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Commit 7f602e97 authored by Dr.李's avatar Dr.李
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modified sql script for fetching data

parent 65c88236
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Showing with 77 additions and 70 deletions
alphamind/data/dbmodel/models.py
View file @ 7f602e97
......@@ -1677,6 +1677,9 @@ class FullFactorView(Base):
AERODEF = Column(BigInteger)
Conglomerates = Column(BigInteger)
COUNTRY = Column(BigInteger)
d_srisk = Column(Float(53))
s_srisk = Column(Float(53))
l_srisk = Column(Float(53))
if __name__ == '__main__':
......
alphamind/data/engines/sqlengine.py
View file @ 7f602e97
......@@ -35,6 +35,7 @@ from alphamind.data.dbmodel.models import RiskCovLong
from alphamind.data.dbmodel.models import RiskExposure
from alphamind.data.dbmodel.models import Market
from alphamind.data.dbmodel.models import FullFactorView
from alphamind.data.dbmodel.models import Universe as UniverseTable
from alphamind.data.transformer import Transformer
from PyFin.api import advanceDateByCalendar
from PyFin.Analysis.SecurityValueHolders import SecurityLatestValueHolder
......@@ -99,11 +100,11 @@ def append_industry_info(df):
def _map_risk_model_table(risk_model: str) -> tuple:
if risk_model == 'day':
return RiskCovDay, SpecificRiskDay
return RiskCovDay, FullFactorView.d_srisk
elif risk_model == 'short':
return RiskCovShort, SpecificRiskShort
return RiskCovShort, FullFactorView.s_srisk
elif risk_model == 'long':
return RiskCovLong, SpecificRiskLong
return RiskCovLong, FullFactorView.l_srisk
else:
raise ValueError("risk model name {0} is not recognized".format(risk_model))
......@@ -172,7 +173,8 @@ class SqlEngine(object):
return strategy_names
def fetch_codes(self, ref_date: str, universe: Universe) -> List[int]:
query = universe.query(ref_date)
cond = universe.query(ref_date)
query = select([UniverseTable.trade_date, UniverseTable.code]).distinct().where(cond)
cursor = self.engine.execute(query)
codes_set = {c[1] for c in cursor.fetchall()}
return sorted(codes_set)
......@@ -182,7 +184,8 @@ class SqlEngine(object):
start_date: str = None,
end_date: str = None,
dates: Iterable[str] = None) -> pd.DataFrame:
query = universe.query_range(start_date, end_date, dates)
cond = universe.query_range(start_date, end_date, dates)
query = select([UniverseTable.trade_date, UniverseTable.code]).distinct().where(cond)
return pd.read_sql(query, self.engine)
def fetch_dx_return(self,
......@@ -219,9 +222,11 @@ class SqlEngine(object):
end_date = advanceDateByCalendar('china.sse', end_date, str(horizon) + 'b').strftime('%Y-%m-%d')
q2 = universe.query_range(start_date, end_date).alias('temp_universe')
big_table = join(DailyReturn, q2,
and_(DailyReturn.trade_date == q2.c.trade_date, DailyReturn.code == q2.c.code))
cond = universe.query_range(start_date, end_date)
big_table = join(DailyReturn, UniverseTable,
and_(DailyReturn.trade_date == UniverseTable.trade_date,
DailyReturn.code == UniverseTable.code,
cond))
stats = func.sum(self.ln_func(1. + DailyReturn.d1)).over(
partition_by=DailyReturn.code,
......@@ -229,8 +234,7 @@ class SqlEngine(object):
rows=(0, horizon)).label('dx')
query = select([DailyReturn.trade_date, DailyReturn.code, stats]) \
.select_from(big_table) \
.where(DailyReturn.trade_date.between(start_date, end_date))
.select_from(big_table)
df = pd.read_sql(query, self.session.bind)
......@@ -310,10 +314,12 @@ class SqlEngine(object):
real_end_date = end_date
real_dates = None
q2 = universe.query_range(real_start_date, real_end_date, real_dates).alias('temp_universe')
