2022-05-08 15:45:20 +00:00
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"""
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This module contains the class to persist trades into SQLite
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"""
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import logging
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2022-10-16 11:34:58 +00:00
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from collections import defaultdict
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2022-05-08 15:45:20 +00:00
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from datetime import datetime, timedelta, timezone
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2022-07-31 12:19:04 +00:00
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from math import isclose
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2023-03-16 05:44:53 +00:00
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from typing import Any, ClassVar, Dict, List, Optional, Sequence, cast
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2022-05-08 15:45:20 +00:00
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2023-03-15 20:09:25 +00:00
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from sqlalchemy import (Enum, Float, ForeignKey, Integer, ScalarResult, Select, String,
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UniqueConstraint, desc, func, select)
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2023-03-16 17:07:22 +00:00
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from sqlalchemy.orm import Mapped, lazyload, mapped_column, relationship
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2022-05-08 15:45:20 +00:00
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2022-07-31 12:19:04 +00:00
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from freqtrade.constants import (DATETIME_PRINT_FORMAT, MATH_CLOSE_PREC, NON_OPEN_EXCHANGE_STATES,
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BuySell, LongShort)
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2022-05-08 15:45:20 +00:00
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from freqtrade.enums import ExitType, TradingMode
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from freqtrade.exceptions import DependencyException, OperationalException
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2022-08-25 05:08:22 +00:00
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from freqtrade.exchange import amount_to_contract_precision, price_to_precision
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2022-05-08 15:45:20 +00:00
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from freqtrade.leverage import interest
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2023-02-28 06:03:22 +00:00
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from freqtrade.persistence.base import ModelBase, SessionType
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2022-08-10 18:31:03 +00:00
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from freqtrade.util import FtPrecise
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2022-05-08 15:45:20 +00:00
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logger = logging.getLogger(__name__)
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2023-02-16 07:04:45 +00:00
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class Order(ModelBase):
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2022-05-08 15:45:20 +00:00
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"""
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Order database model
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Keeps a record of all orders placed on the exchange
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One to many relationship with Trades:
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- One trade can have many orders
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- One Order can only be associated with one Trade
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Mirrors CCXT Order structure
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"""
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__tablename__ = 'orders'
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2023-03-15 20:12:06 +00:00
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session: ClassVar[SessionType]
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2023-02-20 19:00:01 +00:00
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2022-05-08 15:45:20 +00:00
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# Uniqueness should be ensured over pair, order_id
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# its likely that order_id is unique per Pair on some exchanges.
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__table_args__ = (UniqueConstraint('ft_pair', 'order_id', name="_order_pair_order_id"),)
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2023-02-16 07:17:56 +00:00
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id: Mapped[int] = mapped_column(Integer, primary_key=True)
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ft_trade_id: Mapped[int] = mapped_column(Integer, ForeignKey('trades.id'), index=True)
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2022-05-08 15:45:20 +00:00
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2023-02-16 07:17:56 +00:00
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trade: Mapped[List["Trade"]] = relationship("Trade", back_populates="orders")
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2022-05-08 15:45:20 +00:00
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# order_side can only be 'buy', 'sell' or 'stoploss'
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2023-02-16 07:17:56 +00:00
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ft_order_side: Mapped[str] = mapped_column(String(25), nullable=False)
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ft_pair: Mapped[str] = mapped_column(String(25), nullable=False)
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ft_is_open: Mapped[bool] = mapped_column(nullable=False, default=True, index=True)
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ft_amount: Mapped[float] = mapped_column(Float(), nullable=False)
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ft_price: Mapped[float] = mapped_column(Float(), nullable=False)
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2023-02-16 07:07:08 +00:00
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2023-02-16 07:17:56 +00:00
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order_id: Mapped[str] = mapped_column(String(255), nullable=False, index=True)
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status: Mapped[Optional[str]] = mapped_column(String(255), nullable=True)
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symbol: Mapped[Optional[str]] = mapped_column(String(25), nullable=True)
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2023-02-14 10:35:18 +00:00
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# TODO: type: order_type type is Optional[str]
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2023-02-16 07:17:56 +00:00
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order_type: Mapped[str] = mapped_column(String(50), nullable=True)
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side: Mapped[str] = mapped_column(String(25), nullable=True)
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price: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
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average: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
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amount: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
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filled: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
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remaining: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
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cost: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
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stop_price: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
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order_date: Mapped[datetime] = mapped_column(nullable=True, default=datetime.utcnow)
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order_filled_date: Mapped[Optional[datetime]] = mapped_column(nullable=True)
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order_update_date: Mapped[Optional[datetime]] = mapped_column(nullable=True)
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funding_fee: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
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2023-02-16 07:07:08 +00:00
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2023-02-16 07:17:56 +00:00
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ft_fee_base: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
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2022-05-08 15:45:20 +00:00
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@property
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def order_date_utc(self) -> datetime:
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""" Order-date with UTC timezoneinfo"""
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return self.order_date.replace(tzinfo=timezone.utc)
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2022-09-02 04:51:30 +00:00
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@property
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def order_filled_utc(self) -> Optional[datetime]:
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""" last order-date with UTC timezoneinfo"""
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return (
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self.order_filled_date.replace(tzinfo=timezone.utc) if self.order_filled_date else None
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)
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2023-01-08 12:55:09 +00:00
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@property
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def safe_amount(self) -> float:
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return self.amount or self.ft_amount
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2022-05-08 15:45:20 +00:00
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@property
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def safe_price(self) -> float:
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2023-01-08 12:55:09 +00:00
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return self.average or self.price or self.stop_price or self.ft_price
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2022-05-08 15:45:20 +00:00
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@property
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def safe_filled(self) -> float:
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2022-06-13 13:24:27 +00:00
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return self.filled if self.filled is not None else self.amount or 0.0
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2022-05-08 15:45:20 +00:00
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2023-03-02 05:23:01 +00:00
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@property
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def safe_cost(self) -> float:
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return self.cost or 0.0
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2022-11-17 18:58:46 +00:00
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@property
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def safe_remaining(self) -> float:
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return (
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self.remaining if self.remaining is not None else
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2023-01-08 12:55:09 +00:00
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self.safe_amount - (self.filled or 0.0)
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2022-11-17 18:58:46 +00:00
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)
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2022-05-08 15:45:20 +00:00
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@property
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def safe_fee_base(self) -> float:
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return self.ft_fee_base or 0.0
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@property
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def safe_amount_after_fee(self) -> float:
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return self.safe_filled - self.safe_fee_base
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def __repr__(self):
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2023-03-03 17:12:41 +00:00
