def xbar(self, stock, day=None, type=0):
stock = stock[0:6]
df = cache.get('hq_{}'.format(stock))
if df is None or len(df) == 0:
df = self.Hdf.select('/df_{}'.format(stock))
cache.add('hq_{}'.format(stock), df)
if df is not None:
if type == 0:
try:
close, ltm = df.loc[day]
return [{'day': day, 'close': round(close, 2), 'ltm': ltm}]
except Exception as e:
simulation_logger.info('miss:{}:{}:{}'.format(
e, stock, day))
return []
else:
df = df[df.index <= day]
if not df.empty:
close = df['close'].values[-1]
ltm = df['ltm'].values[-1]
day = df.index[-1]
return [{'day': day, 'close': round(close, 2), 'ltm': ltm}]
else:
return []
else:
return []
def find_pinds(self, day):
# 涨跌停股
df = cache.get('find_pinds')
if df is None or len(df) == 0:
df = pd.read_sql('select * from pind', engine)
cache.add('find_pinds', df)
return list(df[(df['date'] == day) & (df['status'] == 1)]['code'])
def find_ah_connection(self, date):
df = cache.get('find_ah_connection')
if df is None or len(df) == 0:
df = pd.read_sql('select sse_code from hh_stock_connection',
engine)
cache.add('find_ah_connection', df)
return list(df['sse_code'])
def find_margin_code(self, date):
'''筛选融资融券股票'''
df = cache.get('find_margin_code')
if df is None or len(df) == 0:
df = pd.read_sql(
'select code, date from margintrade WHERE date = "{}"'.format(
date), engine)
df[['date']] = df[['date']].astype(str)
return list(df[df['date'] == date]['code'])
def find_regionals_code(self, date, region=None):
'''获取地域股票'''
df = cache.get('find_regionals_code')
if df is None or len(df) == 0:
df = pd.read_sql('select code, region from regionals', engine)
cache.add('find_regionals_code', df)
if region:
return list(df[df['region'].isin(region)]['code'])
return list(df['code'])
def find_stock_codes(self):
df = cache.get('find_stock_codes')
if df is not None and len(df) > 0:
return df
else:
df = pd.read_sql('select code from basic', engine)
stocks = list(df['code'])
cache.add('find_stock_codes', stocks)
return stocks
def find_all_code(self, date):
'''获取所有股票'''
df = cache.get('find_all_code')
if df is None or len(df) == 0:
df = pd.read_sql('select code, list_date, delist_date from basic',
engine)
df[['list_date', 'delist_date']] = df[['list_date',
'delist_date']].astype(str)
cache.add('find_all_code', df)
return list(df[(df['list_date'] <= str(date))
& (df['delist_date'] > date)]['code'])
def find_st(self, date):
'''获取st'''
df = cache.get('find_st')
if df is None or len(df) == 0:
df = pd.read_sql('select code, entry_dt, remove_dt from st',
engine)
df[['entry_dt', 'remove_dt']] = df[['entry_dt',
'remove_dt']].astype(str)
cache.add('find_st', df)
return list(df[(df['entry_dt'] <= date)
& (df['remove_dt'] >= date)]['code'])
def find_industry_code(self, date, index):
'''获取行业成份股'''
df = cache.get('find_industry_code')
if df is None or len(df) == 0:
df = pd.read_sql(
'select code, industry_code, hy_code, start_date, end_date from industry',
engine)
df[['start_date', 'end_date']] = df[['start_date',
'end_date']].astype(str)
cache.add('find_industry_code', df)
return list(df[(df['hy_code'].isin(index)) & (df['start_date'] <= date)
& (df['end_date'] > date)]['code'])
def find_second_new(self, date):
'''获取次新股票'''
df = cache.get('find_second_new')
if df is None or len(df) == 0:
df = pd.read_sql('select code,list_date,delist_date from basic',
engine)
df[['list_date', 'delist_date']] = df[['list_date',
'delist_date']].astype(str)
cache.add('find_second_new', df)
return list(df[df['list_date'] > str(
datetime.strptime(date, '%Y-%m-%d').date() -
timedelta(days=365))]['code'])
def find_conseption(self, date, industry=None):
'''筛选股票股票，时间+行业'''
df = cache.get('find_conseption')
if df is None or len(df) == 0:
df = pd.read_sql(
'select gn_code as category, code, list_date, delist_date from conseption',
engine)
df[['list_date', 'delist_date']] = df[['list_date',
'delist_date']].astype(str)
cache.add('find_conseption', df)
return list(
df[(df['category'].isin(industry)) & (df['list_date'] <= date) &
(df['delist_date'] > date)]['code'])
def find_index_code(self, date, index):
'''获取指数成份股,可能为in数据'''
category = [INDEXS.get(str(i), i) for i in index]
df = cache.get('find_index_code')
if df is None or len(df) == 0:
df = pd.read_sql(
'select code, category, list_date, delist_date from indexs',
engine)
df[['list_date', 'delist_date']] = df[['list_date',
'delist_date']].astype(str)
cache.add('find_index_code', df)
return list(
df[(df['category'].isin(category)) & (df['list_date'] <= date) &
(df['delist_date'] > date)]['code'])