def get_live(sec_id, block_size=400):
"""
:param sec_id: list, wind股票代码，如果是全市场，可输入'fulla'或者'ashare'
:param block_size: 内部调用wsq接口一次提取的数量，默认400支
:return: pd.DataFrame, index=sec id, header = [rt_open,rt_high,rt_low,rt_last,rt_vol,rt_amt,rt_vol_ratio,rt_pct_chg_5min]
"""
factor = FactorLoader(start_date=None,
end_date=None,
factor_name='LIVE',
sec_id=sec_id,
block_size=block_size)
ret = factor.load_data()
return ret
def factor_load(start_date, end_date, factor_name, save_file=None, **kwargs):
"""
:param start_date: str, 读取因子数据的开始日期
:param end_date: str, 读取因子数据的结束日期
:param factor_name: str, 因子名称，不区分大小写
:param save_file: str, optional, 保存数据的文件名，可写成 '*.csv' 或者 '*.pkl'
:param kwargs: dict, optional
freq: str, optional, 因子数据的频率， 可选'M', 'W', 'Q', 'S', 'Y'， 参见enums.py - FreqType
tenor: str, optional, 因子数据的周期， 对于截面数据（如换手率，收益率），需要给定数据区间(向前)， 可选数字+FreqType， 如'1Q'
sec_id, str/list, optional, 股票代码或者是指数代码
output_data_format: enum, optional, 参见enums.py - FreqType
MULTI_INDEX_DF: multi-index DataFrame, index=[date, secID], value = factor
PITVOT_TABLE_DF: DataFrame, index=date, columns = secID
is_index: bool, optional, True: 输入的sec_id是指数，实际需要读取的是该指数成分股的因子数据，
False: 直接读取sec_id的因子数据
date_format: str, optional, 日期的格式， 默认'%Y-%m-%d'
:return: pd.DataFrame 整理好的因子数据
"""
if isinstance(factor_name, list):
kwargs = merge(kwargs,
{'output_data_format': OutputFormat.MULTI_INDEX_DF})
factor_names = factor_name
else:
factor_names = [factor_name]
ret = pd.DataFrame()
for factor_name in factor_names:
LOGGER.info('Loading factor data {0}'.format(factor_name))
factor_loader = FactorLoader(start_date=start_date,
end_date=end_date,
factor_name=factor_name,
**kwargs)
factor_data = factor_loader.load_data()
LOGGER.info('factor data {0} is loaded '.format(factor_name))
ret = pd.concat([ret, factor_data], axis=1)
if kwargs.get('reset_col_names'):
ret.columns = factor_names
if save_file:
save_data_to_file(ret, save_file)
LOGGER.critical('Data saved in {0}'.format(save_file))
return ret
def test_query_data(self):
# query_data(api, sec_id, indicator, extra_params=None, start_date=None, end_date=None)
sec_id = ['000001.SZ', '000002.SZ']
start_date = '2017-01-03'
end_date = '2017-01-04'
# w.wsd && factor_name = 'PB'
api = 'w.wsd'
indicator = 'pb_lf'
raw_data = wind_data_provider.query_data(api,
sec_id,
indicator,
start_date=start_date,
end_date=end_date)
calculated = WindData(data=raw_data.Data,
codes=raw_data.Codes,
error_code=raw_data.ErrorCode,
fields=raw_data.Fields,
times=raw_data.Times)
expected = WindData(data=[[0.8822379112243652, 0.8822379112243652],
[2.279218912124634, 2.292412519454956]],
codes=['000001.SZ', '000002.SZ'],
error_code=0,
fields=['PB_LF'],
times=[date(2017, 1, 3),
date(2017, 1, 4)])
self.assertEqual(calculated, expected)
# w.wss && factor_name = 'RETURN'
api = 'w.wss'
factor_name = 'RETURN'
indicator = 'pct_chg_per'
factor_loader = FactorLoader(start_date,
end_date,
factor_name,
sec_id=sec_id,
is_index=False,
tenor='3M')
main_params, extra_params = wind_query_helper.get_query_params(
factor_name)
extra_params[Header.TENOR.value] = factor_loader._get_enum_value(factor_loader.tenor) \
if factor_loader.tenor is not None else None
merged_extra_params = factor_loader._merge_query_params(
extra_params, start_date)
raw_data = wind_data_provider.query_data(
api,
sec_id,
indicator,
extra_params=merged_extra_params,
start_date=start_date,
end_date=start_date)