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return (f"Order(id={self.id}, order_id={self.order_id}, trade_id={self.ft_trade_id}, "
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f"side={self.side}, filled={self.safe_filled}, price={self.safe_price}, "
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f"order_type={self.order_type}, status={self.status})")
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2022-05-08 15:45:20 +00:00
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def update_from_ccxt_object(self, order):
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"""
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Update Order from ccxt response
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Only updates if fields are available from ccxt -
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"""
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if self.order_id != str(order['id']):
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raise DependencyException("Order-id's don't match")
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self.status = order.get('status', self.status)
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self.symbol = order.get('symbol', self.symbol)
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self.order_type = order.get('type', self.order_type)
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self.side = order.get('side', self.side)
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self.price = order.get('price', self.price)
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self.amount = order.get('amount', self.amount)
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self.filled = order.get('filled', self.filled)
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self.average = order.get('average', self.average)
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self.remaining = order.get('remaining', self.remaining)
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self.cost = order.get('cost', self.cost)
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2022-06-22 04:30:30 +00:00
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self.stop_price = order.get('stopPrice', self.stop_price)
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2022-05-08 15:45:20 +00:00
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if 'timestamp' in order and order['timestamp'] is not None:
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self.order_date = datetime.fromtimestamp(order['timestamp'] / 1000, tz=timezone.utc)
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self.ft_is_open = True
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if self.status in NON_OPEN_EXCHANGE_STATES:
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self.ft_is_open = False
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2022-09-03 08:06:23 +00:00
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if self.trade:
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# Assign funding fee up to this point
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# (represents the funding fee since the last order)
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self.funding_fee = self.trade.funding_fees
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2023-01-27 19:21:29 +00:00
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if (order.get('filled', 0.0) or 0.0) > 0 and not self.order_filled_date:
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2022-05-08 15:45:20 +00:00
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self.order_filled_date = datetime.now(timezone.utc)
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self.order_update_date = datetime.now(timezone.utc)
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2022-05-19 04:42:38 +00:00
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def to_ccxt_object(self) -> Dict[str, Any]:
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2023-02-28 06:27:01 +00:00
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order: Dict[str, Any] = {
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2022-05-19 04:42:38 +00:00
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'id': self.order_id,
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'symbol': self.ft_pair,
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'price': self.price,
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'average': self.average,
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'amount': self.amount,
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'cost': self.cost,
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'type': self.order_type,
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'side': self.ft_order_side,
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'filled': self.filled,
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'remaining': self.remaining,
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2022-06-22 04:30:30 +00:00
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'stopPrice': self.stop_price,
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2022-05-19 17:29:39 +00:00
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'datetime': self.order_date_utc.strftime('%Y-%m-%dT%H:%M:%S.%f'),
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2022-05-19 04:42:38 +00:00
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'timestamp': int(self.order_date_utc.timestamp() * 1000),
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'status': self.status,
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'fee': None,
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'info': {},
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}
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2023-02-18 18:25:11 +00:00
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if self.ft_order_side == 'stoploss':
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order['ft_order_type'] = 'stoploss'
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return order
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2022-05-19 04:42:38 +00:00
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2022-05-26 05:11:43 +00:00
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def to_json(self, entry_side: str, minified: bool = False) -> Dict[str, Any]:
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resp = {
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2023-01-31 19:38:18 +00:00
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'amount': self.safe_amount,
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2022-05-08 15:45:20 +00:00
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'safe_price': self.safe_price,
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'ft_order_side': self.ft_order_side,
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'order_filled_timestamp': int(self.order_filled_date.replace(
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tzinfo=timezone.utc).timestamp() * 1000) if self.order_filled_date else None,
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'ft_is_entry': self.ft_order_side == entry_side,
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}
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2022-05-26 05:11:43 +00:00
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if not minified:
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resp.update({
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'pair': self.ft_pair,
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'order_id': self.order_id,
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'status': self.status,
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'average': round(self.average, 8) if self.average else 0,
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'cost': self.cost if self.cost else 0,
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'filled': self.filled,
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'is_open': self.ft_is_open,
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'order_date': self.order_date.strftime(DATETIME_PRINT_FORMAT)
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if self.order_date else None,
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'order_timestamp': int(self.order_date.replace(
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tzinfo=timezone.utc).timestamp() * 1000) if self.order_date else None,
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'order_filled_date': self.order_filled_date.strftime(DATETIME_PRINT_FORMAT)
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if self.order_filled_date else None,
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'order_type': self.order_type,
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'price': self.price,
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'remaining': self.remaining,
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})
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return resp
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2022-05-08 15:45:20 +00:00
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def close_bt_order(self, close_date: datetime, trade: 'LocalTrade'):
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self.order_filled_date = close_date
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self.filled = self.amount
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2022-04-29 04:53:30 +00:00
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self.remaining = 0
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2022-05-08 15:45:20 +00:00
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self.status = 'closed'
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self.ft_is_open = False
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2022-09-02 04:51:30 +00:00
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# Assign funding fees to Order.
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# Assumes backtesting will use date_last_filled_utc to calculate future funding fees.
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self.funding_fee = trade.funding_fees
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2023-02-16 07:27:57 +00:00
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if (self.ft_order_side == trade.entry_side and self.price):
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2022-05-08 15:45:20 +00:00
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trade.open_rate = self.price
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2022-07-31 12:19:04 +00:00
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trade.recalc_trade_from_orders()
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2022-05-15 13:30:57 +00:00
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trade.adjust_stop_loss(trade.open_rate, trade.stop_loss_pct, refresh=True)
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2022-05-08 15:45:20 +00:00
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@staticmethod
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def update_orders(orders: List['Order'], order: Dict[str, Any]):
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"""
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Get all non-closed orders - useful when trying to batch-update orders
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"""
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if not isinstance(order, dict):
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logger.warning(f"{order} is not a valid response object.")
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return
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filtered_orders = [o for o in orders if o.order_id == order.get('id')]
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if filtered_orders:
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oobj = filtered_orders[0]
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oobj.update_from_ccxt_object(order)
|
2022-08-06 13:08:13 +00:00
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Trade.commit()
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2022-05-08 15:45:20 +00:00
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else:
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logger.warning(f"Did not find order for {order}.")
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@staticmethod
|
2023-01-08 12:53:08 +00:00
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def parse_from_ccxt_object(
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order: Dict[str, Any], pair: str, side: str,
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amount: Optional[float] = None, price: Optional[float] = None) -> 'Order':
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2022-05-08 15:45:20 +00:00
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"""
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Parse an order from a ccxt object and return a new order Object.
