def __getitem__(self, key):
if not isinstance(key, six.string_types):
raise patch_user_exc(ValueError('invalid key {} (use order_book_id please)'.format(key)))
instrument = self._data_proxy.instruments(key)
if instrument is None:
raise patch_user_exc(ValueError('invalid order book id or symbol: {}'.format(key)))
order_book_id = instrument.order_book_id
try:
return self._cache[order_book_id]
except KeyError:
try:
if not self._dt:
return BarObject(instrument, NANDict, self._dt)
if ExecutionContext.phase() == EXECUTION_PHASE.OPEN_AUCTION:
bar = self._data_proxy.get_open_auction_bar(order_book_id, self._dt)
else:
bar = self._data_proxy.get_bar(order_book_id, self._dt, self._frequency)
except PermissionError:
raise
except Exception as e:
system_log.exception(e)
raise patch_user_exc(KeyError(_(u"id_or_symbols {} does not exist").format(key)))
if bar is None:
return BarObject(instrument, NANDict, self._dt)
else:
self._cache[order_book_id] = bar
return bar
def before_trading_(self, event):
self._stage = 'before_trading'
for day_rule, time_rule, func in self._registry:
if day_rule() and time_rule():
with ExecutionContext(EXECUTION_PHASE.BEFORE_TRADING):
with ModifyExceptionFromType(EXC_TYPE.USER_EXC):
func(self.ucontext, None)
self._stage = None
def init(self):
if self._init:
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 next_bar_(self, event):
bars = event.bar_dict
self._current_minute = self._minutes_since_midnight(
self.ucontext.now.hour, self.ucontext.now.minute)
for day_rule, time_rule, func in self._registry:
if day_rule() and time_rule():
with ExecutionContext(EXECUTION_PHASE.SCHEDULED):
with ModifyExceptionFromType(EXC_TYPE.USER_EXC):
func(self.ucontext, bars)
self._last_minute = self._current_minute
def current_snapshot(id_or_symbol):
# type: (Union[str, Instrument]) -> Optional[TickObject]
"""
获得当前市场快照数据。只能在日内交易阶段调用，获取当日调用时点的市场快照数据。
市场快照数据记录了每日从开盘到当前的数据信息，可以理解为一个动态的day bar数据。
在目前分钟回测中，快照数据为当日所有分钟线累积而成，一般情况下，最后一个分钟线获取到的快照数据应当与当日的日线行情保持一致。
需要注意，在实盘模拟中，该函数返回的是调用当时的市场快照情况，所以在同一个handle_bar中不同时点调用可能返回的数据不同。
如果当日截止到调用时候对应股票没有任何成交，那么snapshot中的close, high, low, last几个价格水平都将以0表示。
:param d_or_symbol: 合约代码或简称
:example:
在handle_bar中调用该函数，假设策略当前时间是20160104 09:33:
.. code-block:: python3
:linenos:
[In]
logger.info(current_snapshot('000001.XSHE'))
[Out]
2016-01-04 09:33:00.00 INFO
Snapshot(order_book_id: '000001.XSHE', datetime: datetime.datetime(2016, 1, 4, 9, 33), open: 10.0, high: 10.025, low: 9.9667, last: 9.9917, volume: 2050320, total_turnover: 20485195, prev_close: 9.99)
"""
env = Environment.get_instance()
frequency = env.config.base.frequency
order_book_id = assure_order_book_id(id_or_symbol)
dt = env.calendar_dt
if env.config.base.run_type == RUN_TYPE.BACKTEST:
if ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING:
dt = env.data_proxy.get_previous_trading_date(
env.trading_dt.date())
return env.data_proxy.current_snapshot(order_book_id, "1d", dt)
elif ExecutionContext.phase() == EXECUTION_PHASE.AFTER_TRADING:
return env.data_proxy.current_snapshot(order_book_id, "1d", dt)
# PT、实盘直接取最新快照，忽略 frequency, dt 参数
return env.data_proxy.current_snapshot(order_book_id, frequency, dt)
def mavg(self, intervals, frequency='1d'):
if frequency == 'day':
frequency = '1d'
if frequency == 'minute':
frequency = '1m'
# copy form history
env = Environment.get_instance()
dt = env.calendar_dt
if (env.config.base.frequency == '1m' and frequency == '1d') or ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING:
# 在分钟回测获取日线数据, 应该推前一天
dt = env.data_proxy.get_previous_trading_date(env.calendar_dt.date())
bars = env.data_proxy.fast_history(self._instrument.order_book_id, intervals, frequency, 'close', dt)
return bars.mean()
def submit_order(self, order):
if order.position_effect == POSITION_EFFECT.MATCH:
raise TypeError(_("unsupported position_effect {}").format(order.position_effect))
account = self._env.get_account(order.order_book_id)
self._env.event_bus.publish_event(Event(EVENT.ORDER_PENDING_NEW, account=account, order=order))