calculated = WindData(data=raw_data.Data,
codes=raw_data.Codes,
error_code=raw_data.ErrorCode,
fields=raw_data.Fields,
times=len(raw_data.Times))
expected = WindData(data=[[0.43859649122806044, -20.177127454755485]],
codes=['000001.SZ', '000002.SZ'],
error_code=0,
fields=['PCT_CHG_PER'],
times=1)
self.assertEqual(calculated, expected)
# w.wsi && factor_name = 'OHLCV_MIN'
api = 'w.wsi'
indicator = 'open,high,low,close,volume'
start_date = '2017-01-03 09:30:00'
end_date = '2017-01-03 09:32:00'
factor_name = 'OHLCV_MIN'
factor_loader = FactorLoader(start_date,
end_date,
factor_name,
sec_id=sec_id)
main_params, extra_params = wind_query_helper.get_query_params(
factor_name)
merged_extra_params = factor_loader._merge_query_params(
extra_params, start_date)
raw_data = wind_data_provider.query_data(
api,
sec_id,
indicator,
extra_params=merged_extra_params,
start_date=start_date,
end_date=end_date)
calculated = WindData(data=raw_data.Data,
codes=raw_data.Codes,
error_code=raw_data.ErrorCode,
fields=raw_data.Fields,
times=raw_data.Times)
expected = WindData(data=[[
datetime(2017, 1, 3, 9, 30),
datetime(2017, 1, 3, 9, 31),
datetime(2017, 1, 3, 9, 30),
datetime(2017, 1, 3, 9, 31)
], ['000001.SZ', '000001.SZ', '000002.SZ', '000002.SZ'],
[
8.977128569075722, 8.967274421359942,
19.87384420457807, 19.951211967904893
],
[
8.977128569075722, 8.977128569075722,
19.970553908736598, 19.970553908736598
],
[
8.967274421359942, 8.967274421359942,
19.87384420457807, 19.922199056657337
],
[
8.967274421359942, 8.967274421359942,
19.951211967904893, 19.970553908736598
], [673660L, 433800L, 119900L, 146700L]],
codes=['MultiCodes'],
error_code=0,
fields=[
'time', 'windcode', 'open', 'high', 'low',
'close', 'volume'
],
times=[
datetime(2017, 1, 3, 9, 30),
datetime(2017, 1, 3, 9, 31),
datetime(2017, 1, 3, 9, 30),
datetime(2017, 1, 3, 9, 31)
])
self.assertEqual(calculated, expected)
# # w.wsq && factor_name = 'LIVE'
api = 'w.wsq'
indicator = 'rt_open,rt_high,rt_low,rt_last,rt_vol,rt_amt,rt_vol_ratio,rt_pct_chg_5min'
raw_data = wind_data_provider.query_data(api, sec_id, indicator)
calculated = WindData(data=len(raw_data.Data),
codes=raw_data.Codes,
error_code=raw_data.ErrorCode,
fields=raw_data.Fields,
times=len(raw_data.Times))
expected = WindData(data=8,
codes=['000001.SZ', '000002.SZ'],
error_code=0,
fields=[
'RT_OPEN', 'RT_HIGH', 'RT_LOW', 'RT_LAST',
'RT_VOL', 'RT_AMT', 'RT_VOL_RATIO',
'RT_PCT_CHG_5MIN'
],
times=1)
self.assertEqual(calculated, expected)
# # w.wset && factor_name = 'INDUSTRY_WEIGHT_C1'
api = 'w.wset'
index_id = '000300.SH'
short_params = 'windcode=' + index_id
params = short_params if start_date is None else short_params + ';date=' + str(
start_date)
raw_data = w.wset('IndexConstituent', params)
calculated = WindData(data=len(raw_data.Data),
codes=len(raw_data.Codes),
error_code=raw_data.ErrorCode,
fields=raw_data.Fields,
times=len(raw_data.Times))
expected = WindData(
data=4,
codes=300,
error_code=0,
fields=['date', 'wind_code', 'sec_name', 'i_weight'],
times=1)
self.assertEqual(calculated, expected)
raw_data = w.wset('IndexConstituent', short_params)
calculated = WindData(data=len(raw_data.Data),
codes=len(raw_data.Codes),
error_code=raw_data.ErrorCode,
fields=raw_data.Fields,
times=len(raw_data.Times))
expected = WindData(
data=4,
codes=300,
error_code=0,
fields=['date', 'wind_code', 'sec_name', 'i_weight'],
times=1)
self.assertEqual(calculated, expected)