def collect_all():
df = stock_industry_dao.get_list()
for code in df['code'].values:
try:
collect_single(code)
time.sleep(1)
except Exception as e:
logger.error(repr(e))
def industry_filter(code1, code2):
industry_df = stock_industry_dao.get_list()
bk1 = industry_df[industry_df['code'] == code1]['bk_name'].values[0]
bk2 = industry_df[industry_df['code'] == code2]['bk_name'].values[0]
if bk1 == bk2:
return bk1, bk2
else:
return False
def collect_full():
df = stock_industry_dao.get_list()
now = datetime.now().strftime('%Y-%m-%d')
for code in df['code'].values:
try:
collect_single(code=code, start='2015-01-01', end=now)
except Exception as e:
logger.error(
"collect technical features failed code:%s, exception:%s" %
(code, repr(e)))
def init(self, context):
super(KDJStrategy, self).init(context)
# context.pool = stock_pool_dao.get_list()['code'].values
context.pool = stock_industry_dao.get_list()['code'].values
self.context = context
def test_get_list(self):
df = stock_industry_dao.get_list()
logger.debug(df.head())
def collect_all(futu_quote_ctx):
now = datetime.now().strftime('%Y-%m-%d')
df_industry = stock_industry_dao.get_list()
for index,row in df_industry.iterrows():
code = row['code']
collect_single(code=code, start='2013-01-01', end=now, futu_quote_ctx=futu_quote_ctx)
# ae_h - 2018/7/5
from dao.basic.stock_industry_dao import stock_industry_dao
import pandas as pd
def fill_zero(code):
code = str(code)
code = code.zfill(6)
return code
industry_df = stock_industry_dao.get_list()
# bk_code = set(list(industry_df['bk_code'].values))
# print(bk_code)
df = pd.read_csv(
'/Users/yw.h/quant-awesome/quant/strategy/pair/pair_result.csv')
# print(industry_df[industry_df['code'] == '000001']['bk_code'])
list = []
for index, row in df.iterrows():
code1 = fill_zero(str(int(row['stock1'])))
code2 = fill_zero(str(int(row['stock2'])))
bk1 = industry_df[industry_df['code'] == code1]['bk_name'].values[0]
bk2 = industry_df[industry_df['code'] == code2]['bk_name'].values[0]
if bk1 == bk2:
list.append((code1 + bk1, code2 + bk2))