Codex
393 lines
17 KiB
Python
393 lines
17 KiB
Python
from __future__ import annotations
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from collections import deque
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from datetime import timedelta
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from decimal import Decimal, ROUND_DOWN
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from typing import Iterable
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from uuid import uuid4
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from crypto_spot_bot.bybit import BybitClient, Instrument
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from crypto_spot_bot.config import Settings
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from crypto_spot_bot.models import Position, Signal, Ticker, Trade, utc_now
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from crypto_spot_bot.storage import Storage
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class BrokerError(RuntimeError):
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pass
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def _round_step(value: float, step: float) -> float:
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if step <= 0:
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return value
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value_decimal = Decimal(str(value))
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step_decimal = Decimal(str(step))
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rounded = (value_decimal / step_decimal).to_integral_value(rounding=ROUND_DOWN)
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return float(rounded * step_decimal)
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class PaperBroker:
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def __init__(self, settings: Settings, storage: Storage):
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self.settings = settings
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self.storage = storage
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self.positions = storage.open_positions()
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self.cash = float(storage.get_runtime("paper_cash", settings.starting_balance_usdt))
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self.peak_equity = float(storage.get_runtime("peak_equity", settings.starting_balance_usdt))
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self._entry_timestamps = deque()
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def open_positions(self) -> list[Position]:
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return list(self.positions)
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def positions_for_symbol(self, symbol: str) -> list[Position]:
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return [position for position in self.positions if position.symbol == symbol]
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def exposure(self) -> float:
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return sum(position.notional_usdt for position in self.positions)
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def symbol_exposure(self, symbol: str) -> float:
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return sum(position.notional_usdt for position in self.positions_for_symbol(symbol))
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def equity(self, prices: dict[str, float]) -> float:
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value = self.cash
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for position in self.positions:
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value += position.mark_price(prices.get(position.symbol, position.entry_price))
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return value
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def mark_equity(self, prices: dict[str, float]) -> dict[str, float]:
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state = self.account_state(prices)
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equity = state["equity"]
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self.peak_equity = max(self.peak_equity, equity)
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state["drawdown"] = max(0.0, self.peak_equity - equity)
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self.storage.set_runtime("paper_cash", self.cash)
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self.storage.set_runtime("peak_equity", self.peak_equity)
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self.storage.insert_equity(equity, self.cash, self.exposure(), state["drawdown"])
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return state
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def account_state(self, prices: dict[str, float]) -> dict[str, float]:
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equity = self.equity(prices)
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return {
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"equity": equity,
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"cash": self.cash,
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"exposure": self.exposure(),
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"drawdown": max(0.0, self.peak_equity - equity),
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}
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def update_highs(self, tickers: dict[str, Ticker]) -> None:
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for position in self.positions:
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ticker = tickers.get(position.symbol)
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if not ticker:
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continue
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price = ticker.last_price
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if price > position.highest_price:
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position.highest_price = price
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if position.id is not None:
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self.storage.update_position_highest(position.id, price)
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def can_open(
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self,
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symbol: str,
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prices: dict[str, float],
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requested_notional: float | None = None,
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) -> tuple[bool, str]:
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if not self._entry_rate_limit_allows():
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return False, "достигнут лимит новых входов в минуту"
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if len(self.positions) >= self.settings.max_open_positions:
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return False, "достигнут общий лимит открытых позиций"
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if self.settings.strategy_mode == "trend_macd" and len(self.positions_for_symbol(symbol)) >= 1:
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return False, "DCA/усреднение отключено: позиция по паре уже открыта"
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dynamic_pair_limit = _symbol_position_limit(self.settings)
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if len(self.positions_for_symbol(symbol)) >= dynamic_pair_limit:
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return False, "достигнут лимит позиций по паре"
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requested = requested_notional if requested_notional is not None else self.settings.min_position_usdt
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symbol_room = max(0.0, self.settings.max_symbol_exposure_usdt - self.symbol_exposure(symbol))
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if symbol_room < min(requested, self.settings.min_position_usdt):
