RAPTOR v18.4: Исправлена отчетность, активированы выходные
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import logging
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import time
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from typing import Iterator, List
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import t_tech
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from t_tech.invest import (
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CandleInstrument,
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InvestError,
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MarketDataRequest,
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MarketDataResponse,
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SubscribeCandlesRequest,
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SubscriptionAction,
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SubscriptionInterval,
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)
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from t_tech.invest.services import Services
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from t_tech.invest.strategies.base.account_manager import AccountManager
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from t_tech.invest.strategies.base.errors import MarketDataNotAvailableError
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from t_tech.invest.strategies.base.event import DataEvent, SignalEvent
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from t_tech.invest.strategies.base.models import CandleEvent
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from t_tech.invest.strategies.base.signal import CloseSignal, OpenSignal, Signal
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from t_tech.invest.strategies.base.signal_executor_base import SignalExecutor
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from t_tech.invest.strategies.base.trader_base import Trader
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from t_tech.invest.strategies.moving_average.strategy import MovingAverageStrategy
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from t_tech.invest.strategies.moving_average.strategy_settings import (
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MovingAverageStrategySettings,
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)
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from t_tech.invest.strategies.moving_average.strategy_state import (
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MovingAverageStrategyState,
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)
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from t_tech.invest.strategies.moving_average.supervisor import (
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MovingAverageStrategySupervisor,
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)
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from t_tech.invest.utils import floor_datetime, now
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logger = logging.getLogger(__name__)
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class MovingAverageStrategyTrader(Trader):
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def __init__(
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self,
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strategy: MovingAverageStrategy,
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settings: MovingAverageStrategySettings,
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services: Services,
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state: MovingAverageStrategyState,
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signal_executor: SignalExecutor,
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account_manager: AccountManager,
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supervisor: MovingAverageStrategySupervisor,
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):
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super().__init__(strategy, services, settings)
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self._settings: MovingAverageStrategySettings = settings
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self._strategy = strategy
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self._services = services
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self._data: List[CandleEvent]
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self._market_data_stream: Iterator[MarketDataResponse]
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self._state = state
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self._signal_executor = signal_executor
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self._account_manager = account_manager
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self._supervisor = supervisor
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self._data = list(
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self._load_candles(
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(self._settings.short_period + self._settings.long_period) * 3
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)
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)
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for candle_event in self._data:
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self._supervisor.notify(self._convert_to_data_event(candle_event))
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self._strategy.fit(self._data)
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self._ensure_marginal_trade_active()
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self._subscribe()
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def _ensure_marginal_trade_active(self) -> None:
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self._account_manager.ensure_marginal_trade()
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def _subscribe(self):
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current_instrument = CandleInstrument(
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figi=self._settings.share_id,
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interval=SubscriptionInterval.SUBSCRIPTION_INTERVAL_ONE_MINUTE,
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)
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candle_subscribe_request = MarketDataRequest(
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subscribe_candles_request=SubscribeCandlesRequest(
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subscription_action=SubscriptionAction.SUBSCRIPTION_ACTION_SUBSCRIBE,
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instruments=[current_instrument],
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)
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)
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def request_iterator():
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yield candle_subscribe_request
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while True:
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time.sleep(1)
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self._market_data_stream = self._services.market_data_stream.market_data_stream(
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request_iterator()
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)
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def _is_candle_fresh(self, candle: t_tech.invest.Candle) -> bool:
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is_fresh_border = floor_datetime(
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now(), delta=self._settings.candle_interval_timedelta
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)
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logger.debug(
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"Checking if candle is fresh: candle.time=%s > is_fresh_border=%s %s)",
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candle.time,
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is_fresh_border,
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candle.time >= is_fresh_border,
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)
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return candle.time >= is_fresh_border
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@staticmethod
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def _convert_to_data_event(candle_event: CandleEvent) -> DataEvent:
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return DataEvent(candle_event=candle_event, time=candle_event.time)
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def _make_observations(self) -> None:
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while True:
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market_data_response: MarketDataResponse = next(self._market_data_stream)
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logger.debug("got market_data_response: %s", market_data_response)
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if market_data_response.candle is None:
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logger.debug("market_data_response didn't have candle")
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continue
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candle = market_data_response.candle
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logger.debug("candle extracted: %s", candle)
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candle_event = self._convert_candle(candle)
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self._strategy.observe(candle_event)
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self._supervisor.notify(self._convert_to_data_event(candle_event))
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if self._is_candle_fresh(candle):
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logger.info("Data refreshed")
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break
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def _refresh_data(self) -> None:
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logger.info("Refreshing data")
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try:
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self._make_observations()
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except StopIteration as e:
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logger.info("Fresh quotations not available")
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raise MarketDataNotAvailableError() from e
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def _filter_closing_signals(self, signals: List[Signal]) -> List[Signal]:
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return list(filter(lambda signal: isinstance(signal, CloseSignal), signals))
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def _filter_opening_signals(self, signals: List[Signal]) -> List[Signal]:
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return list(filter(lambda signal: isinstance(signal, OpenSignal), signals))
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def _execute(self, signal: Signal) -> None:
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logger.info("Trying to execute signal %s", signal)
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try:
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self._signal_executor.execute(signal) # type: ignore
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except InvestError:
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was_executed = False
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else:
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was_executed = True
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self._supervisor.notify(
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SignalEvent(signal=signal, was_executed=was_executed, time=now())
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)
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def _get_signals(self) -> List[Signal]:
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signals = list(self._strategy.predict())
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return [
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*self._filter_closing_signals(signals),
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*self._filter_opening_signals(signals),
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]
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def trade(self) -> None:
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"""Делает попытку следовать стратегии."""
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logger.info("Balance: %s", self._account_manager.get_current_balance())
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self._refresh_data()
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signals = self._get_signals()
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if signals:
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logger.info("Got signals %s", signals)
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for signal in signals:
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self._execute(signal)
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if self._state.position == 0:
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logger.info("Trade try complete")
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