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2023-01-08 12:53:08 +00:00
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Optional support for overriding amount and price is only used for test simplification.
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2022-05-08 15:45:20 +00:00
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"""
|
2023-01-08 12:53:08 +00:00
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o = Order(
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order_id=str(order['id']),
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ft_order_side=side,
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ft_pair=pair,
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ft_amount=amount if amount else order['amount'],
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ft_price=price if price else order['price'],
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)
|
2022-05-08 15:45:20 +00:00
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o.update_from_ccxt_object(order)
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return o
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@staticmethod
|
2023-03-16 05:44:53 +00:00
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def get_open_orders() -> Sequence['Order']:
|
2022-05-08 15:45:20 +00:00
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"""
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Retrieve open orders from the database
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:return: List of open orders
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"""
|
2023-03-16 05:44:53 +00:00
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|
return Order.session.scalars(select(Order).filter(Order.ft_is_open.is_(True))).all()
|
2022-05-08 15:45:20 +00:00
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|
2022-05-19 04:42:38 +00:00
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|
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@staticmethod
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def order_by_id(order_id: str) -> Optional['Order']:
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"""
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|
Retrieve order based on order_id
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|
:return: Order or None
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"""
|
2023-03-16 05:44:53 +00:00
|
|
|
return Order.session.scalars(select(Order).filter(Order.order_id == order_id)).first()
|
2022-05-19 04:42:38 +00:00
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|
|
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
class LocalTrade():
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"""
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|
|
Trade database model.
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|
Used in backtesting - must be aligned to Trade model!
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|
"""
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|
|
use_db: bool = False
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|
|
# Trades container for backtesting
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|
|
trades: List['LocalTrade'] = []
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|
trades_open: List['LocalTrade'] = []
|
2022-10-16 11:34:58 +00:00
|
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|
# Copy of trades_open - but indexed by pair
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|
|
bt_trades_open_pp: Dict[str, List['LocalTrade']] = defaultdict(list)
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|
bt_open_open_trade_count: int = 0
|
2022-05-08 15:45:20 +00:00
|
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total_profit: float = 0
|
2023-03-01 18:48:15 +00:00
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|
realized_profit: float = 0
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id: int = 0
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orders: List[Order] = []
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exchange: str = ''
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pair: str = ''
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base_currency: Optional[str] = ''
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stake_currency: Optional[str] = ''
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is_open: bool = True
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fee_open: float = 0.0
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fee_open_cost: Optional[float] = None
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fee_open_currency: Optional[str] = ''
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fee_close: Optional[float] = 0.0
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fee_close_cost: Optional[float] = None
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fee_close_currency: Optional[str] = ''
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open_rate: float = 0.0
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open_rate_requested: Optional[float] = None
|
2022-05-08 15:45:20 +00:00
|
|
|
# open_trade_value - calculated via _calc_open_trade_value
|
2023-03-01 18:48:15 +00:00
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open_trade_value: float = 0.0
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close_rate: Optional[float] = None
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close_rate_requested: Optional[float] = None
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close_profit: Optional[float] = None
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close_profit_abs: Optional[float] = None
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stake_amount: float = 0.0
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max_stake_amount: Optional[float] = 0.0
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amount: float = 0.0
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amount_requested: Optional[float] = None
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open_date: datetime
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|
close_date: Optional[datetime] = None
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open_order_id: Optional[str] = None
|
2022-05-08 15:45:20 +00:00
|
|
|
# absolute value of the stop loss
|
2023-03-01 18:48:15 +00:00
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|
stop_loss: float = 0.0
|
2022-05-08 15:45:20 +00:00
|
|
|
# percentage value of the stop loss
|
2023-03-01 18:48:15 +00:00
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|
stop_loss_pct: Optional[float] = 0.0
|
2022-05-08 15:45:20 +00:00
|
|
|
# absolute value of the initial stop loss
|
2023-03-01 18:48:15 +00:00
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|
|
initial_stop_loss: Optional[float] = 0.0
|
2022-05-08 15:45:20 +00:00
|
|
|
# percentage value of the initial stop loss
|
2023-03-01 18:48:15 +00:00
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|
initial_stop_loss_pct: Optional[float] = None
|
2022-05-08 15:45:20 +00:00
|
|
|
# stoploss order id which is on exchange
|
2023-03-01 18:48:15 +00:00
