def report_vol_up_250():
while True:
error_count = 0
email_action = EmailInformer()
try:
# 抓取k线数据
StockTradeDay.record_data(provider='joinquant')
Stock1dKdata.record_data(provider='joinquant')
latest_day: StockTradeDay = StockTradeDay.query_data(
order=StockTradeDay.timestamp.desc(),
limit=1,
return_type='domain')
if latest_day:
target_date = latest_day[0].timestamp
else:
target_date = now_pd_timestamp()
# 计算均线
my_selector = TargetSelector(start_timestamp='2018-01-01',
end_timestamp=target_date)
# add the factors
factor1 = VolumeUpMa250Factor(start_timestamp='2018-01-01',
end_timestamp=target_date)
my_selector.add_filter_factor(factor1)
my_selector.run()
long_targets = my_selector.get_open_long_targets(
timestamp=target_date)
if long_targets:
stocks = get_entities(provider='joinquant',
entity_schema=Stock,
entity_ids=long_targets,
return_type='domain')
info = [f'{stock.name}({stock.code})' for stock in stocks]
msg = ' '.join(info)
else:
msg = 'no targets'
logger.info(msg)
email_action.send_message("*****@*****.**",
f'{target_date} 放量突破年线选股结果', msg)
break
except Exception as e:
logger.exception('report_vol_up_250 error:{}'.format(e))
time.sleep(60 * 3)
error_count = error_count + 1
if error_count == 10:
email_action.send_message(
"*****@*****.**", f'report_vol_up_250 error',
'report_vol_up_250 error:{}'.format(e))
def report_core_company():
while True:
error_count = 0
email_action = EmailInformer()
try:
StockTradeDay.record_data(provider='joinquant')
Stock.record_data(provider='joinquant')
FinanceFactor.record_data(provider='eastmoney')
BalanceSheet.record_data(provider='eastmoney')
latest_day: StockTradeDay = StockTradeDay.query_data(
order=StockTradeDay.timestamp.desc(),
limit=1,
return_type='domain')
if latest_day:
target_date = latest_day[0].timestamp
else:
target_date = now_pd_timestamp()
my_selector: TargetSelector = FundamentalSelector(
start_timestamp='2015-01-01', end_timestamp=target_date)
my_selector.run()
long_targets = my_selector.get_open_long_targets(
timestamp=target_date)
if long_targets:
stocks = get_entities(provider='joinquant',
entity_schema=Stock,
entity_ids=long_targets,
return_type='domain')
info = [f'{stock.name}({stock.code})' for stock in stocks]
msg = ' '.join(info)
else:
msg = 'no targets'
logger.info(msg)
email_action.send_message([
'*****@*****.**', '*****@*****.**',
'*****@*****.**', '*****@*****.**',
'*****@*****.**'
], f'{to_time_str(target_date)} 核心资产选股结果', msg)
break
except Exception as e:
logger.exception('report_core_company error:{}'.format(e))
time.sleep(60 * 3)
error_count = error_count + 1
if error_count == 10:
email_action.send_message(
"*****@*****.**", f'report_core_company error',
'report_core_company error:{}'.format(e))
def record(self, entity, start, end, size, timestamps, http_session):
try:
trade_day = StockTradeDay.query_data(
region=self.region,
limit=1,
order=StockTradeDay.timestamp.desc(),
return_type='domain')
if len(trade_day) > 0:
start = trade_day[0].timestamp
except Exception as _:
pass
df = pd.DataFrame()
dates = self.nyse.schedule(start_date=to_time_str(start),
end_date=to_time_str(
now_pd_timestamp(Region.US)))
dates = dates.index.to_list()
self.logger.info(f'add dates:{dates}')
df['timestamp'] = pd.to_datetime(dates)
df['id'] = [to_time_str(date) for date in dates]
df['entity_id'] = 'nyse'
df_to_db(df=df,
region=self.region,
data_schema=self.data_schema,
provider=self.provider,
force_update=self.force_update)
def record(self, entity, start, end, size, timestamps, http_session):
try:
trade_day = StockTradeDay.query_data(
region=self.region,
limit=1,
order=StockTradeDay.timestamp.desc(),
return_type='domain')
if len(trade_day) > 0:
start = trade_day[0].timestamp
else:
start = "1990-12-19"
except Exception as _:
pass
df = pd.DataFrame()
dates_df = bao_get_trade_days(start_date=start)
dates = dates_df[dates_df['is_trading_day'] ==
'1']['calendar_date'].to_list()
self.logger.info(f'add dates:{dates}')