cond = universe.query_range(real_start_date, real_end_date, real_dates)
big_table = join(FullFactorView, q2,
and_(FullFactorView.trade_date == q2.c.trade_date, FullFactorView.code == q2.c.code))
big_table = join(FullFactorView, UniverseTable,
and_(FullFactorView.trade_date == UniverseTable.trade_date,
FullFactorView.code == UniverseTable.code,
cond))
query = select([FullFactorView.trade_date, FullFactorView.code, FullFactorView.isOpen] + factor_cols) \
.select_from(big_table)
......@@ -365,7 +371,7 @@ class SqlEngine(object):
codes: Iterable[int],
risk_model: str = 'short',
excluded: Iterable[str] = None) -> Tuple[pd.DataFrame, pd.DataFrame]:
risk_cov_table, special_risk_table = _map_risk_model_table(risk_model)
risk_cov_table, special_risk_col = _map_risk_model_table(risk_model)
cov_risk_cols = [risk_cov_table.__table__.columns[f] for f in total_risk_factors]
query = select([risk_cov_table.FactorID,
......@@ -375,14 +381,9 @@ class SqlEngine(object):
)
risk_cov = pd.read_sql(query, self.engine).sort_values('FactorID')
risk_exposure_cols = [RiskExposure.__table__.columns[f] for f in total_risk_factors if f not in set(excluded)]
big_table = outerjoin(special_risk_table, RiskExposure,
and_(special_risk_table.trade_date == RiskExposure.trade_date,
special_risk_table.code == RiskExposure.code))
query = select(
[RiskExposure.code, special_risk_table.SRISK] + risk_exposure_cols) \
.select_from(big_table) \
.where(and_(RiskExposure.trade_date == ref_date, RiskExposure.code.in_(codes)))
risk_exposure_cols = [FullFactorView.__table__.columns[f] for f in total_risk_factors if f not in set(excluded)]
query = select([FullFactorView.code, special_risk_col] + risk_exposure_cols) \
.where(and_(FullFactorView.trade_date == ref_date, FullFactorView.code.in_(codes)))
risk_exp = pd.read_sql(query, self.engine)
......@@ -396,7 +397,7 @@ class SqlEngine(object):
risk_model: str = 'short',
excluded: Iterable[str] = None) -> Tuple[pd.DataFrame, pd.DataFrame]:
risk_cov_table, special_risk_table = _map_risk_model_table(risk_model)
risk_cov_table, special_risk_col = _map_risk_model_table(risk_model)
cov_risk_cols = [risk_cov_table.__table__.columns[f] for f in total_risk_factors]
......@@ -414,17 +415,16 @@ class SqlEngine(object):
if not excluded:
excluded = []
risk_exposure_cols = [RiskExposure.__table__.columns[f] for f in total_risk_factors if f not in set(excluded)]
big_table = outerjoin(special_risk_table, RiskExposure,
and_(special_risk_table.trade_date == RiskExposure.trade_date,
special_risk_table.code == RiskExposure.code))
risk_exposure_cols = [FullFactorView.__table__.columns[f] for f in total_risk_factors if f not in set(excluded)]
q2 = universe.query_range(start_date, end_date, dates).alias('temp_universe')
big_table = join(big_table, q2,
and_(special_risk_table.trade_date == q2.c.trade_date, special_risk_table.code == q2.c.code))
cond = universe.query_range(start_date, end_date, dates)
big_table = join(FullFactorView, UniverseTable,
and_(FullFactorView.trade_date == UniverseTable.trade_date,
FullFactorView.code == UniverseTable.code,
cond))
query = select(
[RiskExposure.trade_date, RiskExposure.code, special_risk_table.SRISK] + risk_exposure_cols) \
[FullFactorView.trade_date, FullFactorView.code, special_risk_col] + risk_exposure_cols) \
.select_from(big_table)
risk_exp = pd.read_sql(query, self.engine)
......@@ -457,27 +457,27 @@ class SqlEngine(object):
dates: Iterable[str] = None,
category: str = 'sw'):
industry_category_name = _map_industry_category(category)