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|
stoploss_order_id: Optional[str] = None
|
2022-05-08 15:45:20 +00:00
|
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|
# last update time of the stoploss order on exchange
|
2023-03-01 18:48:15 +00:00
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|
|
stoploss_last_update: Optional[datetime] = None
|
2022-05-08 15:45:20 +00:00
|
|
|
# absolute value of the highest reached price
|
2023-03-01 18:48:15 +00:00
|
|
|
max_rate: Optional[float] = None
|
2022-05-08 15:45:20 +00:00
|
|
|
# Lowest price reached
|
2023-03-01 18:48:15 +00:00
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|
min_rate: Optional[float] = None
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exit_reason: Optional[str] = ''
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exit_order_status: Optional[str] = ''
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strategy: Optional[str] = ''
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|
enter_tag: Optional[str] = None
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|
timeframe: Optional[int] = None
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|
trading_mode: TradingMode = TradingMode.SPOT
|
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|
amount_precision: Optional[float] = None
|
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|
price_precision: Optional[float] = None
|
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|
precision_mode: Optional[int] = None
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|
contract_size: Optional[float] = None
|
2022-05-08 15:45:20 +00:00
|
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|
|
# Leverage trading properties
|
2023-03-01 18:48:15 +00:00
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|
|
liquidation_price: Optional[float] = None
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|
|
is_short: bool = False
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|
|
leverage: float = 1.0
|
2022-05-08 15:45:20 +00:00
|
|
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|
|
# Margin trading properties
|
2023-03-01 18:48:15 +00:00
|
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|
interest_rate: float = 0.0
|
2022-05-08 15:45:20 +00:00
|
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|
|
# Futures properties
|
2023-03-01 18:48:15 +00:00
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|
|
funding_fees: Optional[float] = None
|
2022-05-08 15:45:20 +00:00
|
|
|
|
2022-07-30 06:12:48 +00:00
|
|
|
@property
|
|
|
|
def stoploss_or_liquidation(self) -> float:
|
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|
|
if self.liquidation_price:
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|
|
if self.is_short:
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|
return min(self.stop_loss, self.liquidation_price)
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|
else:
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|
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|
return max(self.stop_loss, self.liquidation_price)
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|
|
|
|
return self.stop_loss
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|
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|
2022-05-08 15:45:20 +00:00
|
|
|
@property
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|
|
|
def buy_tag(self) -> Optional[str]:
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|
|
"""
|
|
|
|
Compatibility between buy_tag (old) and enter_tag (new)
|
|
|
|
Consider buy_tag deprecated
|
|
|
|
"""
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|
|
return self.enter_tag
|
|
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|
|
|
@property
|
|
|
|
def has_no_leverage(self) -> bool:
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|
|
"""Returns true if this is a non-leverage, non-short trade"""
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|
|
return ((self.leverage == 1.0 or self.leverage is None) and not self.is_short)
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|
|
|
|
|
@property
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|
|
|
def borrowed(self) -> float:
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|
|
"""
|
|
|
|
The amount of currency borrowed from the exchange for leverage trades
|
|
|
|
If a long trade, the amount is in base currency
|
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|
|
If a short trade, the amount is in the other currency being traded
|
|
|
|
"""
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|
|
if self.has_no_leverage:
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|
return 0.0
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|
|
elif not self.is_short:
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|
return (self.amount * self.open_rate) * ((self.leverage - 1) / self.leverage)
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|
else:
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|
|
return self.amount
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|
|
|
2022-09-02 04:51:30 +00:00
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|
|
@property
|
2022-09-03 08:06:23 +00:00
|
|
|
def date_last_filled_utc(self) -> datetime:
|
2022-09-02 04:51:30 +00:00
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|
""" Date of the last filled order"""
|
2022-09-03 08:06:23 +00:00
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|
|
orders = self.select_filled_orders()
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|
if not orders:
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|
|
return self.open_date_utc
|
2022-09-03 17:34:38 +00:00
|
|
|
return max([self.open_date_utc,
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|
|
|
max(o.order_filled_utc for o in orders if o.order_filled_utc)])
|
2022-09-02 04:51:30 +00:00
|
|
|
|
2022-05-08 15:45:20 +00:00
|
|
|
@property
|
|
|
|
def open_date_utc(self):
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|
|
return self.open_date.replace(tzinfo=timezone.utc)
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|
|
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|
2022-09-17 15:07:47 +00:00
|
|
|
@property
|
|
|
|
def stoploss_last_update_utc(self):
|
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|
|
if self.stoploss_last_update:
|
|
|
|
return self.stoploss_last_update.replace(tzinfo=timezone.utc)
|
|
|
|
return None
|
|
|
|
|
2022-05-08 15:45:20 +00:00
|
|
|
@property
|
|
|
|
def close_date_utc(self):
|
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|
|
return self.close_date.replace(tzinfo=timezone.utc)
|
|
|
|
|
|
|
|
@property
|
|
|
|
def entry_side(self) -> str:
|
|
|
|
if self.is_short:
|
|
|
|
return "sell"
|
|
|
|
else:
|
|
|
|
return "buy"
|
|
|
|
|
|
|
|
@property
|
|
|
|
def exit_side(self) -> BuySell:
|
|
|
|
if self.is_short:
|
|
|
|
return "buy"
|
|
|
|
else:
|
|
|
|
return "sell"
|
|
|
|
|
|
|
|
@property
|
|
|
|
def trade_direction(self) -> LongShort:
|
|
|
|
if self.is_short:
|
|
|
|
return "short"
|
|
|
|
else:
|
|
|
|
return "long"
|
|
|
|
|
|
|
|
@property
|
|
|
|
def safe_base_currency(self) -> str:
|
|
|
|
"""
|
|
|
|
Compatibility layer for asset - which can be empty for old trades.
|
|
|
|
"""
|
|
|
|
try:
|
|
|
|
return self.base_currency or self.pair.split('/')[0]
|
|
|
|
except IndexError:
|
|
|
|
return ''
|
|
|
|
|
|
|
|
@property
|
|
|
|
def safe_quote_currency(self) -> str:
|
|
|
|
"""
|
|
|
|
Compatibility layer for asset - which can be empty for old trades.
|
|
|
|
"""
|
|
|
|
try:
|
|
|
|
return self.stake_currency or self.pair.split('/')[1].split(':')[0]
|
|
|
|
except IndexError:
|
|
|
|
return ''
|
|
|
|
|
|
|
|
def __init__(self, **kwargs):
|
|
|
|
for key in kwargs:
|
|
|
|
setattr(self, key, kwargs[key])
|
|
|
|
self.recalc_open_trade_value()
|
|
|
|
if self.trading_mode == TradingMode.MARGIN and self.interest_rate is None:
|
|
|
|
raise OperationalException(
|
|
|
|
f"{self.trading_mode.value} trading requires param interest_rate on trades")
|
|
|
|
|
|
|
|
def __repr__(self):
|
|
|
|
open_since = self.open_date.strftime(DATETIME_PRINT_FORMAT) if self.is_open else 'closed'
|
|
|
|
|
|
|
|
return (
|
|
|
|
f'Trade(id={self.id}, pair={self.pair}, amount={self.amount:.8f}, '
|
|
|
|
f'is_short={self.is_short or False}, leverage={self.leverage or 1.0}, '
|
|
|
|
f'open_rate={self.open_rate:.8f}, open_since={open_since})'
|
|
|
|
)
|
|
|
|
|
2022-05-26 05:11:43 +00:00
|
|
|
def to_json(self, minified: bool = False) -> Dict[str, Any]:
|
2022-05-24 18:31:45 +00:00
|
|
|
filled_orders = self.select_filled_or_open_orders()
|
2022-05-26 05:11:43 +00:00
|
|
|
orders = [order.to_json(self.entry_side, minified) for order in filled_orders]
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
return {
|
|
|
|
'trade_id': self.id,
|
|
|
|
'pair': self.pair,
|
|
|
|
'base_currency': self.safe_base_currency,
|
|
|
|
'quote_currency': self.safe_quote_currency,
|
|
|
|
'is_open': self.is_open,
|
|
|
|
'exchange': self.exchange,
|
|
|
|
'amount': round(self.amount, 8),
|
|
|
|
'amount_requested': round(self.amount_requested, 8) if self.amount_requested else None,
|
|
|
|
'stake_amount': round(self.stake_amount, 8),
|
2022-12-27 12:46:27 +00:00
|
|
|
'max_stake_amount': round(self.max_stake_amount, 8) if self.max_stake_amount else None,
|
2022-05-08 15:45:20 +00:00
|
|
|
'strategy': self.strategy,
|
|
|
|
'enter_tag': self.enter_tag,
|
|
|
|
'timeframe': self.timeframe,
|
|
|
|
|
|
|
|
'fee_open': self.fee_open,
|
|
|
|
'fee_open_cost': self.fee_open_cost,
|
|
|
|
'fee_open_currency': self.fee_open_currency,
|
|
|
|
'fee_close': self.fee_close,
|
|
|
|
'fee_close_cost': self.fee_close_cost,
|
|
|
|
'fee_close_currency': self.fee_close_currency,
|
|
|
|
|
|
|
|
'open_date': self.open_date.strftime(DATETIME_PRINT_FORMAT),
|
|
|
|
'open_timestamp': int(self.open_date.replace(tzinfo=timezone.utc).timestamp() * 1000),
|
|
|
|
'open_rate': self.open_rate,
|
|
|
|
'open_rate_requested': self.open_rate_requested,
|
|
|
|
'open_trade_value': round(self.open_trade_value, 8),
|
|
|
|
|
|
|
|
'close_date': (self.close_date.strftime(DATETIME_PRINT_FORMAT)
|
|
|
|
if self.close_date else None),
|
|
|
|
'close_timestamp': int(self.close_date.replace(
|
|
|
|
tzinfo=timezone.utc).timestamp() * 1000) if self.close_date else None,
|
2022-07-31 12:19:04 +00:00
|
|
|
'realized_profit': self.realized_profit or 0.0,
|
2023-03-04 17:20:31 +00:00
|
|
|
# Close-profit corresponds to relative realized_profit ratio
|
|
|
|
'realized_profit_ratio': self.close_profit or None,
|
2022-05-08 15:45:20 +00:00
|
|
|
'close_rate': self.close_rate,
|
|
|
|
'close_rate_requested': self.close_rate_requested,
|
|
|
|
'close_profit': self.close_profit, # Deprecated
|
|
|
|
'close_profit_pct': round(self.close_profit * 100, 2) if self.close_profit else None,
|
|
|
|
'close_profit_abs': self.close_profit_abs, # Deprecated
|
|
|
|
|
|
|
|
'trade_duration_s': (int((self.close_date_utc - self.open_date_utc).total_seconds())
|
|
|
|
if self.close_date else None),
|
|
|
|
'trade_duration': (int((self.close_date_utc - self.open_date_utc).total_seconds() // 60)
|
|
|
|
if self.close_date else None),
|
|
|
|
|
|
|
|
'profit_ratio': self.close_profit,
|
|
|
|
'profit_pct': round(self.close_profit * 100, 2) if self.close_profit else None,
|
|
|
|
'profit_abs': self.close_profit_abs,
|
|
|
|
|
|
|
|
'exit_reason': self.exit_reason,
|
|
|
|
'exit_order_status': self.exit_order_status,
|
|
|
|
'stop_loss_abs': self.stop_loss,
|
|
|
|
'stop_loss_ratio': self.stop_loss_pct if self.stop_loss_pct else None,
|
|
|
|
'stop_loss_pct': (self.stop_loss_pct * 100) if self.stop_loss_pct else None,
|
|
|
|
'stoploss_order_id': self.stoploss_order_id,
|
|
|
|
'stoploss_last_update': (self.stoploss_last_update.strftime(DATETIME_PRINT_FORMAT)
|
|
|
|
if self.stoploss_last_update else None),
|
|
|
|
'stoploss_last_update_timestamp': int(self.stoploss_last_update.replace(
|
|
|
|
tzinfo=timezone.utc).timestamp() * 1000) if self.stoploss_last_update else None,
|
|
|
|
'initial_stop_loss_abs': self.initial_stop_loss,
|
|
|
|
'initial_stop_loss_ratio': (self.initial_stop_loss_pct
|
|
|
|
if self.initial_stop_loss_pct else None),
|
|
|
|
'initial_stop_loss_pct': (self.initial_stop_loss_pct * 100
|
|
|
|
if self.initial_stop_loss_pct else None),
|
|
|
|
'min_rate': self.min_rate,
|
|
|
|
'max_rate': self.max_rate,
|
|
|
|
|
|
|
|
'leverage': self.leverage,
|
|
|
|
'interest_rate': self.interest_rate,
|
|
|
|
'liquidation_price': self.liquidation_price,
|
|
|
|
'is_short': self.is_short,
|
|
|
|
'trading_mode': self.trading_mode,
|
|
|
|
'funding_fees': self.funding_fees,
|
|
|
|
'open_order_id': self.open_order_id,
|
2023-03-25 10:42:19 +00:00
|
|
|
'amount_precision': self.amount_precision,
|
|
|
|
'price_precision': self.price_precision,
|
|
|
|
'precision_mode': self.precision_mode,
|
2022-05-08 15:45:20 +00:00
|
|
|
'orders': orders,
|
|
|
|
}
|
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def reset_trades() -> None:
|
|
|
|
"""
|
|
|
|
Resets all trades. Only active for backtesting mode.
|
|
|
|
"""
|
|
|
|
LocalTrade.trades = []
|
|
|
|
LocalTrade.trades_open = []
|
2022-10-16 11:34:58 +00:00
|
|
|
LocalTrade.bt_trades_open_pp = defaultdict(list)
|
|
|
|
LocalTrade.bt_open_open_trade_count = 0
|
2022-05-08 15:45:20 +00:00
|
|
|
LocalTrade.total_profit = 0
|
|
|
|
|
|
|
|
def adjust_min_max_rates(self, current_price: float, current_price_low: float) -> None:
|
|
|
|
"""
|
|
|
|
Adjust the max_rate and min_rate.
|
|
|
|
"""
|
|
|
|
self.max_rate = max(current_price, self.max_rate or self.open_rate)
|
|
|
|
self.min_rate = min(current_price_low, self.min_rate or self.open_rate)
|
|
|
|
|
2022-07-30 07:19:48 +00:00
|
|
|
def set_liquidation_price(self, liquidation_price: Optional[float]):
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
|
|
|
Method you should use to set self.liquidation price.
|
|
|
|
Assures stop_loss is not passed the liquidation price
|
|
|
|
"""
|
|
|
|
if not liquidation_price:
|
|
|
|
return
|
|
|
|
self.liquidation_price = liquidation_price
|
|
|
|
|
2022-07-29 05:15:01 +00:00
|
|
|
def __set_stop_loss(self, stop_loss: float, percent: float):
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
2022-07-29 05:15:01 +00:00
|
|
|
Method used internally to set self.stop_loss.