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return False, "достигнут лимит экспозиции по паре"
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if self.cash <= self.settings.min_cash_reserve_usdt:
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return False, "недостаточно свободного USDT после резерва"
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if self.exposure() >= self.settings.max_total_exposure_usdt:
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return False, "достигнут лимит общей экспозиции"
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equity_state = self.mark_equity(prices)
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if equity_state["drawdown"] >= self.settings.max_daily_drawdown_usdt:
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return False, "достигнут лимит просадки"
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return True, "ok"
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def buy(
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self,
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signal: Signal,
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ticker: Ticker,
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instrument: Instrument | None,
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prices: dict[str, float],
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) -> Position | None:
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requested_notional = self._signal_notional(signal)
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allowed, reason = self.can_open(ticker.symbol, prices, requested_notional)
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if not allowed:
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self.storage.event(f"{ticker.symbol}: покупка пропущена, {reason}", "WARN")
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return None
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return self._record_buy(signal, ticker, instrument, "демо-покупка")
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def _record_buy(
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self,
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signal: Signal,
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ticker: Ticker,
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instrument: Instrument | None,
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event_label: str,
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) -> Position | None:
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fill_price = self._buy_price(ticker)
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minimum_budget = self._minimum_entry_budget(instrument)
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notional = self._entry_budget(signal, ticker, minimum_notional=minimum_budget)
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if notional < max(self.settings.min_position_usdt, minimum_budget):
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self.storage.event(f"{ticker.symbol}: покупка пропущена, adaptive-лимит экспозиции исчерпан", "WARN")
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return None
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notional = notional / (1 + self.settings.taker_fee_rate)
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qty = _round_step(notional / fill_price, instrument.qty_step if instrument else 0)
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if instrument and qty < instrument.min_order_qty:
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self.storage.event(f"{ticker.symbol}: количество ниже minOrderQty Bybit", "WARN")
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return None
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executed_notional = qty * fill_price
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if instrument and executed_notional < instrument.min_notional_value:
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self.storage.event(f"{ticker.symbol}: сумма ниже minNotionalValue Bybit", "WARN")
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return None
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fee = executed_notional * self.settings.taker_fee_rate
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if executed_notional + fee > self.cash:
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self.storage.event(f"{ticker.symbol}: недостаточно cash для комиссии", "WARN")
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return None
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stop_loss_percent = self._signal_percent(signal, "stop_loss_percent", self.settings.stop_loss_percent, 0.003, 0.08)
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take_profit_percent = self._signal_percent(
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signal, "take_profit_percent", self.settings.take_profit_percent, 0.003, 0.20
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)
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position = Position(
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id=None,
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symbol=ticker.symbol,
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qty=qty,
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entry_price=fill_price,
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notional_usdt=executed_notional,
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entry_fee_usdt=fee,
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stop_loss=fill_price * (1 - stop_loss_percent),
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take_profit=fill_price * (1 + take_profit_percent),
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highest_price=fill_price,
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entry_reason=signal.reason,
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entry_confidence=signal.confidence,
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entry_pattern=str(signal.diagnostics.get("pattern", {}).get("label", "")),
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entry_diagnostics=signal.diagnostics,
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)
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position.id = self.storage.insert_position(position)
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self.positions.append(position)
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self._record_entry_timestamp()
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self.cash -= executed_notional + fee
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self.storage.set_runtime("paper_cash", self.cash)
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self.storage.insert_trade(
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Trade(
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id=None,
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symbol=ticker.symbol,
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side="BUY",
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qty=qty,
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entry_price=fill_price,
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fee_usdt=fee,
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net_pnl=-fee,
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reason=signal.reason,
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entry_pattern=position.entry_pattern,
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entry_confidence=position.entry_confidence,
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entry_diagnostics=position.entry_diagnostics,
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opened_at=position.opened_at,
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)
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)
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self.storage.event(
