def notify_realtime_earnings(self):
# 实时持仓盈亏检测通知
while True:
df_position = DataFrame()
if os.path.exists(self.__file_path_position):
try:
df_position = Utils.read_data(self.__file_path_position)
except:
# 可能在修改文件，等一分钟
sleep(60)
continue
else:
ERROR('file {0} not exists.'.format(self.__file_path_position))
return
cur_time = Utils.cur_time()
hour = int(cur_time.split(':')[0])
minute = int(cur_time.split(':')[1])
if hour < 9 or (hour == 9 and minute < 30):
LOG( 'notify_realtime_earnings: morning\n{0} hours {1} minutes later market open'\
.format( int( Utils.now2market_morning_time() / 3600 ), int( Utils.now2market_morning_time() % 3600 / 60 ) ) )
sleep(Utils.now2market_morning_time())
elif (hour == 11 and minute >= 30) or hour == 12:
LOG('notify_realtime_earnings: nooning\n{0} hours {1} minutes later market open'
.format(int(Utils.now2market_nooning_time() / 3600),
int(Utils.now2market_nooning_time() % 3600 / 60)))
sleep(Utils.now2market_nooning_time())
elif hour >= 15:
LOG('notify_realtime_earnings: market close')
break
content_notify = ''
content_notify += '{0}\n'.format(cur_time)
total_earn = 0
for index in df_position.index:
code = '%06d' % df_position.loc[index]['code']
name = df_position.loc[index]['name']
try:
df_realtime_quotes = Data().get_realtime_quotes(code)
buy_price = float(df_position.loc[index]['buy_price'])
cur_price = float(df_realtime_quotes['price'])
position = df_position.loc[index]['position']
earn = (cur_price - buy_price) * position
total_earn += earn
content_notify += '-{0} {1} cur:{2:.2f} cost:{3:.2f} sell:{4:.2f} position:{5} earn:{6:.2f}\n'\
.format( code, name, cur_price, buy_price, float( df_position.loc[ index ][ 'sell_price' ] ), position, earn)
except:
pass
content_notify += 'total_earn:{0:.2f}'.format(total_earn)
if SEND_EMAIL:
Utils.send_email(content_notify, 'position notification')
sleep(60 * 10)
else:
LOG(content_notify)
sleep(60 * 10)
except:
pass
if SEND_EMAIL:
# 如果发送邮件，10分钟发一次
Utils.send_email(content_notify, 'opportunity notification')
sleep(10 * 60)
else:
LOG('*********************************')
LOG(content_notify)
LOG('*********************************')
sleep(60 * 5)
if __name__ == '__main__':
if int(Utils.cur_time().split(':')[0]) < 18:
# 18点之前，采用前一个交易日的分析结果
analyse_class = model.spill_wave.Analyse()
list_process = []
list_process.append(
Process(target=Notify().notify_investment_opportunity))
# list_process.append( Process( target = Notify().notify_realtime_earnings ) )
list_process.append(Process(target=Notify().serve_query_request))
for process in list_process:
process.start()
for process in list_process:
process.join()
else:
# 当日18点之后方可更新数据
def notify_investment_opportunity(self):
df_spill_wave_stock = Utils.read_data(
model.spill_wave.Analyse().spill_wave_stock_file)
df_model_basics = Basics().get_basics().set_index('code')
while True:
cur_time = Utils.cur_time()
hour = int(cur_time.split(':')[0])
minute = int(cur_time.split(':')[1])
if hour < 9 or (hour == 9 and minute < 30):
LOG( 'notify_investment_opportunity: morning\n{0} hours {1} minutes later market open'\
.format( int( Utils.now2market_morning_time() / 3600 ), int( Utils.now2market_morning_time() % 3600 / 60 ) ) )
sleep(Utils.now2market_morning_time())
elif (hour == 11 and minute >= 30) or hour == 12:
LOG('notify_investment_opportunity: nooning\n{0} hours {1} minutes later market open'
