def update(self, universe):
if isinstance(universe, (six.string_types, Instrument)):
universe = [universe]
new_set = set(universe)
if new_set != self._set:
self._set = new_set
Environment.get_instance().event_bus.publish_event(Event(EVENT.POST_UNIVERSE_CHANGED, universe=self._set))
def _handle_dividend_book_closure(self, trading_date):
for order_book_id, position in six.iteritems(self._positions):
if position.quantity == 0:
continue
dividend = Environment.get_instance().data_proxy.get_dividend_by_book_date(order_book_id, trading_date)
if dividend is None:
continue
dividend_per_share = sum(dividend['dividend_cash_before_tax'] / dividend['round_lot'])
if np.isnan(dividend_per_share):
raise RuntimeError("Dividend per share of {} is not supposed to be nan.".format(order_book_id))
position.dividend_(dividend_per_share)
if StockAccount.dividend_reinvestment:
last_price = Environment.get_instance().data_proxy.get_bar(order_book_id, trading_date).close
shares = position.quantity * dividend_per_share / last_price
position._quantity += shares
else:
self._dividend_receivable[order_book_id] = {
'quantity': position.quantity,
'dividend_per_share': dividend_per_share,
}
try:
self._dividend_receivable[order_book_id]['payable_date'] = self._int_to_date(
dividend['payable_date'][0]
)
except ValueError:
self._dividend_receivable[order_book_id]['payable_date'] = self._int_to_date(
dividend['ex_dividend_date'][0]
)
def plot(series_name, value):
"""
Add a point to custom series.
:param str series_name: the name of custom series
:param float value: the value of the series in this time
:return: None
"""
Environment.get_instance().add_plot(series_name, value)
def init(self):
if not self._init:
return
with ExecutionContext(EXECUTION_PHASE.ON_INIT):
with ModifyExceptionFromType(EXC_TYPE.USER_EXC):
self._init(self._user_context)
Environment.get_instance().event_bus.publish_event(Event(EVENT.POST_USER_INIT))
def is_de_listed(self):
"""
判断合约是否过期
"""
instrument = Environment.get_instance().get_instrument(self.order_book_id)
current_date = Environment.get_instance().trading_dt
if instrument.de_listed_date is not None and current_date >= instrument.de_listed_date:
return True
return False
def update_universe(id_or_symbols):
"""
该方法用于更新现在关注的证券的集合（e.g.：股票池）。PS：会在下一个bar事件触发时候产生（新的关注的股票池更新）效果。并且update_universe会是覆盖（overwrite）的操作而不是在已有的股票池的基础上进行增量添加。比如已有的股票池为['000001.XSHE', '000024.XSHE']然后调用了update_universe(['000030.XSHE'])之后，股票池就会变成000030.XSHE一个股票了，随后的数据更新也只会跟踪000030.XSHE这一个股票了。
:param id_or_ins: 标的物
:type id_or_ins: :class:`~Instrument` object | `str` | List[:class:`~Instrument`] | List[`str`]
"""
if isinstance(id_or_symbols, (six.string_types, Instrument)):
id_or_symbols = [id_or_symbols]
order_book_ids = set(assure_order_book_id(order_book_id) for order_book_id in id_or_symbols)
if order_book_ids != Environment.get_instance().get_universe():
Environment.get_instance().update_universe(order_book_ids)
def is_suspended(order_book_id, count=1):
"""
判断某只股票是否全天停牌。
:param str order_book_id: 某只股票的代码或股票代码，可传入单只股票的order_book_id, symbol
:param int count: 回溯获取的数据个数。默认为当前能够获取到的最近的数据
:return: count为1时 `bool`; count>1时 `pandas.DataFrame`
"""
dt = Environment.get_instance().calendar_dt.date()
order_book_id = assure_stock_order_book_id(order_book_id)
return Environment.get_instance().data_proxy.is_suspended(order_book_id, dt, count)
def prev_settlement(self):
"""
[float] 昨日结算价（期货专用）
"""
try:
return self._data['prev_settlement']
except (ValueError, KeyError):
pass
if self._prev_settlement is None:
trading_dt = Environment.get_instance().trading_dt
data_proxy = Environment.get_instance().data_proxy
self._prev_settlement = data_proxy.get_prev_settlement(self._instrument.order_book_id, trading_dt)
return self._prev_settlement
def prev_close(self):
"""
[float] 昨日收盘价
"""
try:
return self._data['prev_close']
except (ValueError, KeyError):
pass
if self._prev_close is None:
trading_dt = Environment.get_instance().trading_dt
data_proxy = Environment.get_instance().data_proxy
self._prev_close = data_proxy.get_prev_close(self._instrument.order_book_id, trading_dt)
return self._prev_close
def basis_spread(self):
try:
return self._data['basis_spread']
except (ValueError, KeyError):
if self._instrument.type != 'Future' or Environment.get_instance().config.base.run_type != RUN_TYPE.PAPER_TRADING:
raise
if self._basis_spread is None:
if self._instrument.underlying_symbol in ['IH', 'IC', 'IF']:
order_book_id = self.INDEX_MAP[self._instrument.underlying_symbol]
bar = Environment.get_instance().data_proxy.get_bar(order_book_id, None, '1m')
self._basis_spread = self.close - bar.close
else:
self._basis_spread = np.nan
return self._basis_spread
def is_st_stock(order_book_id, count=1):
"""
判断股票在一段时间内是否为ST股（包括ST与*ST）。
ST股是有退市风险因此风险比较大的股票，很多时候您也会希望判断自己使用的股票是否是'ST'股来避开这些风险大的股票。另外，我们目前的策略比赛也禁止了使用'ST'股。
:param str order_book_id: 某只股票的代码，可传入单只股票的order_book_id, symbol
:param int count: 回溯获取的数据个数。默认为当前能够获取到的最近的数据
:return: count为1时 `bool`; count>1时 `pandas.DataFrame`
"""
