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