.format(int(Utils.now2market_nooning_time() / 3600),
int(Utils.now2market_nooning_time() % 3600 / 60)))
sleep(Utils.now2market_nooning_time())
elif hour >= 15:
LOG('notify_investment_opportunity: market close')
break
content_notify = ''
content_notify += '{0}\n'.format(cur_time)
for index in df_spill_wave_stock.index:
code = '%06d' % df_spill_wave_stock.loc[index]['code']
name = df_spill_wave_stock.loc[index]['name']
try:
df_realtime_quotes = Data().get_realtime_quotes(code)
if float(df_realtime_quotes['price']) >= (float(
df_spill_wave_stock.loc[index]['buy_price']) *
0.99):
content_notify += '-{0} {1} cur price:{2:.2f} buy price:{3:.2f} sell price:{4:.2f} expect earn:{5:.2f}\n'\
.format( code, name, float( df_realtime_quotes[ 'price' ] ), \
float( df_spill_wave_stock.loc[ index ][ 'buy_price' ] ), \
float( df_spill_wave_stock.loc[ index ][ 'sell_price' ] ), \
float( df_spill_wave_stock.loc[ index ][ 'expect_earn_rate' ] ), \
float( df_spill_wave_stock.loc[ index ][ 'min_earn_rate' ] ) )
content_notify += '\tprofit rank:{0}\n \tindustry:{1} pe rank:{2}\n'.format( df_model_basics[ 'rank_profit_grow' ][ int( code ) ],\
df_model_basics[ 'industry' ][ int( code ) ], df_model_basics[ 'rank_pe' ][ int( code ) ] )
id_concept = 1
id_rank = 1
name_concept = '_'.join(['concept',
str(id_concept)])
name_rank = '_'.join(['rank_pe',
str(id_rank)])
while df_model_basics[name_concept][int(
code)] is not np.nan:
content_notify += '\tconcept:{0} pe rank:{1}\n'.format( df_model_basics[ name_concept ][ int( code ) ], \
df_model_basics[ name_rank ][ int( code ) ] )
id_concept += 1
id_rank += 1
if id_concept > 20:
break
name_concept = '_'.join(
['concept', str(id_concept)])
name_rank = '_'.join(['rank_pe',
str(id_rank)])
content_notify += '\n'
except:
pass
if SEND_EMAIL:
# 如果发送邮件，10分钟发一次
Utils.send_email(content_notify, 'opportunity notification')
sleep(10 * 60)
else:
LOG('*********************************')
LOG(content_notify)
LOG('*********************************')
sleep(60 * 5)
def do_realtime_trade( self ):
pd.options.mode.chained_assignment = None # 不显示warn信息 default='warn'
df_model_basics = Basics().get_basics().set_index( 'code' )
if os.path.exists( self.__file_path_trade ):
self.df_trade = Utils.read_data( self.__file_path_trade )
if self.df_trade.index.size >= 1:
self.remain_money = self.df_trade.loc[ self.df_trade.index.size - 1 ][ 'remain' ]
if os.path.exists( self.__file_path_position ):
self.df_position = Utils.read_data( self.__file_path_position )
while True:
cur_time = Utils.cur_time()
hour = int( cur_time.split( ':' )[ 0 ] )
minute = int( cur_time.split( ':' )[ 1 ] )
if hour < 9 or ( hour == 9 and minute < 30 ):
LOG( 'Trade_Simulator: morning\n{0} hours {1} minutes later market open'\
.format( int( Utils.now2market_morning_time() / 3600 ), int( Utils.now2market_morning_time() % 3600 / 60 ) ) )
sleep( Utils.now2market_morning_time() )
elif ( hour == 11 and minute >= 30 ) or hour == 12:
LOG( 'Trade_Simulator: nooning\n{0} hours {1} minutes later market open'
.format( int( Utils.now2market_nooning_time() / 3600 ), int( Utils.now2market_nooning_time() % 3600 / 60 ) ) )
sleep( Utils.now2market_nooning_time() )
elif hour >= 15:
LOG( 'Trade_Simulator: market close' )
break
# sell
for index in self.df_position.index:
code = '%06d' % int( self.df_position.loc[ index ][ 'code' ] )