dt = Environment.get_instance().calendar_dt.date()
order_book_id = assure_stock_order_book_id(order_book_id)
return Environment.get_instance().data_proxy.is_st_stock(order_book_id, dt, count)
def margin_rate(self):
env = Environment.get_instance()
instrument = env.get_instrument(self.order_book_id)
margin_multiplier = env.config.base.margin_multiplier
return instrument.margin_rate * margin_multiplier
def run(config, source_code=None, user_funcs=None):
env = Environment(config)
persist_helper = None
init_succeed = False
mod_handler = ModHandler()
try:
# avoid register handlers everytime
# when running in ipython
set_loggers(config)
init_rqdatac(getattr(config.base, 'rqdatac_uri', None))
system_log.debug("\n" + pformat(config.convert_to_dict()))
env.set_strategy_loader(init_strategy_loader(env, source_code, user_funcs, config))
mod_handler.set_env(env)
mod_handler.start_up()
if not env.data_source:
env.set_data_source(BaseDataSource(config.base.data_bundle_path, getattr(config.base, "future_info", {})))
if env.price_board is None:
from rqalpha.data.bar_dict_price_board import BarDictPriceBoard
env.price_board = BarDictPriceBoard()
env.set_data_proxy(DataProxy(env.data_source, env.price_board))
_adjust_start_date(env.config, env.data_proxy)
ctx = ExecutionContext(const.EXECUTION_PHASE.GLOBAL)
ctx._push()
# FIXME
start_dt = datetime.datetime.combine(config.base.start_date, datetime.datetime.min.time())
env.calendar_dt = start_dt
env.trading_dt = start_dt
assert env.broker is not None
assert env.event_source is not None
if env.portfolio is None:
from rqalpha.portfolio import Portfolio
env.set_portfolio(Portfolio(config.base.accounts, config.base.init_positions))
env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_INIT))
scope = create_base_scope()
scope.update({"g": env.global_vars})
scope.update(get_strategy_apis())
scope = env.strategy_loader.load(scope)
if config.extra.enable_profiler:
enable_profiler(env, scope)
ucontext = StrategyContext()
executor = Executor(env)
persist_helper = init_persist_helper(env, ucontext, executor, config)
user_strategy = Strategy(env.event_bus, scope, ucontext)
env.user_strategy = user_strategy
env.event_bus.publish_event(Event(EVENT.BEFORE_STRATEGY_RUN))
if persist_helper:
with LogCapture(user_log) as log_capture:
user_strategy.init()
else:
user_strategy.init()
if config.extra.context_vars:
for k, v in config.extra.context_vars.items():
if isinstance(v, RqAttrDict):
v = v.__dict__
setattr(ucontext, k, v)
if persist_helper:
env.event_bus.publish_event(Event(EVENT.BEFORE_SYSTEM_RESTORED))
if persist_helper.restore(None):
user_system_log.info(_('system restored'))
else:
log_capture.replay()
env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_RESTORED))
init_succeed = True
bar_dict = BarMap(env.data_proxy, config.base.frequency)
executor.run(bar_dict)
env.event_bus.publish_event(Event(EVENT.POST_STRATEGY_RUN))
if env.profile_deco:
output_profile_result(env)
except CustomException as e:
if init_succeed and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_CRASH:
persist_helper.persist()
code = _exception_handler(e)
mod_handler.tear_down(code, e)
except Exception as e:
if init_succeed and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_CRASH:
persist_helper.persist()
exc_type, exc_val, exc_tb = sys.exc_info()
user_exc = create_custom_exception(exc_type, exc_val, exc_tb, config.base.strategy_file)
code = _exception_handler(user_exc)
mod_handler.tear_down(code, user_exc)
else:
if persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_NORMAL_EXIT:
persist_helper.persist()
result = mod_handler.tear_down(const.EXIT_CODE.EXIT_SUCCESS)
system_log.debug(_(u"strategy run successfully, normal exit"))
return result
def annualized_returns(self):
"""
[float] 累计年化收益率
"""
current_date = Environment.get_instance().trading_dt.date()
return self.unit_net_value ** (DAYS_CNT.DAYS_A_YEAR / float((current_date - self.start_date).days + 1)) - 1
def all_instruments(type=None, date=None):
"""
获取某个国家市场的所有合约信息。使用者可以通过这一方法很快地对合约信息有一个快速了解，目前仅支持中国市场。
:param str type: 需要查询合约类型，例如：type='CS'代表股票。默认是所有类型
:param date: 查询时间点
:type date: `str` | `datetime` | `date`
:return: `pandas DataFrame` 所有合约的基本信息。
其中type参数传入的合约类型和对应的解释如下：
========================= ===================================================
合约类型 说明
========================= ===================================================
CS Common Stock, 即股票
ETF Exchange Traded Fund, 即交易所交易基金
LOF Listed Open-Ended Fund，即上市型开放式基金
FenjiMu Fenji Mu Fund, 即分级母基金
FenjiA Fenji A Fund, 即分级A类基金
FenjiB Fenji B Funds, 即分级B类基金
INDX Index, 即指数
Future Futures，即期货，包含股指、国债和商品期货
========================= ===================================================
:example:
获取中国市场所有分级基金的基础信息:
.. code-block:: python3
:linenos:
[In]all_instruments('FenjiA')
[Out]
abbrev_symbol order_book_id product sector_code symbol
0 CYGA 150303.XSHE null null 华安创业板50A
1 JY500A 150088.XSHE null null 金鹰500A
2 TD500A 150053.XSHE null null 泰达稳健
3 HS500A 150110.XSHE null null 华商500A
4 QSAJ 150235.XSHE null null 鹏华证券A
...
