def is_supported(self, code, date):
last_year = date.year - 1
cashflows = self.bonusDataManager.get_data(
code, constant.talbe_name_cashflow, cj.CashflowCrawler())
rtn = get_value_year(cashflows, last_year, 'pub_date',
['total_liability', 'total_current_assets'])
if not base.is_df_validate(rtn):
return False
# 流动资产
total_current_assets = float(
rtn.get('total_current_assets') if rtn.get('total_current_assets'
) is not None else 0.0)
balances = self.bonusDataManager.get_data(code,
constant.table_name_balance,
cj.BalanceCrawler())
rtn = get_value_year(balances, last_year, 'pub_date',
['total_current_liability'])
if rtn is None:
logging.info(
' filter_safecurrentratio drop， no last year capitals code {} '
.format(code))
return False
# 流动负债合计
total_current_liability = float(rtn.get('total_current_liability'))
rtn = (total_current_assets / total_current_liability) > 2
if not rtn:
logging.info(
' filter_safecurrentratio drop，code: {}, total_current_assets: {}, total_current_liability: {}'
.format(code, total_current_assets, total_current_liability))
return rtn
def is_supported(self, code, date):
last_year = date.year - 1
incomes = self.bonusDataManager.get_data(code,
constant.talbe_name_incomes,
cj.IncomesCrawler())
last_year_total_profit = get_value_year(incomes, last_year,
'report_date',
['total_profit'])
last_five_year_total_profit = get_value_year(incomes, last_year,
'report_date',
['total_profit'])
if last_year_total_profit is None or last_five_year_total_profit is None:
return False
last_year_total_profit = last_year_total_profit.get('total_profit')
last_five_year_total_profit = last_five_year_total_profit.get(
'total_profit')
if last_year_total_profit is None or last_five_year_total_profit is None:
return False
return ( float(last_year_total_profit) - float(last_five_year_total_profit))\
/ float(last_five_year_total_profit) > (7/100)
def is_supported(self, code, date):
last_year = date.year - 1
# 获取上一个报告日的有形资产
totle_tangibles = self._get_totle_tangibles(code, last_year)
if None is totle_tangibles:
return False
cashflows = self.bonusDataManager.get_data(
code, constant.talbe_name_cashflow, cj.CashflowCrawler())
rtn = get_value_year(cashflows, last_year, 'pub_date',
['total_liability', 'total_current_assets'])
if base.is_df_validate(rtn):
# 总负债
total_liability = float(rtn.get('total_liability'))
# 流动资产
total_current_assets = float(
rtn.get('total_current_assets') if rtn.
get('total_current_assets') is not None else 0.0)
if not total_liability < totle_tangibles:
logging.info(
'filter SafeTotalLiability drop code {} :, total_liability: {} , totle_tangibles: {} '
.format(code, total_liability, totle_tangibles))
return False
if not total_current_assets < totle_tangibles:
logging.info(
'filter SafeTotalLiability drop code {} :, total_current_assets: {} , totle_tangibles: {} '
.format(code, total_current_assets, totle_tangibles))
return True
else:
return False
def is_supported(self, code, date):
last_year = date.year
# 获取上一个报告日的有形资产
totle_tangibles = self._get_totle_tangibles(code, last_year)
if None is totle_tangibles:
return False
capitals = self.bonusDataManager.get_data(code,
constant.talbe_name_capital,
cj.CapitalCrawler())
rtn = get_value_year(capitals, last_year, 'pub_date', ['share_total'])
if rtn is None:
logging.info(
' filter_cashflow drop， no last year capitals code {} '.format(
code))
return False
share_total = float(rtn.get('share_total')) * 10000
close = self._get_close(code)
if None is close:
return False
tmp = (totle_tangibles / share_total) * 2 / 3
rtn = close < tmp
if not rtn:
logging.info(
' filter_balance drop code {} : , close : {} , result {}'.
format(code, close, tmp))
return rtn
def _get_eps(self, code, year):
incomes = self.bonusDataManager.get_data(code,
constant.talbe_name_incomes,
cj.IncomesCrawler())
rtn = get_value_year(incomes, year, 'report_date', ['basic_eps'])
if rtn is not None:
return rtn.get('basic_eps')
def is_supported(self, code, date):
last_year = date.year - 1
incomes = self.bonusDataManager.get_data(code,
constant.talbe_name_incomes,
cj.IncomesCrawler())
for i in range(5):
if not self._is_year_support(last_year - 1, incomes):
return False
return True
def _get_bonus_ratio(self, code, year):
dividens = self.bonusDataManager.get_data(
code=code,
table_name=constant.table_name_dividend,
crawler=cj.DividendsCrawler())
if base.is_df_validate(dividens):
dividens = dividens.loc[(dividens['bonus_type'] == '年度分红')]
if base.is_df_validate(dividens):
dividens = dividens.sort_values(by=['report_date'],
ascending=False).head(1)
return dividens['bonus_ratio_rmb'].iloc[0]
def is_supported(self, code, date):
last_year = date.year
cashflows = self.bonusDataManager.get_data(
code, constant.talbe_name_cashflow, cj.CashflowCrawler())
rtn = get_value_year(cashflows, last_year, 'pub_date',
['total_liability', 'total_current_assets'])
if base.is_df_validate(rtn):
# 总负债
total_liability = float(rtn.get('total_liability'))
# 流动资产
total_current_assets = float(
rtn.get('total_current_assets') if rtn.
get('total_current_assets') is not None else 0.0)
capitals = self.bonusDataManager.get_data(
code, constant.talbe_name_capital, cj.CapitalCrawler())
rtn = get_value_year(capitals, last_year, 'pub_date',
['share_total'])
share_total = float(rtn.get('share_total')) * 10000
# print("cashflow : close {} current {}".format(close, (total_current_assets - total_liability)/ share_total* 2 / 3))
tmp = (total_current_assets - total_liability) / share_total
if not tmp > 0:
return False
close = self._get_close(code)
if None is close:
return False
rtn = close < tmp * 2 / 3
if not rtn:
logging.info('filter_cashflow drop code {} : {} '.format(
code, tmp))
return not rtn
return False
def _get_totle_tangibles(self, code, year):
df_balance = self.bonusDataManager.get_data(
code, constant.table_name_balance, cj.BalanceCrawler())
if base.is_df_validate(df_balance):
df_balance = df_balance.sort_values(by=['report_date'],
ascending=False).head(1)
intangible_assets = df_balance['intangible_assets'].iloc[0].astype(
float)
if intangible_assets > 0:
totle_tangibles = df_balance['total_assets'].iloc[0].astype(
float) - intangible_assets
else:
totle_tangibles = df_balance['total_assets'].iloc[0].astype(
float)
return totle_tangibles
def __init__(self):
self.historyManager = HistoryDataManager.HistoryDataManager()
self.jqDataCrawler = cj.JQDataCrawler()
self.bonusDataManager = BonusDataManager()
def __init__(self):
self.jqDataCrawler = cij.JQDataCrawler()