df_realtime_quotes = Data().get_realtime_quotes( code )
# T + 1 交易
if self.df_position.loc[ index ][ 'buy_date' ] < Utils.cur_date():
name = self.df_position.loc[ index ][ 'name' ]
if float( df_realtime_quotes[ 'price' ] ) >= self.df_position.loc[ index ][ 'sell_price' ]:
self.remain_money += float( df_realtime_quotes[ 'price' ] ) * float( self.df_position.loc[ index ][ 'position' ] )
total_earn = '{0:.2f}'.format( ( float( df_realtime_quotes[ 'price' ] ) - float( self.df_position.loc[ index ][ 'cost_price' ] ) ) \
* float( self.df_position.loc[ index ][ 'position' ] ) + float( self.df_trade.loc[ self.df_trade.index.size - 1 ][ 'total_earn' ] ) )
self.df_trade.loc[ self.df_trade.index.size ] = [ ' '.join( [ Utils.cur_date(), Utils.cur_time() ] ), code, name, 'sell', \
self.df_position.loc[ index ][ 'position' ], total_earn, self.remain_money ]
self.df_position = self.df_position.drop( index )
continue
self.df_position[ 'earn' ][ index ] = '{0:.2f}'.format( ( float( df_realtime_quotes[ 'price' ] ) - float( self.df_position.loc[ index ][ 'cost_price' ] ) ) \
* float( self.df_position.loc[ index ][ 'position' ] ) )
sleep( 1 )
# buy
for index in self.df_model_stock.index:
code = '%06d' % int( self.df_model_stock.loc[ index ][ 'code' ] )
name = self.df_model_stock.loc[ index ][ 'name' ]
# 每只在仓股不再买入
if int( code ) in self.df_position[ 'code' ].to_dict().values() or \
code in self.df_position[ 'code' ].to_dict().values():
continue
try:
df_realtime_quotes = Data().get_realtime_quotes( code )
if float( df_realtime_quotes[ 'price' ] ) >= ( float( self.df_model_stock.loc[ index ][ 'buy_price' ] ) * 0.99 ) and \
float( df_realtime_quotes[ 'price' ] ) <= ( float( self.df_model_stock.loc[ index ][ 'buy_price' ] ) * 1.002 ) and \
float( self.df_model_stock.loc[ index ][ 'expect_earn_rate' ] ) >= 0.2:
try:
if float( df_model_basics[ 'rank_profit_grow' ][ int( code ) ].split( '/' )[ 0 ] ) / \
float( df_model_basics[ 'rank_profit_grow' ][ int( code ) ].split( '/' )[ 1 ] ) >= 0.5:
continue
# LOG( '{0} {1}'.format( code, df_model_basics[ 'rank_profit_grow' ][ int( code ) ].split( '/' ) ) )
except:pass
buy_hand_num = 0
# 至少剩余买一手的资金
if 100 * float( df_realtime_quotes[ 'price' ] ) <= self.remain_money:
buy_hand_num = int( min( self.initial_fund * float( self.df_model_stock.loc[ index ][ 'expect_earn_rate' ] ) * 0.5 / float( df_realtime_quotes[ 'price' ] ) / 100, \
self.max_buy_each_stock / float( df_realtime_quotes[ 'price' ] ) / 100, self.remain_money / float( df_realtime_quotes[ 'price' ] ) / 100 ) )
if self.df_trade.index.size >= 1:
total_earn = self.df_trade.loc[ self.df_trade.index.size - 1 ][ 'total_earn' ]
else:
total_earn = 0
self.remain_money -= buy_hand_num * 100 * float( df_realtime_quotes[ 'price' ] )
self.df_trade.loc[ self.df_trade.index.size ] = [ ' '.join( [ Utils.cur_date(), Utils.cur_time() ] ), code, name, 'buy', \
buy_hand_num * 100, total_earn, self.remain_money ]
self.df_position.loc[ self.df_position.index.size ] = [ code, name, Utils.cur_date(), float( df_realtime_quotes[ 'price' ] ), \
float( df_realtime_quotes[ 'price' ] ) * ( 0.2 * float( self.df_model_stock.loc[ index ][ 'expect_earn_rate' ] ) + 1.0 ), \
buy_hand_num * 100, 0 ]
sleep( 1 )
except:
pass
self.save_data( self.df_trade, self.__file_path_trade )
self.save_data( self.df_position, self.__file_path_position )