"""
env = Environment.get_instance()
if date is None:
dt = env.trading_dt
else:
dt = pd.Timestamp(date).to_pydatetime()
dt = min(dt, env.trading_dt)
if type is not None:
if isinstance(type, six.string_types):
type = [type]
types = set()
for t in type:
if t == 'Stock':
types.add('CS')
elif t == 'Fund':
types.update(
['ETF', 'LOF', 'SF', 'FenjiA', 'FenjiB', 'FenjiMu'])
else:
types.add(t)
else:
types = None
result = env.data_proxy.all_instruments(types, dt)
if types is not None and len(types) == 1:
return pd.DataFrame([i.__dict__ for i in result])
return pd.DataFrame(
[[i.order_book_id, i.symbol, i.type, i.listed_date, i.de_listed_date]
for i in result],
columns=[
'order_book_id', 'symbol', 'type', 'listed_date', 'de_listed_date'
])
def order_shares(id_or_ins, amount, price=None, style=None):
"""
落指定股数的买/卖单，最常见的落单方式之一。如有需要落单类型当做一个参量传入，如果忽略掉落单类型，那么默认是市价单（market order）。
:param id_or_ins: 下单标的物
:type id_or_ins: :class:`~Instrument` object | `str`
:param int amount: 下单量, 正数代表买入，负数代表卖出。将会根据一手xx股来向下调整到一手的倍数，比如中国A股就是调整成100股的倍数。
:param float price: 下单价格，默认为None，表示 :class:`~MarketOrder`, 此参数主要用于简化 `style` 参数。
:param style: 下单类型, 默认是市价单。目前支持的订单类型有 :class:`~LimitOrder` 和 :class:`~MarketOrder`
:type style: `OrderStyle` object
:return: :class:`~Order` object
:example:
.. code-block:: python
#购买Buy 2000 股的平安银行股票，并以市价单发送：
order_shares('000001.XSHE', 2000)
#卖出2000股的平安银行股票，并以市价单发送：
order_shares('000001.XSHE', -2000)
#购买1000股的平安银行股票，并以限价单发送，价格为￥10：
order_shares('000001.XSHG', 1000, style=LimitOrder(10))
"""
if amount == 0:
# 如果下单量为0，则认为其并没有发单，则直接返回None
return None
style = cal_style(price, style)
if isinstance(style, LimitOrder):
if style.get_limit_price() <= 0:
raise RQInvalidArgument(_(u"Limit order price should be positive"))
order_book_id = assure_stock_order_book_id(id_or_ins)
env = Environment.get_instance()
price = env.get_last_price(order_book_id)
if np.isnan(price):
user_system_log.warn(
_(u"Order Creation Failed: [{order_book_id}] No market data").
format(order_book_id=order_book_id))
return
if amount > 0:
side = SIDE.BUY
else:
amount = abs(amount)
side = SIDE.SELL
round_lot = int(env.get_instrument(order_book_id).round_lot)
try:
amount = int(Decimal(amount) / Decimal(round_lot)) * round_lot
except ValueError:
amount = 0
r_order = Order.__from_create__(order_book_id, amount, side, style, None)
if price == 0:
user_system_log.warn(
_(u"Order Creation Failed: [{order_book_id}] No market data").
format(order_book_id=order_book_id))
r_order.mark_rejected(
_(u"Order Creation Failed: [{order_book_id}] No market data").
format(order_book_id=order_book_id))
return r_order
if amount == 0:
# 如果计算出来的下单量为0, 则不生成Order, 直接返回None
# 因为很多策略会直接在handle_bar里面执行order_target_percent之类的函数，经常会出现下一个量为0的订单，如果这些订单都生成是没有意义的。
r_order.mark_rejected(_(u"Order Creation Failed: 0 order quantity"))
return r_order
if r_order.type == ORDER_TYPE.MARKET:
r_order.set_frozen_price(price)
if env.can_submit_order(r_order):
env.broker.submit_order(r_order)
return r_order
def __init__(self, commission_multiplier):
self.commission_multiplier = commission_multiplier
self.hedge_type = HEDGE_TYPE.SPECULATION
self.env = Environment.get_instance()
def tick_size(self):
return Environment.get_instance().data_proxy.get_tick_size(self.order_book_id)
def run(config, source_code=None, user_funcs=None):
env = Environment(config)
persist_helper = None
init_succeed = False
mod_handler = ModHandler()
try:
# avoid register handlers everytime
# when running in ipython
set_loggers(config)
basic_system_log.debug("\n" + pformat(config.convert_to_dict()))
if source_code is not None:
env.set_strategy_loader(SourceCodeStrategyLoader(source_code))
elif user_funcs is not None:
env.set_strategy_loader(UserFuncStrategyLoader(user_funcs))
else:
env.set_strategy_loader(
FileStrategyLoader(config.base.strategy_file))
env.set_global_vars(GlobalVars())
mod_handler.set_env(env)
mod_handler.start_up()
if not env.data_source:
env.set_data_source(BaseDataSource(config.base.data_bundle_path))
env.set_data_proxy(DataProxy(env.data_source))
Scheduler.set_trading_dates_(env.data_source.get_trading_calendar())
scheduler = Scheduler(config.base.frequency)
mod_scheduler._scheduler = scheduler
env._universe = StrategyUniverse()
_adjust_start_date(env.config, env.data_proxy)
_validate_benchmark(env.config, env.data_proxy)
# FIXME
start_dt = datetime.datetime.combine(config.base.start_date,
datetime.datetime.min.time())
env.calendar_dt = start_dt
env.trading_dt = start_dt
broker = env.broker
assert broker is not None
env.portfolio = broker.get_portfolio()
env.benchmark_portfolio = create_benchmark_portfolio(env)
event_source = env.event_source
assert event_source is not None
bar_dict = BarMap(env.data_proxy, config.base.frequency)
env.set_bar_dict(bar_dict)
if env.price_board is None:
from .core.bar_dict_price_board import BarDictPriceBoard
env.price_board = BarDictPriceBoard()
ctx = ExecutionContext(const.EXECUTION_PHASE.GLOBAL)
ctx._push()
env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_INIT))
scope = create_base_scope()
scope.update({"g": env.global_vars})
apis = api_helper.get_apis()
scope.update(apis)
scope = env.strategy_loader.load(scope)
if env.config.extra.enable_profiler:
enable_profiler(env, scope)
ucontext = StrategyContext()
user_strategy = Strategy(env.event_bus, scope, ucontext)
scheduler.set_user_context(ucontext)
if not config.extra.force_run_init_when_pt_resume:
with run_with_user_log_disabled(disabled=config.base.resume_mode):
user_strategy.init()
if config.extra.context_vars:
for k, v in six.iteritems(config.extra.context_vars):
setattr(ucontext, k, v)
if config.base.persist:
persist_provider = env.persist_provider
if persist_provider is None:
raise RuntimeError(
_(u"Missing persist provider. You need to set persist_provider before use persist"
))
persist_helper = PersistHelper(persist_provider, env.event_bus,
config.base.persist_mode)
env.set_persist_helper(persist_helper)
persist_helper.register('core', CoreObjectsPersistProxy(scheduler))