df['timestamp'] = pd.to_datetime(dates)
df['id'] = [to_time_str(date) for date in dates]
df['entity_id'] = 'chn'
df_to_db(df=df,
region=self.region,
data_schema=self.data_schema,
provider=self.provider,
force_update=self.force_update)
def run(self):
trade_days = StockTradeDay.query_data(region=self.region,
order=StockTradeDay.timestamp.desc(),
return_type='domain')
self.trade_day = [day.timestamp for day in trade_days]
super().run()
def evaluate_start_end_size_timestamps(self, entity):
start, end, size, timestamps = super().evaluate_start_end_size_timestamps(entity)
if start:
trade_day = StockTradeDay.query_data(limit=1, order=StockTradeDay.timestamp.desc(), return_type='domain')
if trade_day:
if is_same_date(trade_day[0].timestamp, start):
size = 0
return start, end, size, timestamps
def record_stock():
while True:
email_action = EmailInformer()
try:
Stock.record_data(provider='joinquant', sleeping_time=1)
StockTradeDay.record_data(provider='joinquant', sleeping_time=1)
email_action.send_message("*****@*****.**",
'joinquant record stock finished', '')
break
except Exception as e:
msg = f'joinquant record stock:{e}'
logger.exception(msg)
email_action.send_message("*****@*****.**",
'joinquant record stock error', msg)
time.sleep(60 * 5)
def process_loop(self, entity, http_session):
trade_days = StockTradeDay.query_data(region=self.region,
return_type='df')
if len(trade_days) > 0:
start = to_time_str(trade_days['timestamp'].max(axis=0))
else:
start = "1990-12-19"
df = bao_get_trade_days(start_date=start)
if pd_is_not_null(df):
df = self.format(entity, df)
self.persist(df)
return None
def process_loop(self, entity, http_session):
trade_days = StockTradeDay.query_data(region=self.region,
return_type='df')
if len(trade_days) > 0:
start = to_time_str(trade_days['timestamp'].max(axis=0))
else:
start = "1980-01-01"
dates = jq_get_trade_days(date=start)
dates = dates.iloc[:, 0]
self.logger.info(f'add dates:{dates}')
if len(dates) > 0:
df = pd.DataFrame(dates, columns=['timestamp'])
df = self.format(df)
self.persist(df)
return None
def process_loop(self, entity, http_session):
calendar = mcal.get_calendar(entity)
trade_days = StockTradeDay.query_data(region=self.region,
return_type='df')
if len(trade_days) > 0:
start = to_time_str(trade_days['timestamp'].max(axis=0))
else:
start = "1980-01-01"
dates = calendar.schedule(start_date=start,
end_date=to_time_str(
now_pd_timestamp(Region.US)))
dates = dates.index.to_list()
self.logger.info(f'add dates:{dates}')
if len(dates) > 0:
df = pd.DataFrame(dates, columns=['timestamp'])
df = self.format(entity, df)
self.persist(df)
return None
def run(self):
http_session = get_http_session()
trade_days= StockTradeDay.query_data(region=self.region, order=StockTradeDay.timestamp.desc(), return_type='domain')
trade_day = [day.timestamp for day in trade_days]
stock_detail = StockDetail.query_data(region=self.region, columns=['entity_id', 'end_date'], index=['entity_id'], return_type='df')
time.sleep(random.randint(0, self.share_para[1]))
process_identity = multiprocessing.current_process()._identity
if len(process_identity) > 0:
# The worker process tqdm bar shall start at Position 1
worker_id = (process_identity[0]-1)%self.share_para[1] + 1
else:
worker_id = 0
desc = "{:02d}: {}".format(worker_id, self.share_para[0])
with tqdm(total=len(self.entities), ncols=80, position=worker_id, desc=desc, leave=self.share_para[3]) as pbar:
for entity_item in self.entities:
self.process_loop(entity_item, trade_day, stock_detail, http_session)
self.share_para[2].acquire()
pbar.update()
self.share_para[2].release()
self.on_finish()
def report_tm():
while True:
error_count = 0
discord_informer = DiscordInformer()
try:
# 抓取k线数据
# StockTradeDay.record_data(provider='baostock', sleeping_time=2)
# Stock1dKdata.record_data(provider='baostock', sleeping_time=1.5)
latest_day: StockTradeDay = StockTradeDay.query_data(order=StockTradeDay.timestamp.desc(), limit=1,provider='joinquant',