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f"{ticker.symbol}: {event_label} кол-во={qty:.8f} цена={fill_price:.8f} сумма={executed_notional:.2f} уверенность={signal.confidence:.2f}"
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)
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return position
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def sell(self, position: Position, ticker: Ticker, reason: str) -> Trade:
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return self._record_sell(position, ticker, reason, "демо-продажа")
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def _record_sell(
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self,
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position: Position,
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ticker: Ticker,
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reason: str,
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event_label: str,
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) -> Trade:
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fill_price = self._sell_price(ticker)
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exit_notional = position.qty * fill_price
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exit_fee = exit_notional * self.settings.taker_fee_rate
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gross_pnl = (fill_price - position.entry_price) * position.qty
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net_pnl = gross_pnl - position.entry_fee_usdt - exit_fee
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self.cash += exit_notional - exit_fee
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if position.id is not None:
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self.storage.close_position(position.id)
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self.positions = [item for item in self.positions if item.id != position.id]
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self.storage.set_runtime("paper_cash", self.cash)
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trade = Trade(
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id=None,
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symbol=position.symbol,
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side="SELL",
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qty=position.qty,
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entry_price=position.entry_price,
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exit_price=fill_price,
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gross_pnl=gross_pnl,
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fee_usdt=position.entry_fee_usdt + exit_fee,
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net_pnl=net_pnl,
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reason=reason,
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entry_pattern=position.entry_pattern,
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entry_confidence=position.entry_confidence,
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entry_diagnostics=position.entry_diagnostics,
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opened_at=position.opened_at,
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closed_at=utc_now(),
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)
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trade.id = self.storage.insert_trade(trade)
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self.storage.event(
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f"{position.symbol}: {event_label} кол-во={position.qty:.8f} цена={fill_price:.8f} итог={net_pnl:.4f} причина={reason}"
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)
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return trade
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def _buy_price(self, ticker: Ticker) -> float:
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base = ticker.ask if ticker.ask > 0 else ticker.last_price
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return base * (1 + self.settings.slippage_rate)
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def _sell_price(self, ticker: Ticker) -> float:
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base = ticker.bid if ticker.bid > 0 else ticker.last_price
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return base * (1 - self.settings.slippage_rate)
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def _signal_notional(self, signal: Signal) -> float:
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raw = signal.diagnostics.get("position_notional_usdt", self.settings.max_position_usdt)
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try:
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value = float(raw)
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except (TypeError, ValueError):
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value = self.settings.max_position_usdt
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low = max(0.0, self.settings.min_position_usdt)
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high = max(low, self.settings.max_position_usdt)
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return max(low, min(high, value))
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def _signal_percent(self, signal: Signal, key: str, default: float, low: float, high: float) -> float:
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rules = signal.diagnostics.get("adaptive_rules") or {}
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raw = signal.diagnostics.get(key, rules.get(key, default) if isinstance(rules, dict) else default)
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try:
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value = float(raw)
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except (TypeError, ValueError):
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value = default
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return max(low, min(high, value))
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def _minimum_entry_budget(self, instrument: Instrument | None) -> float:
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minimum = max(0.0, self.settings.min_position_usdt)
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if instrument and instrument.min_notional_value > 0:
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exchange_minimum = instrument.min_notional_value * (1 + self.settings.taker_fee_rate) * 1.002 + 0.01
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minimum = max(minimum, exchange_minimum)
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return minimum
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def _entry_budget(
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self,
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signal: Signal,
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ticker: Ticker,
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extra_cap: float | None = None,
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minimum_notional: float = 0.0,
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) -> float:
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available = max(0.0, self.cash - self.settings.min_cash_reserve_usdt)
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rules = signal.diagnostics.get("adaptive_rules") or {}
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target_total = self._adaptive_cap(rules, "target_total_exposure_usdt", self.settings.max_total_exposure_usdt)
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target_symbol = self._adaptive_cap(rules, "target_symbol_exposure_usdt", self.settings.max_symbol_exposure_usdt)
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exposure_room = max(0.0, target_total - self.exposure())
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symbol_room = max(0.0, target_symbol - self.symbol_exposure(ticker.symbol))
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requested = min(
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max(self._signal_notional(signal), minimum_notional),