persist_helper.register('user_context', ucontext)
persist_helper.register('global_vars', env.global_vars)
persist_helper.register('universe', env._universe)
if isinstance(event_source, Persistable):
persist_helper.register('event_source', event_source)
persist_helper.register('portfolio', env.portfolio)
if env.benchmark_portfolio:
persist_helper.register('benchmark_portfolio',
env.benchmark_portfolio)
for name, module in six.iteritems(env.mod_dict):
if isinstance(module, Persistable):
persist_helper.register('mod_{}'.format(name), module)
# broker will restore open orders from account
if isinstance(broker, Persistable):
persist_helper.register('broker', broker)
env.event_bus.publish_event(Event(EVENT.BEFORE_SYSTEM_RESTORED))
persist_helper.restore()
env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_RESTORED))
init_succeed = True
# When force_run_init_when_pt_resume is active,
# we should run `init` after restore persist data
if config.extra.force_run_init_when_pt_resume:
assert config.base.resume_mode == True
with run_with_user_log_disabled(disabled=False):
env._universe._set = set()
user_strategy.init()
from .core.executor import Executor
Executor(env).run(bar_dict)
if env.profile_deco:
output_profile_result(env)
except CustomException as e:
if init_succeed and env.config.base.persist and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_CRASH:
persist_helper.persist()
code = _exception_handler(e)
mod_handler.tear_down(code, e)
except Exception as e:
if init_succeed and env.config.base.persist and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_CRASH:
persist_helper.persist()
exc_type, exc_val, exc_tb = sys.exc_info()
user_exc = create_custom_exception(exc_type, exc_val, exc_tb,
config.base.strategy_file)
code = _exception_handler(user_exc)
mod_handler.tear_down(code, user_exc)
else:
if (env.config.base.persist and persist_helper
and env.config.base.persist_mode
== const.PERSIST_MODE.ON_NORMAL_EXIT):
persist_helper.persist()
result = mod_handler.tear_down(const.EXIT_CODE.EXIT_SUCCESS)
system_log.debug(_(u"strategy run successfully, normal exit"))
return result
def _get_tax(self, order_book_id, side, cost_money):
instrument = Environment.get_instance().get_instrument(order_book_id)
if instrument.type != 'CS':
return 0
return cost_money * self.tax_rate if side == SIDE.SELL else 0
def margin_rate(self):
env = Environment.get_instance()
margin_info = env.data_proxy.get_margin_info(self.order_book_id)
margin_multiplier = env.config.base.margin_multiplier
return margin_info['long_margin_ratio'] * margin_multiplier
def order(id_or_ins, amount, side, position_effect, style):
if not isinstance(style, OrderStyle):
raise RuntimeError
if amount < 0:
raise RuntimeError
if amount == 0:
user_system_log.warn(_(u"Order Creation Failed: Order amount is 0."))
return None
if isinstance(style, LimitOrder) and style.get_limit_price() <= 0:
raise RQInvalidArgument(_(u"Limit order price should be positive"))
order_book_id = assure_future_order_book_id(id_or_ins)
env = Environment.get_instance()
if env.config.base.run_type != RUN_TYPE.BACKTEST:
if "88" in order_book_id:
raise RQInvalidArgument(
_(u"Main Future contracts[88] are not supported in paper trading."
))
if "99" in order_book_id:
raise RQInvalidArgument(
_(u"Index Future contracts[99] are not supported in paper trading."
))
price = env.get_last_price(order_book_id)
if not is_valid_price(price):
user_system_log.warn(
_(u"Order Creation Failed: [{order_book_id}] No market data").
format(order_book_id=order_book_id))
return
amount = int(amount)
env = Environment.get_instance()
orders = []
if position_effect == POSITION_EFFECT.CLOSE:
if side == SIDE.BUY:
if env.portfolio:
position = env.portfolio.positions[order_book_id]
sell_quantity, sell_old_quantity = position.sell_quantity, position.sell_old_quantity
else:
position = env.booking.get_position(order_book_id,
POSITION_DIRECTION.SHORT)
sell_quantity, sell_old_quantity = position.quantity, position.old_quantity
# 如果平仓量大于持仓量，则 Warning 并 取消订单创建
if amount > sell_quantity:
user_system_log.warn(
_(u"Order Creation Failed: close amount {amount} is larger than position "
u"quantity {quantity}").format(amount=amount,
quantity=sell_quantity))
return []
sell_old_quantity = sell_old_quantity
if amount > sell_old_quantity:
if sell_old_quantity != 0:
# 如果有昨仓，则创建一个 POSITION_EFFECT.CLOSE 的平仓单
orders.append(
Order.__from_create__(order_book_id, sell_old_quantity,
side, style,
POSITION_EFFECT.CLOSE))
# 剩下还有仓位，则创建一个 POSITION_EFFECT.CLOSE_TODAY 的平今单
orders.append(
Order.__from_create__(order_book_id,
amount - sell_old_quantity, side,
style, POSITION_EFFECT.CLOSE_TODAY))
else:
# 创建 POSITION_EFFECT.CLOSE 的平仓单
orders.append(
Order.__from_create__(order_book_id, amount, side, style,
POSITION_EFFECT.CLOSE))
else:
if env.portfolio:
position = env.portfolio.positions[order_book_id]
buy_quantity, buy_old_quantity = position.buy_quantity, position.buy_old_quantity
else:
position = env.booking.get_position(order_book_id,
POSITION_DIRECTION.LONG)
buy_quantity, buy_old_quantity = position.quantity, position.old_quantity
if amount > buy_quantity:
user_system_log.warn(
_(u"Order Creation Failed: close amount {amount} is larger than position "
u"quantity {quantity}").format(amount=amount,
quantity=buy_quantity))
return []
buy_old_quantity = buy_old_quantity
if amount > buy_old_quantity:
if buy_old_quantity != 0:
orders.append(
Order.__from_create__(order_book_id, buy_old_quantity,
side, style,
POSITION_EFFECT.CLOSE))
orders.append(
Order.__from_create__(order_book_id,
amount - buy_old_quantity, side,
style, POSITION_EFFECT.CLOSE_TODAY))
else:
orders.append(
Order.__from_create__(order_book_id, amount, side, style,
POSITION_EFFECT.CLOSE))
else:
orders.append(
Order.__from_create__(order_book_id, amount, side, style,
position_effect))
if not is_valid_price(price):
user_system_log.warn(
_(u"Order Creation Failed: [{order_book_id}] No market data").