if order.is_final():
return
if order.position_effect == POSITION_EFFECT.EXERCISE:
return self._open_exercise_orders.append((account, order))
if ExecutionContext.phase() == EXECUTION_PHASE.OPEN_AUCTION:
self._open_auction_orders.append((account, order))
else:
self._open_orders.append((account, order))
order.active()
self._env.event_bus.publish_event(Event(EVENT.ORDER_CREATION_PASS, account=account, order=order))
if self._match_immediately:
self._match()
def _history_bars(self, order_book_id, bar_count, freq, dt):
if self.fetch_data_by_api and ExecutionContext.phase() in (
EXECUTION_PHASE.BEFORE_TRADING, EXECUTION_PHASE.ON_BAR,
EXECUTION_PHASE.ON_TICK, EXECUTION_PHASE.AFTER_TRADING,
EXECUTION_PHASE.SCHEDULED):
bars = history_bars(order_book_id,
bar_count,
freq,
fields=None)
else:
bars = self.rqalpha_env.data_proxy.history_bars(
order_book_id,
bar_count,
freq,
field=[
"datetime", "open", "high", "low", "close",
"volume"
],
dt=dt)
return bars
def vwap(self, intervals, frequency='1d'):
if frequency == 'day':
frequency = '1d'
if frequency == 'minute':
frequency = '1m'
# copy form history
env = Environment.get_instance()
dt = env.calendar_dt
if (env.config.base.frequency == '1m' and frequency == '1d') or ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING:
# 在分钟回测获取日线数据, 应该推前一天
dt = env.data_proxy.get_previous_trading_date(env.calendar_dt.date())
bars = env.data_proxy.fast_history(self._instrument.order_book_id, intervals, frequency, ['close', 'volume'], dt)
sum = bars['volume'].sum()
if sum == 0:
# 全部停牌
return 0
return np.dot(bars['close'], bars['volume']) / sum
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))
restored_obj_state = persist_helper.restore(None)
check_key = ["global_vars", "user_context", "executor", "universe"]
kept_current_init_data = not any(
v for k, v in restored_obj_state.items() if k in check_key)
system_log.debug(
"restored_obj_state: {}".format(restored_obj_state))
system_log.debug(
"kept_current_init_data: {}".format(kept_current_init_data))
if kept_current_init_data:
# 未能恢复init相关数据 保留当前策略初始化变量(展示当前策略初始化日志)
log_capture.replay()
else:
user_system_log.info(_('system restored'))
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)
release_print(scope)
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:
system_log.error(traceback.format_exc())
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 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'或'1m'分别表示每日和每分钟，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] 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
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 _get_bar(self, order_book_id):
if ExecutionContext.phase() == EXECUTION_PHASE.OPEN_AUCTION:
return self._env.data_proxy.get_open_auction_bar(order_book_id, self._env.calendar_dt)
return self._env.get_bar(order_book_id)
def open_auction(self, event):
bar_dict = event.bar_dict
with ExecutionContext(EXECUTION_PHASE.OPEN_AUCTION):
with ModifyExceptionFromType(EXC_TYPE.USER_EXC):
self._open_auction(self._user_context, bar_dict)
def handle_tick(self, event):
tick = event.tick
with ExecutionContext(EXECUTION_PHASE.ON_TICK):
with ModifyExceptionFromType(EXC_TYPE.USER_EXC):
self._handle_tick(self._user_context, tick)
def handle_bar(self, event):
bar_dict = event.bar_dict
with ExecutionContext(EXECUTION_PHASE.ON_BAR):
with ModifyExceptionFromType(EXC_TYPE.USER_EXC):
self._handle_bar(self._user_context, bar_dict)
def before_trading(self, event):
with ExecutionContext(EXECUTION_PHASE.BEFORE_TRADING):
with ModifyExceptionFromType(EXC_TYPE.USER_EXC):
self._before_trading(self._user_context)
def after_trading(self, event):
with ExecutionContext(EXECUTION_PHASE.AFTER_TRADING):
with ModifyExceptionFromType(EXC_TYPE.USER_EXC):
self._after_trading(self._user_context)
def wrapped_handler(event):
with ExecutionContext(EXECUTION_PHASE.GLOBAL):
with ModifyExceptionFromType(EXC_TYPE.USER_EXC):
return handler(self._user_context, event)