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max(0.0, self.settings.max_position_usdt),
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)
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caps = [requested, available, exposure_room, symbol_room]
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if extra_cap is not None:
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caps.append(max(0.0, extra_cap))
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return max(0.0, min(caps))
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def _adaptive_cap(self, rules: object, key: str, default: float) -> float:
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if not isinstance(rules, dict):
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return default
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try:
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value = float(rules.get(key, default))
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except (TypeError, ValueError):
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value = default
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return max(0.0, min(default, value))
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def _entry_rate_limit_allows(self) -> bool:
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limit = self.settings.max_entries_per_minute
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if limit <= 0:
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return True
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now = utc_now()
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cutoff = now - timedelta(seconds=60)
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while self._entry_timestamps and self._entry_timestamps[0] < cutoff:
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self._entry_timestamps.popleft()
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return len(self._entry_timestamps) < limit
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def _record_entry_timestamp(self) -> None:
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if self.settings.max_entries_per_minute <= 0:
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return
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self._entry_timestamps.append(utc_now())
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class LiveBroker(PaperBroker):
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def __init__(self, settings: Settings, storage: Storage, client: BybitClient):
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super().__init__(settings, storage)
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if not settings.live_ready:
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raise BrokerError("Live mode is not unlocked by settings")
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self.client = client
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def buy(
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self,
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signal: Signal,
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ticker: Ticker,
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instrument: Instrument | None,
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prices: dict[str, float],
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) -> Position | None:
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minimum_budget = self._minimum_entry_budget(instrument)
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requested_notional = min(
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max(self._signal_notional(signal), minimum_budget),
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self.settings.live_order_max_usdt,
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)
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allowed, reason = self.can_open(ticker.symbol, prices, requested_notional)
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if not allowed:
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self.storage.event(f"{ticker.symbol}: live BUY пропущен, {reason}", "WARN")
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return None
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budget = self._entry_budget(
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signal,
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ticker,
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self.settings.live_order_max_usdt,
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minimum_notional=minimum_budget,
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)
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if budget < max(self.settings.min_position_usdt, minimum_budget):
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self.storage.event(f"{ticker.symbol}: live BUY skipped, adjusted budget below minimum", "WARN")
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return None
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signal.diagnostics["position_notional_usdt"] = budget
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notional = budget / (1 + self.settings.taker_fee_rate)
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response = self.client.place_spot_market_order(
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symbol=ticker.symbol,
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side="Buy",
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qty=notional,
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market_unit="quoteCoin",
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order_link_id=f"tb-buy-{uuid4().hex[:18]}",
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)
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self.storage.event(f"{ticker.symbol}: реальная покупка отправлена orderId={response.get('orderId')}")
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return self._record_buy(signal, ticker, instrument, "реальная покупка, локальная запись")
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def sell(self, position: Position, ticker: Ticker, reason: str) -> Trade:
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response = self.client.place_spot_market_order(
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symbol=position.symbol,
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side="Sell",
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qty=position.qty,
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market_unit="baseCoin",
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order_link_id=f"tb-sell-{uuid4().hex[:18]}",
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)
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self.storage.event(
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f"{position.symbol}: реальная продажа отправлена orderId={response.get('orderId')} причина={reason}"
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)
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return self._record_sell(position, ticker, reason, "реальная продажа, локальная запись")
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def prices_from_tickers(tickers: Iterable[Ticker]) -> dict[str, float]:
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return {ticker.symbol: ticker.last_price for ticker in tickers}
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def _symbol_position_limit(settings: Settings) -> int:
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configured_limit = max(1, settings.max_positions_per_symbol)
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exposure_based_limit = max(
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1,
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int(settings.max_symbol_exposure_usdt // max(settings.min_position_usdt, 0.01)),
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)
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return min(configured_limit, exposure_based_limit)
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