format(order_book_id=order_book_id))
return []
if len(orders) > 1:
user_system_log.warn(
_("Order was separated, original order: {original_order_repr}, new orders: [{new_orders_repr}]"
.format(
original_order_repr=
"Order(order_book_id={}, quantity={}, side={}, position_effect={})"
.format(order_book_id, amount, side, position_effect),
new_orders_repr=", ".join([
"Order({}, {}, {}, {})".format(o.order_book_id,
o.quantity, o.side,
o.position_effect)
for o in orders
]))))
for o in orders:
if o.type == ORDER_TYPE.MARKET:
o.set_frozen_price(price)
if env.can_submit_order(o):
env.broker.submit_order(o)
else:
orders.remove(o)
# 向前兼容，如果创建的order_list 只包含一个订单的话，直接返回对应的订单，否则返回列表
if len(orders) == 1:
return orders[0]
else:
return orders
def __init__(self):
self._env = Environment.get_instance()
self._tenors = list(six.itervalues(YIELD_CURVE_TENORS))
def contract_multiplier(self):
return Environment.get_instance().get_instrument(self.order_book_id).contract_multiplier
def run(config, source_code=None, user_funcs=None):
env = Environment(config)
persist_helper = None
init_succeed = False
mod_handler = ModHandler()
try:
# avoid register handlers everytime
# when running in ipython
set_loggers(config)
basic_system_log.debug("\n" + pformat(config.convert_to_dict()))
env.set_strategy_loader(init_strategy_loader(env, source_code, user_funcs, config))
env.set_global_vars(GlobalVars())
mod_handler.set_env(env)
mod_handler.start_up()
if not env.data_source:
env.set_data_source(BaseDataSource(config.base.data_bundle_path, getattr(config.base, "future_info", {})))
if env.price_board is None:
from rqalpha.data.bar_dict_price_board import BarDictPriceBoard
env.price_board = BarDictPriceBoard()
env.set_data_proxy(DataProxy(env.data_source, env.price_board))
Scheduler.set_trading_dates_(env.data_source.get_trading_calendar())
scheduler = Scheduler(config.base.frequency)
mod_scheduler._scheduler = scheduler
env._universe = StrategyUniverse()
_adjust_start_date(env.config, env.data_proxy)
# FIXME
start_dt = datetime.datetime.combine(config.base.start_date, datetime.datetime.min.time())
env.calendar_dt = start_dt
env.trading_dt = start_dt
broker = env.broker
assert broker is not None
env.portfolio = broker.get_portfolio()
if env.benchmark_provider:
env.benchmark_portfolio = BenchmarkPortfolio(env.benchmark_provider, env.portfolio.units)
event_source = env.event_source
assert event_source is not None
bar_dict = BarMap(env.data_proxy, config.base.frequency)
env.set_bar_dict(bar_dict)
ctx = ExecutionContext(const.EXECUTION_PHASE.GLOBAL)
ctx._push()
env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_INIT))
scope = create_base_scope(config.base.run_type == RUN_TYPE.BACKTEST)
scope.update({
"g": env.global_vars
})
apis = api_helper.get_apis()
scope.update(apis)
scope = env.strategy_loader.load(scope)
if env.config.extra.enable_profiler:
enable_profiler(env, scope)
ucontext = StrategyContext()
scheduler.set_user_context(ucontext)
from .core.executor import Executor
executor = Executor(env)
persist_helper = init_persist_helper(env, scheduler, ucontext, executor, config)
if persist_helper:
should_resume = persist_helper.should_resume()
should_run_init = persist_helper.should_run_init()
else:
should_resume = False
should_run_init = True
user_strategy = Strategy(env.event_bus, scope, ucontext, should_run_init)
env.user_strategy = user_strategy
if (should_resume and not should_run_init) or not should_resume:
with run_with_user_log_disabled(disabled=should_resume):
user_strategy.init()
if config.extra.context_vars:
for k, v in six.iteritems(config.extra.context_vars):
if isinstance(v, RqAttrDict):
v = v.__dict__
setattr(ucontext, k, v)
if persist_helper:
env.event_bus.publish_event(Event(EVENT.BEFORE_SYSTEM_RESTORED))
env.event_bus.publish_event(Event(EVENT.DO_RESTORE))
env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_RESTORED))
init_succeed = True
if should_resume and should_run_init:
user_strategy.init()
executor.run(bar_dict)
if env.profile_deco:
output_profile_result(env)
except CustomException as e:
if init_succeed and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_CRASH:
persist_helper.persist()
code = _exception_handler(e)
mod_handler.tear_down(code, e)
except Exception as e:
if init_succeed and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_CRASH:
persist_helper.persist()
exc_type, exc_val, exc_tb = sys.exc_info()
user_exc = create_custom_exception(exc_type, exc_val, exc_tb, config.base.strategy_file)
code = _exception_handler(user_exc)
mod_handler.tear_down(code, user_exc)
else:
if persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_NORMAL_EXIT:
persist_helper.persist()
result = mod_handler.tear_down(const.EXIT_CODE.EXIT_SUCCESS)
system_log.debug(_(u"strategy run successfully, normal exit"))
return result
def listing(self):
now = Environment.get_instance().calendar_dt
return self.listed_date <= now <= self.de_listed_date
def margin_rate(self):
return self._instrument.margin_rate * Environment.get_instance(
).config.base.margin_multiplier
def history_bars(order_book_id,
bar_count,
frequency,
fields=None,
skip_suspended=True,
include_now=False,
adjust_type='pre'):
"""
获取指定合约的历史行情，同时支持日以及分钟历史数据。不能在init中调用。 注意，该API会自动跳过停牌数据。
日回测获取分钟历史数据：不支持
日回测获取日历史数据
========================= ===================================================
调用时间 返回数据
========================= ===================================================
T日before_trading T-1日day bar
T日handle_bar T日day bar
========================= ===================================================
分钟回测获取日历史数据