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
2022-08-17 07:51:28 +00:00
|
|
|
stop_loss_norm = price_to_precision(stop_loss, self.price_precision, self.precision_mode)
|
2022-05-08 15:45:20 +00:00
|
|
|
if not self.stop_loss:
|
2022-08-17 07:51:28 +00:00
|
|
|
self.initial_stop_loss = stop_loss_norm
|
|
|
|
self.stop_loss = stop_loss_norm
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
self.stop_loss_pct = -1 * abs(percent)
|
|
|
|
|
2023-03-01 06:26:35 +00:00
|
|
|
def adjust_stop_loss(self, current_price: float, stoploss: Optional[float],
|
2022-05-14 13:37:04 +00:00
|
|
|
initial: bool = False, refresh: bool = False) -> None:
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
|
|
|
This adjusts the stop loss to it's most recently observed setting
|
|
|
|
:param current_price: Current rate the asset is traded
|
|
|
|
:param stoploss: Stoploss as factor (sample -0.05 -> -5% below current price).
|
|
|
|
:param initial: Called to initiate stop_loss.
|
|
|
|
Skips everything if self.stop_loss is already set.
|
|
|
|
"""
|
2023-03-01 06:26:35 +00:00
|
|
|
if stoploss is None or (initial and not (self.stop_loss is None or self.stop_loss == 0)):
|
2022-05-08 15:45:20 +00:00
|
|
|
# Don't modify if called with initial and nothing to do
|
|
|
|
return
|
2022-05-15 13:30:57 +00:00
|
|
|
refresh = True if refresh and self.nr_of_successful_entries == 1 else False
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
leverage = self.leverage or 1.0
|
|
|
|
if self.is_short:
|
|
|
|
new_loss = float(current_price * (1 + abs(stoploss / leverage)))
|
|
|
|
else:
|
|
|
|
new_loss = float(current_price * (1 - abs(stoploss / leverage)))
|
|
|
|
|
|
|
|
# no stop loss assigned yet
|
2022-05-14 13:37:04 +00:00
|
|
|
if self.initial_stop_loss_pct is None or refresh:
|
2022-07-29 05:15:01 +00:00
|
|
|
self.__set_stop_loss(new_loss, stoploss)
|
2022-08-17 07:51:28 +00:00
|
|
|
self.initial_stop_loss = price_to_precision(
|
|
|
|
new_loss, self.price_precision, self.precision_mode)
|
2022-05-08 15:45:20 +00:00
|
|
|
self.initial_stop_loss_pct = -1 * abs(stoploss)
|
|
|
|
|
|
|
|
# evaluate if the stop loss needs to be updated
|
|
|
|
else:
|
|
|
|
|
|
|
|
higher_stop = new_loss > self.stop_loss
|
|
|
|
lower_stop = new_loss < self.stop_loss
|
|
|
|
|
|
|
|
# stop losses only walk up, never down!,
|
|
|
|
# ? But adding more to a leveraged trade would create a lower liquidation price,
|
|
|
|
# ? decreasing the minimum stoploss
|
|
|
|
if (higher_stop and not self.is_short) or (lower_stop and self.is_short):
|
|
|
|
logger.debug(f"{self.pair} - Adjusting stoploss...")
|
2022-07-29 05:15:01 +00:00
|
|
|
self.__set_stop_loss(new_loss, stoploss)
|
2022-05-08 15:45:20 +00:00
|
|
|
else:
|
|
|
|
logger.debug(f"{self.pair} - Keeping current stoploss...")
|
|
|
|
|
|
|
|
logger.debug(
|
|
|
|
f"{self.pair} - Stoploss adjusted. current_price={current_price:.8f}, "
|
|
|
|
f"open_rate={self.open_rate:.8f}, max_rate={self.max_rate or self.open_rate:.8f}, "
|
|
|
|
f"initial_stop_loss={self.initial_stop_loss:.8f}, "
|
|
|
|
f"stop_loss={self.stop_loss:.8f}. "
|
|
|
|
f"Trailing stoploss saved us: "
|
2023-03-01 17:17:37 +00:00
|
|
|
f"{float(self.stop_loss) - float(self.initial_stop_loss or 0.0):.8f}.")
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
def update_trade(self, order: Order) -> None:
|
|
|
|
"""
|
|
|
|
Updates this entity with amount and actual open/close rates.
|
|
|
|
:param order: order retrieved by exchange.fetch_order()
|
|
|
|
:return: None
|
|
|
|
"""
|
|
|
|
|
|
|
|
# Ignore open and cancelled orders
|
|
|
|
if order.status == 'open' or order.safe_price is None:
|
|
|
|
return
|
|
|
|
|
|
|
|
logger.info(f'Updating trade (id={self.id}) ...')
|
|
|
|
|
|
|
|
if order.ft_order_side == self.entry_side:
|
|
|
|
# Update open rate and actual amount
|
|
|
|
self.open_rate = order.safe_price
|
|
|
|
self.amount = order.safe_amount_after_fee
|
|
|
|
if self.is_open:
|
|
|
|
payment = "SELL" if self.is_short else "BUY"
|
|
|
|
logger.info(f'{order.order_type.upper()}_{payment} has been fulfilled for {self}.')
|
2022-07-31 12:19:04 +00:00
|
|
|
# condition to avoid reset value when updating fees
|
|
|
|
if self.open_order_id == order.order_id:
|
|
|
|
self.open_order_id = None
|
|
|
|
else:
|
|
|
|
logger.warning(
|
|
|
|
f'Got different open_order_id {self.open_order_id} != {order.order_id}')
|
2022-05-08 15:45:20 +00:00
|
|
|
self.recalc_trade_from_orders()
|
|
|
|
elif order.ft_order_side == self.exit_side:
|
|
|
|
if self.is_open:
|
|
|
|
payment = "BUY" if self.is_short else "SELL"
|
|
|
|
# * On margin shorts, you buy a little bit more than the amount (amount + interest)
|
|
|
|
logger.info(f'{order.order_type.upper()}_{payment} has been fulfilled for {self}.')