cond = universe.query_range(start_date, end_date, dates)
if dates:
q1 = select([Industry.trade_date,
Industry.code,
Industry.industryID1.label('industry_code'),
Industry.industryName1.label('industry')]).where(
and_(Industry.industry == industry_category_name,
Industry.trade_date.in_(dates))).alias('temp_industry')
big_table = join(Industry, UniverseTable,
and_(Industry.trade_date == UniverseTable.trade_date,
Industry.code == UniverseTable.code,
Industry.industry == industry_category_name,
Industry.trade_date.in_(dates),
cond))
else:
q1 = select([Industry.trade_date,
big_table = join(Industry, UniverseTable,
and_(Industry.trade_date == UniverseTable.trade_date,
Industry.code == UniverseTable.code,
Industry.industry == industry_category_name,
Industry.trade_date.between(start_date, end_date),
cond))
query = select([Industry.trade_date,
Industry.code,
Industry.industryID1.label('industry_code'),
Industry.industryName1.label('industry')]).where(
and_(Industry.industry == industry_category_name,
Industry.trade_date.between(start_date, end_date))).alias('temp_industry')
q2 = universe.query_range(start_date, end_date, dates).alias('temp_universe')
big_table = join(q1, q2,
and_(q1.c.trade_date == q2.c.trade_date, q1.c.code == q2.c.code))
query = select([q1]).select_from(big_table)
Industry.industryName1.label('industry')]).select_from(big_table)
return pd.read_sql(query, self.engine)
def fetch_data(self, ref_date: str,
......@@ -551,18 +551,19 @@ if __name__ == '__main__':
from PyFin.api import *
from alphamind.api import alpha_logger
db_url = 'postgresql+psycopg2://postgres:A12345678!@10.63.6.220/alpha'
db_url = 'postgresql+psycopg2://postgres:we083826@localhost/alpha'
# db_url = 'mssql+pymssql://licheng:A12345678!@10.63.6.220/alpha'
universe = Universe('custom', ['zz500'])
engine = SqlEngine(db_url)
start_date = '2017-08-01'
ref_date = '2017-08-02'
start_date = '2012-01-01'
end_date = '2017-08-31'
dates = makeSchedule(start_date, end_date, '1w', 'china.sse')
alpha_logger.info('start')
# codes = engine.fetch_codes(universe=universe, ref_date=ref_date)
codes = engine.fetch_codes_range(universe=universe, dates=dates)
data1 = engine.fetch_factor_range(universe=universe,
start_date=start_date,
......@@ -578,3 +579,4 @@ if __name__ == '__main__':
alpha_logger.info('end')
data2 = engine.fetch_codes_range(universe, start_date=start_date, end_date=end_date, dates=dates)
alpha_logger.info('end')
alpha_logger.info(len(codes))
alphamind/data/engines/universe.py
View file @ 7f602e97
......@@ -56,35 +56,37 @@ class Universe(object):
return all_and_conditions, all_or_conditions
def query(self, ref_date):
query = select([UniverseTable.trade_date, UniverseTable.code]).distinct()
all_and_conditions, all_or_conditions = self._create_condition()
query = query.where(
and_(
if all_or_conditions:
query = and_(
UniverseTable.trade_date == ref_date,
or_(
and_(*all_and_conditions),
*all_or_conditions
)
)
else:
query = and_(
UniverseTable.trade_date == ref_date,
*all_and_conditions
)
return query
def query_range(self, start_date=None, end_date=None, dates=None):
query = select([UniverseTable.trade_date, UniverseTable.code]).distinct()
all_and_conditions, all_or_conditions = self._create_condition()
dates_cond = UniverseTable.trade_date.in_(dates) if dates else UniverseTable.trade_date.between(start_date, end_date)
query = query.where(
and_(
if all_or_conditions:
query = and_(
dates_cond,
or_(
and_(*all_and_conditions),
*all_or_conditions
)
)
)
else:
query = and_(dates_cond, *all_and_conditions)
return query
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