========================= ===================================================
调用时间 返回数据
========================= ===================================================
T日before_trading T-1日day bar
T日handle_bar T-1日day bar
========================= ===================================================
分钟回测获取分钟历史数据
========================= ===================================================
调用时间 返回数据
========================= ===================================================
T日before_trading T-1日最后一个minute bar
T日handle_bar T日当前minute bar
========================= ===================================================
:param order_book_id: 合约代码
:type order_book_id: `str`
:param int bar_count: 获取的历史数据数量，必填项
:param str frequency: 获取数据什么样的频率进行。'1d'或'1m'分别表示每日和每分钟，必填项
:param str fields: 返回数据字段。必填项。见下方列表。
========================= ===================================================
fields 字段名
========================= ===================================================
datetime 时间戳
open 开盘价
high 最高价
low 最低价
close 收盘价
volume 成交量
total_turnover 成交额
open_interest 持仓量（期货专用）
basis_spread 期现差（股指期货专用）
settlement 结算价（期货日线专用）
prev_settlement 结算价（期货日线专用）
========================= ===================================================
:param bool skip_suspended: 是否跳过停牌数据
:param bool include_now: 是否包含当前数据
:param str adjust_type: 复权类型，默认为前复权 pre；可选 pre, none, post
:return: `ndarray`, 方便直接与talib等计算库对接，效率较history返回的DataFrame更高。
:example:
获取最近5天的日线收盘价序列（策略当前日期为20160706）:
.. code-block:: python3
:linenos:
[In]
logger.info(history_bars('000002.XSHE', 5, '1d', 'close'))
[Out]
[ 8.69 8.7 8.71 8.81 8.81]
"""
order_book_id = assure_order_book_id(order_book_id)
env = Environment.get_instance()
dt = env.calendar_dt
if frequency[-1] not in {'m', 'd'}:
raise RQInvalidArgument('invalid frequency {}'.format(frequency))
if frequency[-1] == 'm' and env.config.base.frequency == '1d':
raise RQInvalidArgument('can not get minute history in day back test')
if frequency[-1] == 'd' and frequency != '1d':
raise RQInvalidArgument('invalid frequency')
if adjust_type not in {'pre', 'post', 'none'}:
raise RuntimeError('invalid adjust_type')
if frequency == '1d':
sys_frequency = Environment.get_instance().config.base.frequency
if ((sys_frequency in ['1m', 'tick'] and not include_now)
or ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING):
dt = env.data_proxy.get_previous_trading_date(
env.trading_dt.date())
# 当 EXECUTION_PHASE.BEFORE_TRADING 的时候，强制 include_now 为 False
include_now = False
if sys_frequency == "1d":
# 日回测不支持 include_now
include_now = False
if fields is None:
fields = ["datetime", "open", "high", "low", "close", "volume"]
return env.data_proxy.history_bars(order_book_id,
bar_count,
frequency,
fields,
dt,
skip_suspended=skip_suspended,
include_now=include_now,
adjust_type=adjust_type,
adjust_orig=env.trading_dt)
def is_night_trading(universe):
# for compatible
from rqalpha.environment import Environment
return Environment.get_instance().data_proxy.is_night_trading(universe)
def init_fixture(self):
from rqalpha.utils import RqAttrDict
from rqalpha.environment import Environment
super(EnvironmentFixture, self).init_fixture()
self.env = Environment(RqAttrDict(self.env_config))
def symbol(order_book_id, sep=", "):
if isinstance(order_book_id, six.string_types):
return "{}[{}]".format(order_book_id, Environment.get_instance().get_instrument(order_book_id).symbol)
else:
s = sep.join(symbol(item) for item in order_book_id)
return s
def history_bars(
order_book_id,
bar_count,
frequency,
fields=None,
skip_suspended=True,
include_now=False,
adjust_type="pre",
):
# type:(str, int, str, Optional[Union[str, List[str]]], Optional[bool], Optional[bool], Optional[str]) -> np.ndarray
"""
获取指定合约的历史 k 线行情，同时支持日以及分钟历史数据。不能在init中调用。
日回测获取分钟历史数据：不支持
日回测获取日历史数据
========================= ===================================================
调用时间 返回数据
========================= ===================================================
T日before_trading T-1日day bar
T日handle_bar T日day bar
========================= ===================================================
分钟回测获取日历史数据
========================= ===================================================
调用时间 返回数据
========================= ===================================================
T日before_trading T-1日day bar
T日handle_bar T-1日day bar
========================= ===================================================
分钟回测获取分钟历史数据
========================= ===================================================
调用时间 返回数据
========================= ===================================================
T日before_trading T-1日最后一个minute bar
T日handle_bar T日当前minute bar
========================= ===================================================
:param order_book_id: 合约代码
:param bar_count: 获取的历史数据数量，必填项
:param frequency: 获取数据什么样的频率进行。'1d'、'1m' 和 '1w' 分别表示每日、每分钟和每周，必填项
:param fields: 返回数据字段。必填项。见下方列表。
:param skip_suspended: 是否跳过停牌数据
:param include_now: 是否包含当前数据
:param adjust_type: 复权类型，默认为前复权 pre；可选 pre, none, post
========================= ===================================================
fields 字段名
========================= ===================================================
datetime 时间戳
open 开盘价
high 最高价
low 最低价
close 收盘价
volume 成交量
total_turnover 成交额
open_interest 持仓量（期货专用）
basis_spread 期现差（股指期货专用）
settlement 结算价（期货日线专用）
prev_settlement 结算价（期货日线专用）
========================= ===================================================
:example:
获取最近5天的日线收盘价序列（策略当前日期为20160706）:
.. code-block:: python3
:linenos:
[In]
logger.info(history_bars('000002.XSHE', 5, '1d', 'close'))
[Out]
[ 8.69 8.7 8.71 8.81 8.81]
"""
