def set_all_data(self, quantity_change_info, price_change_info,
index_info):
df, _ = self.read()
if df.empty:
logger.error("read empty file for:%s" % self.code)
return False
#modify price and quanity for all split-adjusted share prices
df = self.adjust_share(df, quantity_change_info)
if df.empty:
logger.error("adjust share %s failed" % self.code)
return False
df = self.qfq(df, price_change_info)
if df.empty:
logger.error("qfq %s failed" % self.code)
return False
#transfer data to split-adjusted share prices
df = self.transfer2adjusted(df)
#compute strength relative index
df = self.relative_index_strength(df, index_info)
if df is None:
logger.error("length of code %s is not equal to index." %
self.code)
return False
#set chip distribution
dist_data = self.compute_distribution(df)
if dist_data.empty:
logger.error("%s is empty distribution." % self.code)
return False
if not self.set_chip_distribution(dist_data):
logger.error("store %s distribution failed" % self.code)
return False
df['uprice'] = mac(dist_data, 0)
df['sprice'] = mac(dist_data, 5)
df['mprice'] = mac(dist_data, 13)
df['lprice'] = mac(dist_data, 37)
df = pro_nei_chip(df, dist_data)
if is_df_has_unexpected_data(df):
logger.error("data for %s is not clean." % self.code)
return False
day_table = self.get_day_table()
if not self.mysql_client.delsert(df, day_table):
logger.error("save %s data to mysql failed." % self.code)
return False
self.redis.sadd(day_table, *set(df.date.tolist()))
return True
def set_today_data(self, df, index_df, pre_date, cdate):
day_table = self.get_day_table()
if self.is_date_exists(day_table, cdate):
logger.debug("existed data for code:%s, date:%s" %
(self.code, cdate))
return True
index_df = index_df.loc[index_df.date == cdate]
preday_df = self.get_k_data(date=pre_date)
if preday_df is None:
logger.error("%s get pre date data failed." % self.code)
return False
if preday_df.empty:
logger.error("%s get pre date data empty." % self.code)
return False
df['adj'] = 1.0
df['preclose'] = preday_df['close'][0]
df['totals'] = preday_df['totals'][0]
df['outstanding'] = preday_df['outstanding'][0]
#transfer data to split-adjusted share prices
df = self.transfer2adjusted(df)
df = self.relative_index_strength(df, index_df, cdate)
if df is None: return False
#set chip distribution
dist_df = df.append(preday_df, sort=False)
dist_df = dist_df.sort_values(by='date', ascending=True)
dist_data = self.compute_distribution(dist_df, cdate)
if dist_data.empty:
logger.error("%s chip distribution compute failed." % self.code)
return False
if self.set_chip_distribution(dist_data, zdate=cdate):
df['uprice'] = mac(dist_data, 0)
df['sprice'] = mac(dist_data, 5)
df['mprice'] = mac(dist_data, 13)
df['lprice'] = mac(dist_data, 37)
df = pro_nei_chip(df, dist_data, preday_df, cdate)
if is_df_has_unexpected_data(df):
logger.error("data for %s is not clean." % self.code)
return False
if self.mysql_client.set(df, self.get_day_table()):
return self.redis.sadd(day_table, cdate)
return False