|
2022-07-31 12:19:04 +00:00
|
|
|
# condition to avoid reset value when updating fees
|
|
|
|
if self.open_order_id == order.order_id:
|
|
|
|
self.open_order_id = None
|
|
|
|
else:
|
|
|
|
logger.warning(
|
|
|
|
f'Got different open_order_id {self.open_order_id} != {order.order_id}')
|
2022-08-25 05:08:22 +00:00
|
|
|
amount_tr = amount_to_contract_precision(self.amount, self.amount_precision,
|
|
|
|
self.precision_mode, self.contract_size)
|
2022-08-16 07:49:53 +00:00
|
|
|
if isclose(order.safe_amount_after_fee, amount_tr, abs_tol=MATH_CLOSE_PREC):
|
2022-07-31 12:19:04 +00:00
|
|
|
self.close(order.safe_price)
|
|
|
|
else:
|
|
|
|
self.recalc_trade_from_orders()
|
2022-11-08 19:34:18 +00:00
|
|
|
elif order.ft_order_side == 'stoploss' and order.status not in ('canceled', 'open'):
|
2022-05-08 15:45:20 +00:00
|
|
|
self.stoploss_order_id = None
|
|
|
|
self.close_rate_requested = self.stop_loss
|
|
|
|
self.exit_reason = ExitType.STOPLOSS_ON_EXCHANGE.value
|
|
|
|
if self.is_open:
|
|
|
|
logger.info(f'{order.order_type.upper()} is hit for {self}.')
|
|
|
|
self.close(order.safe_price)
|
|
|
|
else:
|
|
|
|
raise ValueError(f'Unknown order type: {order.order_type}')
|
|
|
|
Trade.commit()
|
|
|
|
|
|
|
|
def close(self, rate: float, *, show_msg: bool = True) -> None:
|
|
|
|
"""
|
|
|
|
Sets close_rate to the given rate, calculates total profit
|
|
|
|
and marks trade as closed
|
|
|
|
"""
|
|
|
|
self.close_rate = rate
|
|
|
|
self.close_date = self.close_date or datetime.utcnow()
|
|
|
|
self.is_open = False
|
|
|
|
self.exit_order_status = 'closed'
|
|
|
|
self.open_order_id = None
|
2022-07-31 12:19:04 +00:00
|
|
|
self.recalc_trade_from_orders(is_closing=True)
|
2022-05-08 15:45:20 +00:00
|
|
|
if show_msg:
|
|
|
|
logger.info(
|
|
|
|
'Marking %s as closed as the trade is fulfilled and found no open orders for it.',
|
|
|
|
self
|
|
|
|
)
|
|
|
|
|
|
|
|
def update_fee(self, fee_cost: float, fee_currency: Optional[str], fee_rate: Optional[float],
|
|
|
|
side: str) -> None:
|
|
|
|
"""
|
|
|
|
Update Fee parameters. Only acts once per side
|
|
|
|
"""
|
|
|
|
if self.entry_side == side and self.fee_open_currency is None:
|
|
|
|
self.fee_open_cost = fee_cost
|
|
|
|
self.fee_open_currency = fee_currency
|
|
|
|
if fee_rate is not None:
|
|
|
|
self.fee_open = fee_rate
|
|
|
|
# Assume close-fee will fall into the same fee category and take an educated guess
|
|
|
|
self.fee_close = fee_rate
|
|
|
|
elif self.exit_side == side and self.fee_close_currency is None:
|
|
|
|
self.fee_close_cost = fee_cost
|
|
|
|
self.fee_close_currency = fee_currency
|
|
|
|
if fee_rate is not None:
|
|
|
|
self.fee_close = fee_rate
|
|
|
|
|
|
|
|
def fee_updated(self, side: str) -> bool:
|
|
|
|
"""
|
|
|
|
Verify if this side (buy / sell) has already been updated
|
|
|
|
"""
|
|
|
|
if self.entry_side == side:
|
|
|
|
return self.fee_open_currency is not None
|
|
|
|
elif self.exit_side == side:
|
|
|
|
return self.fee_close_currency is not None
|
|
|
|
else:
|
|
|
|
return False
|
|
|
|
|
|
|
|
def update_order(self, order: Dict) -> None:
|
|
|
|
Order.update_orders(self.orders, order)
|
|
|
|
|
|
|
|
def get_exit_order_count(self) -> int:
|
|
|
|
"""
|
|
|
|
Get amount of failed exiting orders
|
|
|
|
assumes full exits.
|
|
|
|
"""
|
|
|
|
return len([o for o in self.orders if o.ft_order_side == self.exit_side])
|
|
|
|
|
2022-07-31 12:19:04 +00:00
|
|
|
def _calc_open_trade_value(self, amount: float, open_rate: float) -> float:
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
|
|
|
Calculate the open_rate including open_fee.
|
|
|
|
:return: Price in of the open trade incl. Fees
|
|
|
|
"""
|
2022-08-10 18:31:03 +00:00
|
|
|
open_trade = FtPrecise(amount) * FtPrecise(open_rate)
|
|
|
|
fees = open_trade * FtPrecise(self.fee_open)
|
2022-05-08 15:45:20 +00:00
|
|
|
if self.is_short:
|
|
|
|
return float(open_trade - fees)
|
|
|
|
else:
|
|
|
|
return float(open_trade + fees)
|
|
|
|
|
|
|
|
def recalc_open_trade_value(self) -> None:
|
|
|
|
"""
|
|
|
|
Recalculate open_trade_value.
|
2022-05-13 14:02:52 +00:00
|
|
|
Must be called whenever open_rate, fee_open is changed.
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
2022-07-31 12:19:04 +00:00
|
|
|
self.open_trade_value = self._calc_open_trade_value(self.amount, self.open_rate)
|
2022-05-08 15:45:20 +00:00
|
|
|
|
2022-08-10 18:31:03 +00:00
|
|
|
def calculate_interest(self) -> FtPrecise:
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
2022-06-17 09:53:29 +00:00
|
|
|
Calculate interest for this trade. Only applicable for Margin trading.
