def test_cross_ma_selector():
entity_ids = ["stock_sz_000338"]
entity_type = "stock"
start_timestamp = "2018-01-01"
end_timestamp = "2019-06-30"
my_selector = TargetSelector(entity_ids=entity_ids,
entity_schema=entity_type,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp)
# add the factors
my_selector.add_factor(
CrossMaFactor(
entity_ids=entity_ids,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
computing_window=10,
windows=[5, 10],
need_persist=False,
level=IntervalLevel.LEVEL_1DAY,
adjust_type="hfq",
))
my_selector.run()
print(my_selector.open_long_df)
print(my_selector.open_short_df)
assert "stock_sz_000338" in my_selector.get_open_short_targets(
"2018-01-29")
def test_cross_ma_selector():
region = Region.CHN
entity_ids = ['stock_sz_000338']
entity_type = EntityType.Stock
start_timestamp = '2018-01-01'
end_timestamp = '2019-06-30'
my_selector = TargetSelector(region=region,
entity_ids=entity_ids,
entity_schema=entity_type,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp)
# add the factors
my_selector \
.add_filter_factor(CrossMaFactor(region=region,
entity_ids=entity_ids,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
computing_window=10,
windows=[5, 10],
need_persist=False,
level=IntervalLevel.LEVEL_1DAY,
adjust_type='qfq'))
my_selector.run()
print(my_selector.open_long_df)
print(my_selector.open_short_df)
assert 'stock_sz_000338' in my_selector.get_open_short_targets(
'2018-01-29')
def report_bull():
while True:
error_count = 0
email_action = EmailInformer()
try:
latest_day: Stock1dHfqKdata = Stock1dHfqKdata.query_data(order=Stock1dHfqKdata.timestamp.desc(), limit=1,
return_type='domain')
target_date = latest_day[0].timestamp
# 计算均线
start = '2019-01-01'
my_selector = TargetSelector(start_timestamp=start, end_timestamp=target_date)
# add the factors
factor1 = BullFactor(start_timestamp=start, end_timestamp=target_date)
factor2 = CrossMaVolumeFactor(start_timestamp=start, end_timestamp=target_date,
windows=[5, 120, 250])
my_selector.add_factor(factor1)
my_selector.add_factor(factor2)
my_selector.run()
long_stocks = my_selector.get_open_long_targets(timestamp=target_date)
msg = 'no targets'
if long_stocks:
stocks = get_entities(provider='joinquant', entity_schema=Stock, entity_ids=long_stocks,
return_type='domain')
# add them to eastmoney
try:
try:
eastmoneypy.del_group('bull')
except:
pass
eastmoneypy.create_group('bull')
for stock in stocks:
eastmoneypy.add_to_group(stock.code, group_name='bull')
except Exception as e:
email_action.send_message(zvt_config['email_username'], f'report_bull error',
'report_bull error:{}'.format(e))
infos = stocks_with_info(stocks)
msg = '\n'.join(infos) + '\n'
logger.info(msg)
email_action.send_message(zvt_config['email_username'], f'{target_date} bull选股结果', msg)
break
except Exception as e:
logger.exception('report_bull error:{}'.format(e))
time.sleep(60 * 3)
error_count = error_count + 1
if error_count == 10:
email_action.send_message(zvt_config['email_username'], f'report_bull error',
'report_bull error:{}'.format(e))
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: Stock1dKdata = Stock1dKdata.query_data(order=Stock1dKdata.timestamp.desc(), limit=1,
return_type='domain')
target_date = latest_day[0].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')
# add them to eastmoney
try:
try:
eastmoneypy.del_group('tech')
except:
pass
eastmoneypy.create_group('tech')
for stock in stocks:
eastmoneypy.add_to_group(stock.code, group_name='tech')
except Exception as e:
email_action.send_message("*****@*****.**", f'report_vol_up_250 error',