order_book_id = assure_order_book_id(order_book_id)
env = Environment.get_instance()
dt = env.calendar_dt
if frequency[-1] == "m" and env.config.base.frequency == "1d":
raise RQInvalidArgument("can not get minute history in day back test")
if frequency[-1] == "d" and frequency != "1d":
raise RQInvalidArgument("invalid frequency")
if adjust_type not in {"pre", "post", "none"}:
raise RuntimeError("invalid adjust_type")
if frequency == "1d":
sys_frequency = Environment.get_instance().config.base.frequency
if (
sys_frequency in ["1m", "tick"]
and not include_now
and ExecutionContext.phase() != EXECUTION_PHASE.AFTER_TRADING
) or (ExecutionContext.phase() in (EXECUTION_PHASE.BEFORE_TRADING, EXECUTION_PHASE.OPEN_AUCTION)):
dt = env.data_proxy.get_previous_trading_date(env.trading_dt.date())
# 当 EXECUTION_PHASE.BEFORE_TRADING 的时候，强制 include_now 为 False
include_now = False
if sys_frequency == "1d":
# 日回测不支持 include_now
include_now = False
if fields is None:
fields = ["datetime", "open", "high", "low", "close", "volume"]
return env.data_proxy.history_bars(
order_book_id,
bar_count,
frequency,
fields,
dt,
skip_suspended=skip_suspended,
include_now=include_now,
adjust_type=adjust_type,
adjust_orig=env.trading_dt,
)
def industry(code):
# type: (str) -> List[str]
"""
获得属于某一行业的所有股票列表。
:param code: 行业名称或行业代码。例如，农业可填写industry_code.A01 或 'A01'
我们目前使用的行业分类来自于中国国家统计局的 `国民经济行业分类 <http://www.stats.gov.cn/tjsj/tjbz/hyflbz/>`_ ，可以使用这里的任何一个行业代码来调用行业的股票列表：
========================= ===================================================
行业代码 行业名称
========================= ===================================================
A01 农业
A02 林业
A03 畜牧业
A04 渔业
A05 农、林、牧、渔服务业
B06 煤炭开采和洗选业
B07 石油和天然气开采业
B08 黑色金属矿采选业
B09 有色金属矿采选业
B10 非金属矿采选业
B11 开采辅助活动
B12 其他采矿业
C13 农副食品加工业
C14 食品制造业
C15 酒、饮料和精制茶制造业
C16 烟草制品业
C17 纺织业
C18 纺织服装、服饰业
C19 皮革、毛皮、羽毛及其制品和制鞋业
C20 木材加工及木、竹、藤、棕、草制品业
C21 家具制造业
C22 造纸及纸制品业
C23 印刷和记录媒介复制业
C24 文教、工美、体育和娱乐用品制造业
C25 石油加工、炼焦及核燃料加工业
C26 化学原料及化学制品制造业
C27 医药制造业
C28 化学纤维制造业
C29 橡胶和塑料制品业
C30 非金属矿物制品业
C31 黑色金属冶炼及压延加工业
C32 有色金属冶炼和压延加工业
C33 金属制品业
C34 通用设备制造业
C35 专用设备制造业
C36 汽车制造业
C37 铁路、船舶、航空航天和其它运输设备制造业
C38 电气机械及器材制造业
C39 计算机、通信和其他电子设备制造业
C40 仪器仪表制造业
C41 其他制造业
C42 废弃资源综合利用业
C43 金属制品、机械和设备修理业
D44 电力、热力生产和供应业
D45 燃气生产和供应业
D46 水的生产和供应业
E47 房屋建筑业
E48 土木工程建筑业
E49 建筑安装业
E50 建筑装饰和其他建筑业
F51 批发业
F52 零售业
G53 铁路运输业
G54 道路运输业
G55 水上运输业
G56 航空运输业
G57 管道运输业
G58 装卸搬运和运输代理业
G59 仓储业
G60 邮政业
H61 住宿业
H62 餐饮业
I63 电信、广播电视和卫星传输服务
I64 互联网和相关服务
I65 软件和信息技术服务业
J66 货币金融服务
J67 资本市场服务
J68 保险业
J69 其他金融业
K70 房地产业
L71 租赁业
L72 商务服务业
M73 研究和试验发展
M74 专业技术服务业
M75 科技推广和应用服务业
N76 水利管理业
N77 生态保护和环境治理业
N78 公共设施管理业
O79 居民服务业
O80 机动车、电子产品和日用产品修理业
O81 其他服务业
P82 教育
Q83 卫生
Q84 社会工作
R85 新闻和出版业
R86 广播、电视、电影和影视录音制作业
R87 文化艺术业
R88 体育
R89 娱乐业
S90 综合
========================= ===================================================
:example:
.. code-block:: python3
:linenos:
def init(context):
stock_list = industry('A01')
logger.info("农业股票列表：" + str(stock_list))
#INITINFO 农业股票列表：['600354.XSHG', '601118.XSHG', '002772.XSHE', '600371.XSHG', '600313.XSHG', '600672.XSHG', '600359.XSHG', '300143.XSHE', '002041.XSHE', '600762.XSHG', '600540.XSHG', '300189.XSHE', '600108.XSHG', '300087.XSHE', '600598.XSHG', '000998.XSHE', '600506.XSHG']
"""
if isinstance(code, IndustryCodeItem):
code = code.code
else:
code = to_industry_code(code)
cs_instruments = Environment.get_instance().data_proxy.all_instruments(
(INSTRUMENT_TYPE.CS, ))
return [i.order_book_id for i in cs_instruments if i.industry_code == code]
def register_event(self):
"""
注册事件
"""
event_bus = Environment.get_instance().event_bus
event_bus.prepend_listener(EVENT.PRE_BEFORE_TRADING, self._pre_before_trading)
def _margin_of(self, quantity, price):
env = Environment.get_instance()
instrument = env.data_proxy.instruments(self.order_book_id)
return quantity * instrument.contract_multiplier * price * self.margin_rate
def register_event(self):
event_bus = Environment.get_instance().event_bus
event_bus.prepend_listener(EVENT.PRE_BEFORE_TRADING,
self._pre_before_trading)
event_bus.prepend_listener(EVENT.POST_SETTLEMENT,
self._post_settlement)
def get_trading_period(universe, accounts):
# for compatible
from rqalpha.environment import Environment
trading_period = STOCK_TRADING_PERIOD if DEFAULT_ACCOUNT_TYPE.STOCK in accounts else []
return Environment.get_instance().data_proxy.get_trading_period(
universe, trading_period)
def order_value(id_or_ins, cash_amount, price=None, style=None):
"""
使用想要花费的金钱买入/卖出股票，而不是买入/卖出想要的股数，正数代表买入，负数代表卖出。股票的股数总是会被调整成对应的100的倍数（在A中国A股市场1手是100股）。当您提交一个卖单时，该方法代表的意义是您希望通过卖出该股票套现的金额。如果金额超出了您所持有股票的价值，那么您将卖出所有股票。需要注意，如果资金不足，该API将不会创建发送订单。
:param id_or_ins: 下单标的物
:type id_or_ins: :class:`~Instrument` object | `str`
:param float cash_amount: 需要花费现金购买/卖出证券的数目。正数代表买入，负数代表卖出。
:param float price: 下单价格，默认为None，表示 :class:`~MarketOrder`, 此参数主要用于简化 `style` 参数。
:param style: 下单类型, 默认是市价单。目前支持的订单类型有 :class:`~LimitOrder` 和 :class:`~MarketOrder`
:type style: `OrderStyle` object
:return: :class:`~Order` object
:example:
.. code-block:: python
#买入价值￥10000的平安银行股票，并以市价单发送。如果现在平安银行股票的价格是￥7.5，那么下面的代码会买入1300股的平安银行，因为少于100股的数目将会被自动删除掉：
order_value('000001.XSHE', 10000)
#卖出价值￥10000的现在持有的平安银行：
order_value('000001.XSHE', -10000)
"""
style = cal_style(price, style)
if isinstance(style, LimitOrder):
if style.get_limit_price() <= 0:
raise RQInvalidArgument(_(u"Limit order price should be positive"))
order_book_id = assure_stock_order_book_id(id_or_ins)
env = Environment.get_instance()
price = env.get_last_price(order_book_id)
if not is_valid_price(price):
user_system_log.warn(
_(u"Order Creation Failed: [{order_book_id}] No market data").