return_type='domain')
if latest_day:
target_date = latest_day[0].timestamp
else:
target_date = now_pd_timestamp()
start_date = target_date - timedelta(60)
# 计算
my_selector = TargetSelector(entity_schema=Stock, provider='joinquant',
start_timestamp=start_date, end_timestamp=target_date)
# add the factors
tm_factor = TMFactor(entity_schema=Stock, provider='joinquant',
start_timestamp=start_date,
end_timestamp=target_date)
my_selector.add_filter_factor(tm_factor)
my_selector.run()
long_targets = my_selector.get_open_long_targets(timestamp=target_date)
logger.info(long_targets)
msg = 'no targets'
# 过滤亏损股
# check StockValuation data
pe_date = target_date - timedelta(10)
if StockValuation.query_data(start_timestamp=pe_date, limit=1, return_type='domain'):
positive_df = StockValuation.query_data(provider='joinquant', entity_ids=long_targets,
start_timestamp=pe_date,
filters=[StockValuation.pe > 0],
columns=['entity_id'])
bad_stocks = set(long_targets) - set(positive_df['entity_id'].tolist())
if bad_stocks:
stocks = get_entities(provider='joinquant', entity_schema=Stock, entity_ids=bad_stocks,
return_type='domain')
info = [f'{stock.name}({stock.code})' for stock in stocks]
msg = '亏损股:' + ' '.join(info) + '\n'
long_stocks = set(positive_df['entity_id'].tolist())
if long_stocks:
# use block to filter
block_selector = BlockSelector(start_timestamp='2020-01-01', long_threshold=0.8)
block_selector.run()
long_blocks = block_selector.get_open_long_targets(timestamp=target_date)
if long_blocks:
blocks = Block.query_data(provider='sina', entity_ids=long_blocks,
return_type='domain')
info = [f'{block.name}({block.code})' for block in blocks]
msg = ' '.join(info) + '\n'
block_stocks = BlockStock.query_data(provider='sina', filters=[
BlockStock.stock_id.in_(long_stocks)],
entity_ids=long_blocks, return_type='domain')
block_map_stocks = {}
for block_stock in block_stocks:
stocks = block_map_stocks.get(block_stock.name)
if not stocks:
stocks = []
block_map_stocks[block_stock.name] = stocks
stocks.append(f'{block_stock.stock_name}({block_stock.stock_code})')
for block in block_map_stocks:
stocks = block_map_stocks[block]
stock_msg = ' '.join(stocks)
msg = msg + f'{block}:\n' + stock_msg + '\n'
discord_informer.send_message(f'{target_date} TM选股结果 {msg}')
break
except Exception as e:
logger.exception('report_tm error:{}'.format(e))
time.sleep(60 * 3)
error_count = error_count + 1
if error_count == 10:
discord_informer.send_message(f'report_tm error',
'report_tm error:{}'.format(e))
def record2(self, entity, start, end, size, timestamps):
if not end:
end = to_time_str(now_pd_timestamp())
if (pd.to_datetime(end) - start).days >= 30:
from datetime import timedelta
end = to_time_str(start + timedelta(days=30))
start = to_time_str(start)
if start == end:
return None
# 暂不处理港股
if 'hk' in entity.id:
return None
exchange = 'SH' if 'sh' in entity.id else 'SZ'
em_code = entity.code + '.' + exchange
columns_list = {
'TOTALSHARE': 'capitalization', # 总股本
'LIQSHARE': 'circulating_cap', # 流通股本
'MV': 'market_cap', # 总市值
'LIQMV': 'circulating_market_cap', # 流通市值
'TURN': 'turnover_ratio', # 换手率
'PELYR': 'pe', # 静态pe
'PETTM': 'pe_ttm', # 动态pe
'PBLYR': 'pb', # 市净率PB(最新年报)
'PBMRQ': 'pb_mrq', # 市净率PB(MRQ)
'PSTTM': 'ps_ttm', # 市销率PS(TTM)
'PCFTTM': 'pcf_ttm', # 市现率PCF(最新年报，经营性现金流)
}
# df = c.csd(em_code, [i for i in columns_list.keys()], start,end,"ispandas=1,DelType=2")
df = get_data(data_schema=StockValuation, entity_id=entity.id, provider='joinquant', start_timestamp=start,
end_timestamp=end)
if df.empty:
df = get_data(data_schema=StockValuation, entity_id=entity.id, provider='joinquant', limit=1)
start = df.timestamp[0]
end = to_time_str(start + timedelta(days=30))
df = get_data(data_schema=StockValuation, entity_id=entity.id, provider='joinquant', start_timestamp=start,
end_timestamp=end)
if df.empty:
return None
df.rename(columns={