'report_vol_up_250 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(get_subscriber_emails(), 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_cross_ma():
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
ma_factor = CrossMaFactor(start_timestamp='2018-01-01',
end_timestamp=target_date)
my_selector.add_filter_factor(ma_factor)
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} 均线选股结果', msg)
break
except Exception as e:
logger.exception('report_cross_ma error:{}'.format(e))
time.sleep(60 * 3)
error_count = error_count + 1
if error_count == 10:
email_action.send_message("*****@*****.**",
f'report_cross_ma error',
'report_cross_ma error:{}'.format(e))
def every_day_report():
while True:
try:
t = now_pd_timestamp()
if t.dayofweek in (5, 6):
logger.info(f'today:{t} is {t.day_name()},just ignore')
today = to_time_str(t)
# 抓取k线数据
JqChinaStockKdataRecorder(level=IntervalLevel.LEVEL_1DAY).run()
JqChinaStockKdataRecorder(level=IntervalLevel.LEVEL_1WEEK).run()
JqChinaStockKdataRecorder(level=IntervalLevel.LEVEL_1MON).run()
# 计算均线
my_selector = TargetSelector(start_timestamp='2016-01-01',
end_timestamp=today)
# add the factors
# 设置dry_run为True，因为我们只需要最近的数据，不需要加载全量数据进行回测
ma_factor = CrossMaFactor(start_timestamp='2016-01-01',
end_timestamp=today,
dry_run=True)
my_selector.add_filter_factor(ma_factor)
my_selector.run()
long_targets = my_selector.get_open_long_targets(timestamp=today)
if long_targets:
df = get_entities(provider='eastmoney',
entity_schema=Stock,
entity_ids=long_targets,
columns=['code', 'name'])
info = [
df.loc[i, 'code'] + ' ' + df.loc[i, 'name']
for i in df.index
]
msg = ' '.join(info)
else:
msg = 'no targets'
logger.info(msg)
email_action = EmailInformer()
email_action.send_message("*****@*****.**", f'{today} 均线选股结果', msg)
break
except Exception as e:
logger.exception('report1 sched error:{}'.format(e))
time.sleep(60 * 3)
def report_tm():
while True:
error_count = 0
discord_informer = DiscordInformer()
try:
# 抓取k线数据
# Coin1dKdata.record_data()
target_date = date.today() - timedelta(days=1)
start_date = target_date - timedelta(60)
# 计算
my_selector = TargetSelector(entity_schema=Coin,
provider='ccxt',
start_timestamp=start_date,
end_timestamp=target_date)
# add the factors
tm_factor = TMFactor(entity_schema=Coin,
provider='ccxt',
start_timestamp=start_date,
end_timestamp=target_date)
my_selector.add_filter_factor(tm_factor)
my_selector.run()
long_targets = list(
map(
lambda x: x.replace('_', '.'),
filter(
lambda k: ('USDT' in k) or ('PERP' in k),
my_selector.get_open_long_targets(
timestamp=target_date))))
logger.info(long_targets)
discord_informer.send_message(
f'{target_date} TM选股结果 {long_targets}')
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 test_cross_ma_selector():
entity_ids = ['stock_sz_000338']
entity_type = 'stock'
start_timestamp = '2018-01-01'
end_timestamp = '2019-06-30'
my_selector = TargetSelector(entity_ids=entity_ids,
entity_type=entity_type,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp)
# add the factors
my_selector \
.add_filter_factor(CrossMaFactor(entity_ids=entity_ids,
entity_type=entity_type,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
level=IntervalLevel.LEVEL_1DAY))
my_selector.run()
print(my_selector.open_long_df)
print(my_selector.open_short_df)
assert 'stock_sz_000338' in my_selector.get_open_short_targets(
'2018-01-29')
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 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: Stock1dHfqKdata = Stock1dHfqKdata.query_data(
order=Stock1dHfqKdata.timestamp.desc(),
limit=1,
return_type='domain')
target_date = latest_day[0].timestamp
# 计算均线
my_selector = TargetSelector(start_timestamp='2018-10-01',