format(order_book_id=order_book_id))
return
if price == 0:
return order_shares(order_book_id, 0, style)
account = env.portfolio.accounts[DEFAULT_ACCOUNT_TYPE.STOCK.name]
round_lot = int(env.get_instrument(order_book_id).round_lot)
if cash_amount > 0:
cash_amount = min(cash_amount, account.cash)
if isinstance(style, MarketOrder):
amount = int(
Decimal(cash_amount) / Decimal(price) /
Decimal(round_lot)) * round_lot
else:
amount = int(
Decimal(cash_amount) / Decimal(style.get_limit_price()) /
Decimal(round_lot)) * round_lot
# if the cash_amount is larger than you current security’s position,
# then it will sell all shares of this security.
position = account.positions[order_book_id]
amount = downsize_amount(amount, position)
return order_shares(order_book_id, amount, style=style)
def open_orders(self):
return Environment.get_instance().broker.get_open_orders(self.order_book_id)
def _on_before_trading(self, _):
trading_date = Environment.get_instance().trading_dt.date()
for position in self._iter_pos():
self._total_cash += position.before_trading(trading_date)
def order_target_portfolio(target_portfolio):
# type: (Dict[Union[str, Instrument], float]) -> List[Order]
"""
买入/卖出证券以批量调整证券的仓位，以期使其持仓市值占账户总权益的比重达到指定值。
:param target_portfolio: 下单标的物及其目标市值占比的字典
:example:
.. code-block:: python
# 调整仓位，以使平安银行和万科 A 的持仓占比分别达到 10% 和 15%
order_target_portfolio({
'000001.XSHE': 0.1
'000002.XSHE': 0.15
})
"""
if isinstance(target_portfolio, pd.Series):
# FIXME: kind of dirty
total_percent = sum(target_portfolio)
else:
total_percent = sum(target_portfolio.values())
if total_percent > 1 and not np.isclose(total_percent, 1):
raise RQInvalidArgument(
_(u"total percent should be lower than 1, current: {}").format(
total_percent))
env = Environment.get_instance()
account = env.portfolio.accounts[DEFAULT_ACCOUNT_TYPE.STOCK]
account_value = account.total_value
target_quantities = {}
for id_or_ins, target_percent in target_portfolio.items():
order_book_id = assure_order_book_id(id_or_ins)
if target_percent < 0:
raise RQInvalidArgument(
_(u"target percent of {} should between 0 and 1, current: {}").
format(order_book_id, target_percent))
price = env.data_proxy.get_last_price(order_book_id)
if not is_valid_price(price):
user_system_log.warn(
_(u"Order Creation Failed: [{order_book_id}] No market data").
format(order_book_id=order_book_id))
continue
target_quantities[order_book_id] = (account_value * target_percent /
price, price)
close_orders, open_orders = [], []
current_quantities = {
p.order_book_id: p.quantity
for p in account.get_positions()
if p.direction == POSITION_DIRECTION.LONG
}
for order_book_id, quantity in current_quantities.items():
if order_book_id not in target_portfolio:
close_orders.append(
Order.__from_create__(order_book_id, quantity, SIDE.SELL,
MarketOrder(), POSITION_EFFECT.CLOSE))
for order_book_id, (target_quantity, price) in target_quantities.items():
ins = assure_instrument(order_book_id)
round_lot = 100
if order_book_id in current_quantities:
delta_quantity = target_quantity - current_quantities[order_book_id]
else:
delta_quantity = target_quantity
if _is_ksh(ins):
# KSH can buy(sell) 201, 202 shares
delta_quantity = _get_ksh_amount(delta_quantity)
else:
delta_quantity = int(
Decimal(delta_quantity) / Decimal(round_lot)) * round_lot
if delta_quantity > 0:
open_order = Order.__from_create__(order_book_id, delta_quantity,
SIDE.BUY, MarketOrder(),
POSITION_EFFECT.OPEN)
open_order.set_frozen_price(price)
open_orders.append(open_order)
elif delta_quantity < -1:
close_order = Order.__from_create__(order_book_id,
abs(delta_quantity), SIDE.SELL,
MarketOrder(),
POSITION_EFFECT.CLOSE)
close_order.set_frozen_price(price)
close_orders.append(close_order)
submit_orders = []
for order in chain(close_orders, open_orders):
if env.can_submit_order(order):
submit_orders.append(order)
env.broker.submit_order(order)
return submit_orders