),
unit=min_unit, field=u"", pandas="1")
df_bc_min = DataAPI.MktBarHistDateRangeGet(securityID=bc, startDate=start_date.replace('-', ''),
endDate=end_date.replace('-', ''),
unit=min_unit, field=u"", pandas="1")
lst = []
for date in t_dates:
_df_min = df_min[df_min.dataDate == date]
_df_bc_min = df_bc_min[df_bc_min.dataDate == date]
_df = get_features_by_date(security_id=security_id, date=date, min_unit=min_unit, tick=tick, df_min=_df_min,
df_bc_min=_df_bc_min, win_len=win_len)
lst.append(_df)
try:
ret = pd.concat(lst, axis=0)
except Exception as ex:
logger.warn('concat the feautres for security id:{0} with error:{1}'.format(security_id, ex))
ret = None
return ret
def uqer1(start, end, fre='day'):
client = uqer.Client(
token='811e6680b27759e045ed16e2ed9b408dc8a0cbffcf14e4bb755144dd45fa5ea0'
)
trade_day = DataAPI.TradeCalGet(exchangeCD=u"XSHG",
beginDate=start,
endDate=end,
field=u"",
pandas="1")
trade_day = trade_day[trade_day.isOpen == 1][[
'calendarDate', 'isWeekEnd', 'isMonthEnd'
]]
if fre == 'month':
df = trade_day[trade_day.isMonthEnd == 1]['calendarDate']
elif fre == 'week':
df = trade_day[trade_day.isWeekEnd == 1]['calendarDate']
elif fre == 'day':
df = trade_day['calendarDate']
elif fre == '2week':
df = trade_day[trade_day.isWeekEnd == 1][['calendarDate', 'isWeekEnd']]
df = df[1::2]
df = df['calendarDate']
else:
print 'change fre parameter'
raise ValueError
df.index = range(len(df))
df = pd.DataFrame(df)
df['calendarDate'] = pd.to_datetime(df['calendarDate'], format='%Y-%m-%d')
df['calendarDate'] = df['calendarDate'].apply(
lambda x: x.strftime("%Y%m%d"))
df = df['calendarDate']
df.name = 'trade_day'
return df
def tdaysoffset_uqer(tdate, N, fre, offset):
client = uqer.Client(
token='811e6680b27759e045ed16e2ed9b408dc8a0cbffcf14e4bb755144dd45fa5ea0'
)
all_day = DataAPI.TradeCalGet(exchangeCD=u"XSHG",
beginDate='19000101',
endDate='20181231',
field=u"",
pandas="1")
all_day = all_day[all_day.isOpen == 1]
all_day = all_day.reset_index(drop=True)
all_day['calendarDate'] = pd.to_datetime(all_day['calendarDate'],
format='%Y-%m-%d')
all_day['calendarDate'] = all_day['calendarDate'].apply(
lambda x: x.strftime("%Y%m%d"))
tdate_index = all_day[all_day.calendarDate <= tdate]
tdate_index = len(tdate_index) - 1
if fre == 'day':
t_index = tdate_index + N * offset
elif fre == 'week':
t_index = tdate_index + N * 5 * offset
if t_index > len(all_day) - 1:
t = None
elif t_index < 0:
t = None
else:
t = all_day.ix[t_index, 'calendarDate']
return t
def custom_fetch_date(self, start_date, end_date, interval):
df = DataAPI.TradeCalGet(exchangeCD=u"XSHG",beginDate=start_date,
endDate=end_date, field='calendarDate,isOpen',pandas="1")
df = df[df['isOpen']==1]
str_trade_date_list = list(set(df['calendarDate']))
str_trade_date_list.sort(reverse=False)
str_trade_date_list = list(filter(lambda x: str_trade_date_list.index(x) % interval == 0, str_trade_date_list))
trade_date_list = [datetime.datetime.strptime(d, '%Y-%m-%d').date() for d in str_trade_date_list]
return trade_date_list
def get_latest_trading_day_map(self):
df = DataAPI.TradeCalGet(exchangeCD=u"XSHG", field=u"", pandas="1")
df['calendarDate'] = df['calendarDate'].apply(
lambda x: x.replace('-', ''))
trading_day_series = df[df['isOpen'] == 1]['calendarDate']
trading_day_series.index = trading_day_series.values
df.set_index('calendarDate', inplace=True)
df['tradeDate'] = trading_day_series
df['tradeDate'].fillna(method='ffill', inplace=True)
return df['tradeDate']
def get_month_start_end_dates(start_date='', end_date=''):
df = DataAPI.TradeCalGet(exchangeCD=u"XSHG,XSHE", beginDate=start_date, endDate=end_date, isOpen=u"1",
field=u"", pandas="1")
t_dates = list(set(df['calendarDate']))
t_dates = sorted(t_dates)
df = df[df.isMonthEnd == 1]
t_month_end = list(set(df['calendarDate']))
t_month_end = sorted(t_month_end)
ret = [t_dates[0]]
for d in t_month_end:
try:
_idx = t_dates.index(d)
ret.append(d)
ret.append(t_dates[_idx + 1])
except Exception as ex:
pass
return ret
def getTradeday(self):
# if not os.path.isfile('tradeday_%s_%s.csv'%(self.start,self.end)):
# trade_day = DataAPI.TradeCalGet(exchangeCD=u"XSHG",beginDate=self.start,endDate=self.end,field=u"",pandas="1")
# trade_day.to_csv('tradeday_%s_%s.csv'%(self.start,self.end))
#
# trade_day = pd.read_csv('tradeday_%s_%s.csv'%(self.start,self.end),index_col = 0)
trade_day = DataAPI.TradeCalGet(exchangeCD=u"XSHG",
beginDate=self.start,
endDate=self.end,
field=u"",
pandas="1")
trade_day = trade_day[trade_day.isOpen == 1][[
'calendarDate', 'isWeekEnd', 'isMonthEnd'
]]
if self.fre == 'month':
df = trade_day[trade_day.isMonthEnd == 1]['calendarDate']
elif self.fre == 'week':
df = trade_day[trade_day.isWeekEnd == 1]['calendarDate']
elif self.fre == 'day':
df = trade_day['calendarDate']
elif self.fre == '2week':
df = trade_day[trade_day.isWeekEnd == 1][[
'calendarDate', 'isWeekEnd'
]]
df = df[1::2]
df = df['calendarDate']
else:
print 'change fre parameter'
raise ValueError
df.index = range(len(df))
df = pd.DataFrame(df)
df['calendarDate'] = pd.to_datetime(df['calendarDate'],
format='%Y-%m-%d')
df['calendarDate'] = df['calendarDate'].apply(
lambda x: x.strftime("%Y%m%d"))
df = df['calendarDate']
return df
def _fetch_all_date(self, start_date, end_date, columns):
from uqer import DataAPI
field = 'calendarDate,' + columns
df = DataAPI.TradeCalGet(exchangeCD=u"XSHG",beginDate=start_date,
endDate=end_date, field=field,pandas="1")
return df