"ps": "ps_ttm",
"pcf": "pcf_ttm",
}, inplace=True)
trade_day = StockTradeDay.query_data(order=StockTradeDay.timestamp.desc(), start_timestamp=start,
end_timestamp=end)
df_capital_all = pd.DataFrame()
for tradeday in trade_day.timestamp:
df_capital = c.css(em_code, "WACC,DIVIDENDYIELDNEW",
f"TradeDate={to_time_str(tradeday)},FrIndex=1,MrIndex=1,ispandas=1")
try:
df_capital['DATES'] = tradeday
except:
continue
df_capital_all = df_capital_all.append(df_capital)
# 'DIVIDENDYIELDNEW': 'div_yield', #股息率
try:
if df.empty:
return None
except:
self.logger.info(f'choice数据源的个股估值尚未准备完成，获取失败。'
f'股票代码：{em_code}-开始时间：{start}-结束时间：{end}')
return None
df['CODES'] = df_capital_all.index[0]
df['DATES'] = df['timestamp']
df_capital_all['DATES'] = pd.to_datetime(df_capital_all['DATES'])
df_capital_all.rename(columns={"DIVIDENDYIELDNEW": "div_yield", "WACC": "wacc"}, inplace=True)
df = pd.merge(df, df_capital_all, on=['CODES', 'DATES'], how='outer')
df.dropna(subset=['id'],inplace=True)
df_to_db(df=df, data_schema=self.data_schema, provider=self.provider, force_update=self.force_update)
return None
account_stock_position_response = s.get(
f"{beehive3_api}/api/portfolio/position/{portfolio_id}")
account_position = account_stock_position_response.json()
# 现有持仓
stock_df = pd.DataFrame()
for sotck_pos in account_position['industry_info']:
for i in sotck_pos['stocks']:
stock_df = stock_df.append(pd.DataFrame(i, index=[0]))
nowend = '20210909'
back_date = [nowend]
for ye in back_date:
start = f'{ye}'
end = nowend
trade_data = StockTradeDay.query_data(
start_timestamp=pd.to_datetime(start) - np.timedelta64(1, 'Y'),
end_timestamp=pd.to_datetime(end)).timestamp
trade_data = list(set(str(i.year) for i in trade_data))
# 设置调仓日
relocation_date = '0501'
buy_signal = pd.DataFrame()
no_symbol = []
for sheet_name in trade_data:
print(sheet_name)
# data = pd.read_excel("C:/Users/32771/Desktop/选股情况记录/20210801/WACC54结果.xlsx", sheet_name=sheet_name)
data = pd.read_excel("C:\\Users\\32771\\Downloads\\好公司2021V2.xlsx",
sheet_name=sheet_name)
try:
# data = data[data.市场 == 'A股']
data.dropna(subset=['智道分类'], inplace=True)
def get_stock_trade_day(provider: Provider, lock, region):
# 交易日
StockTradeDay.record_data(provider=provider,
share_para=('Trade Day', 0, lock, True,
region),
sleeping_time=0)
def report_core_company():
while True:
error_count = 0
email_action = EmailInformer()
try:
StockTradeDay.record_data(provider='joinquant')
# Stock.record_data(provider='joinquant')
# FinanceFactor.record_data(provider='eastmoney')
# BalanceSheet.record_data(provider='eastmoney')
latest_day: StockTradeDay = StockTradeDay.query_data(
order=StockTradeDay.timestamp.desc(),
limit=1,
return_type='domain')
if latest_day:
target_date = latest_day[0].timestamp
else:
target_date = now_pd_timestamp()
my_selector: TargetSelector = FundamentalSelector(
start_timestamp='2015-01-01', end_timestamp=target_date)
my_selector.run()
long_targets = my_selector.get_open_long_targets(
timestamp=target_date)
if long_targets:
stocks = get_entities(provider='joinquant',
entity_schema=Stock,
entity_ids=long_targets,
return_type='domain')
# add them to eastmoney
try:
try:
eastmoneypy.del_group('core')
except:
pass
eastmoneypy.create_group('core')
for stock in stocks:
eastmoneypy.add_to_group(stock.code, group_name='core')
except Exception as e:
email_action.send_message(
"*****@*****.**", f'report_core_company error',
'report_core_company error:{}'.format(e))
info = [f'{stock.name}({stock.code})' for stock in stocks]
msg = ' '.join(info)
else:
msg = 'no targets'
logger.info(msg)
email_action.send_message(subscriber_emails,
f'{to_time_str(target_date)} 核心资产选股结果',
msg)
break
except Exception as e:
logger.exception('report_core_company error:{}'.format(e))
time.sleep(60 * 3)
error_count = error_count + 1
if error_count == 10:
email_action.send_message(
"*****@*****.**", f'report_core_company error',
'report_core_company error:{}'.format(e))