end_timestamp=target_date)
# add the factors
factor1 = VolumeUpMaFactor(start_timestamp='2018-10-01',
end_timestamp=target_date)
my_selector.add_filter_factor(factor1)
my_selector.run()
long_stocks = my_selector.get_open_long_targets(
timestamp=target_date)
msg = 'no targets'
# 过滤亏损股
# check StockValuation data
pe_date = target_date - datetime.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_stocks,
start_timestamp=pe_date,
filters=[StockValuation.pe > 0],
columns=['entity_id'])
bad_stocks = set(long_stocks) - 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:
stocks = get_entities(provider='joinquant',
entity_schema=Stock,
entity_ids=long_stocks,
return_type='domain')
# add them to eastmoney
try:
try:
eastmoneypy.del_group('tech')
except:
pass
eastmoneypy.create_group('tech')
for stock in stocks:
eastmoneypy.add_to_group(stock.code, group_name='tech')
except Exception as e:
email_action.send_message(
"*****@*****.**", f'report_vol_up_250 error',
'report_vol_up_250 error:{}'.format(e))
info = [f'{stock.name}({stock.code})' for stock in stocks]
msg = msg + '盈利股:' + ' '.join(info) + '\n'
logger.info(msg)
email_action.send_message(get_subscriber_emails(),
f'{target_date} 改进版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_vol_up():
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: Stock1dHfqKdata = Stock1dHfqKdata.query_data(
order=Stock1dHfqKdata.timestamp.desc(),
limit=1,
return_type='domain')
target_date = latest_day[0].timestamp
start_timestamp = next_date(target_date, -50)
# 成交量
vol_df = get_top_volume_entities(entity_type='stock',
start_timestamp=start_timestamp,
end_timestamp=target_date,
pct=0.4)
current_entity_pool = vol_df.index.tolist()
# 计算均线
start = '2019-01-01'
my_selector = TargetSelector(start_timestamp=start,
end_timestamp=target_date,
select_mode=SelectMode.condition_or)
# add the factors
factor1 = VolumeUpMaFactor(entity_ids=current_entity_pool,
start_timestamp=start,
end_timestamp=target_date,
windows=[120, 250],
over_mode='or')
my_selector.add_factor(factor1)
my_selector.run()
long_stocks = my_selector.get_open_long_targets(
timestamp=target_date)
msg = 'no targets'
if long_stocks:
stocks = get_entities(provider='joinquant',
entity_schema=Stock,
entity_ids=long_stocks,
return_type='domain')
# add them to eastmoney
try:
try:
eastmoneypy.del_group('tech')
except:
pass
eastmoneypy.create_group('tech')
for stock in stocks:
eastmoneypy.add_to_group(stock.code, group_name='tech')
except Exception as e:
email_action.send_message(
zvt_config['email_username'], f'report_vol_up error',
'report_vol_up error:{}'.format(e))
infos = stocks_with_info(stocks)
msg = '\n'.join(infos) + '\n'
logger.info(msg)
email_action.send_message(zvt_config['email_username'],
f'{target_date} 改进版放量突破(半)年线选股结果', msg)
break
except Exception as e:
logger.exception('report_vol_up error:{}'.format(e))
time.sleep(60 * 3)
error_count = error_count + 1
if error_count == 10:
email_action.send_message(zvt_config['email_username'],
f'report_vol_up error',
'report_vol_up error:{}'.format(e))
from zvdata.utils.time_utils import now_pd_timestamp
from zvt.factors.ma.ma_factor import CrossMaFactor
from zvt.factors.target_selector import TargetSelector
my_selector = TargetSelector(start_timestamp='2018-10-01',
end_timestamp=now_pd_timestamp())
# add the factors
ma_factor = CrossMaFactor(start_timestamp='2018-10-01',
end_timestamp=now_pd_timestamp())
my_selector.add_filter_factor(ma_factor)
my_selector.run()
long_targets = my_selector.get_open_long_targets(timestamp='2019-11-11')
print(long_targets)
print(len(long_targets))