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
2022-08-10 18:31:03 +00:00
|
|
|
zero = FtPrecise(0.0)
|
2022-05-08 15:45:20 +00:00
|
|
|
# If nothing was borrowed
|
|
|
|
if self.trading_mode != TradingMode.MARGIN or self.has_no_leverage:
|
|
|
|
return zero
|
|
|
|
|
|
|
|
open_date = self.open_date.replace(tzinfo=None)
|
|
|
|
now = (self.close_date or datetime.now(timezone.utc)).replace(tzinfo=None)
|
2022-08-10 18:31:03 +00:00
|
|
|
sec_per_hour = FtPrecise(3600)
|
|
|
|
total_seconds = FtPrecise((now - open_date).total_seconds())
|
2022-05-08 15:45:20 +00:00
|
|
|
hours = total_seconds / sec_per_hour or zero
|
|
|
|
|
2022-08-10 18:31:03 +00:00
|
|
|
rate = FtPrecise(self.interest_rate)
|
|
|
|
borrowed = FtPrecise(self.borrowed)
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
return interest(exchange_name=self.exchange, borrowed=borrowed, rate=rate, hours=hours)
|
|
|
|
|
2023-03-01 06:25:33 +00:00
|
|
|
def _calc_base_close(self, amount: FtPrecise, rate: float, fee: Optional[float]) -> FtPrecise:
|
2022-05-08 15:45:20 +00:00
|
|
|
|
2022-08-10 18:31:03 +00:00
|
|
|
close_trade = amount * FtPrecise(rate)
|
2023-03-01 06:25:33 +00:00
|
|
|
fees = close_trade * FtPrecise(fee or 0.0)
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
if self.is_short:
|
|
|
|
return close_trade + fees
|
|
|
|
else:
|
|
|
|
return close_trade - fees
|
|
|
|
|
2023-01-21 14:01:56 +00:00
|
|
|
def calc_close_trade_value(self, rate: float, amount: Optional[float] = None) -> float:
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
2022-06-17 09:53:29 +00:00
|
|
|
Calculate the Trade's close value including fees
|
2022-06-17 07:00:42 +00:00
|
|
|
:param rate: rate to compare with.
|
2022-06-17 09:53:29 +00:00
|
|
|
:return: value in stake currency of the open trade
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
|
|
|
if rate is None and not self.close_rate:
|
|
|
|
return 0.0
|
|
|
|
|
2022-08-10 18:31:03 +00:00
|
|
|
amount1 = FtPrecise(amount or self.amount)
|
2022-05-08 15:45:20 +00:00
|
|
|
trading_mode = self.trading_mode or TradingMode.SPOT
|
|
|
|
|
|
|
|
if trading_mode == TradingMode.SPOT:
|
2022-07-31 12:19:04 +00:00
|
|
|
return float(self._calc_base_close(amount1, rate, self.fee_close))
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
elif (trading_mode == TradingMode.MARGIN):
|
|
|
|
|
2022-06-17 09:53:29 +00:00
|
|
|
total_interest = self.calculate_interest()
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
if self.is_short:
|
2022-07-31 12:19:04 +00:00
|
|
|
amount1 = amount1 + total_interest
|
|
|
|
return float(self._calc_base_close(amount1, rate, self.fee_close))
|
2022-05-08 15:45:20 +00:00
|
|
|
else:
|
|
|
|
# Currency already owned for longs, no need to purchase
|
2022-07-31 12:19:04 +00:00
|
|
|
return float(self._calc_base_close(amount1, rate, self.fee_close) - total_interest)
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
elif (trading_mode == TradingMode.FUTURES):
|
|
|
|
funding_fees = self.funding_fees or 0.0
|
|
|
|
# Positive funding_fees -> Trade has gained from fees.
|
|
|
|
# Negative funding_fees -> Trade had to pay the fees.
|
|
|
|
if self.is_short:
|
2022-07-31 12:19:04 +00:00
|
|
|
return float(self._calc_base_close(amount1, rate, self.fee_close)) - funding_fees
|
2022-05-08 15:45:20 +00:00
|
|
|
else:
|
2022-07-31 12:19:04 +00:00
|
|
|
return float(self._calc_base_close(amount1, rate, self.fee_close)) + funding_fees
|
2022-05-08 15:45:20 +00:00
|
|
|
else:
|
|
|
|
raise OperationalException(
|
|
|
|
f"{self.trading_mode.value} trading is not yet available using freqtrade")
|
|
|
|
|
2023-01-21 14:01:56 +00:00
|
|
|
def calc_profit(self, rate: float, amount: Optional[float] = None,
|
|
|
|
open_rate: Optional[float] = None) -> float:
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
|
|
|
Calculate the absolute profit in stake currency between Close and Open trade
|
2022-06-17 07:00:42 +00:00
|
|
|
:param rate: close rate to compare with.
|
2022-07-31 12:19:04 +00:00
|
|
|
:param amount: Amount to use for the calculation. Falls back to trade.amount if not set.
|
|
|
|
:param open_rate: open_rate to use. Defaults to self.open_rate if not provided.
|
2022-06-17 09:53:29 +00:00
|
|
|
:return: profit in stake currency as float
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
2022-07-31 12:19:04 +00:00
|
|
|
close_trade_value = self.calc_close_trade_value(rate, amount)
|
|
|
|
if amount is None or open_rate is None:
|
|
|
|
open_trade_value = self.open_trade_value
|
|
|
|
else:
|
|
|
|
open_trade_value = self._calc_open_trade_value(amount, open_rate)
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
if self.is_short:
|
2022-07-31 12:19:04 +00:00
|
|
|
profit = open_trade_value - close_trade_value
|
2022-05-08 15:45:20 +00:00
|
|
|
else:
|
2022-07-31 12:19:04 +00:00
|
|
|
profit = close_trade_value - open_trade_value
|
2022-05-08 15:45:20 +00:00
|
|
|
return float(f"{profit:.8f}")
|
|
|
|
|
2022-07-31 12:19:04 +00:00
|
|
|
def calc_profit_ratio(
|
2023-01-21 14:01:56 +00:00
|
|
|
self, rate: float, amount: Optional[float] = None,
|
|
|
|
open_rate: Optional[float] = None) -> float:
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
|
|
|
Calculates the profit as ratio (including fee).
|
2022-06-17 07:00:42 +00:00
|
|
|
:param rate: rate to compare with.
|
2022-07-31 12:19:04 +00:00
|
|
|
:param amount: Amount to use for the calculation. Falls back to trade.amount if not set.
|
|
|
|
:param open_rate: open_rate to use. Defaults to self.open_rate if not provided.
|
2022-05-08 15:45:20 +00:00
|
|
|
:return: profit ratio as float
|
|
|
|
"""
|
2022-07-31 12:19:04 +00:00
|
|
|
close_trade_value = self.calc_close_trade_value(rate, amount)
|
|
|
|
|
|
|
|
if amount is None or open_rate is None:
|
|
|
|
open_trade_value = self.open_trade_value
|
|
|
|
else:
|
|
|
|
open_trade_value = self._calc_open_trade_value(amount, open_rate)
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
short_close_zero = (self.is_short and close_trade_value == 0.0)
|
2022-07-31 12:19:04 +00:00
|
|
|
long_close_zero = (not self.is_short and open_trade_value == 0.0)
|
2022-05-08 15:45:20 +00:00
|
|
|
leverage = self.leverage or 1.0
|
|
|
|
|
|
|
|
if (short_close_zero or long_close_zero):
|
|
|
|
return 0.0
|
|
|
|
else:
|
|
|
|
if self.is_short:
|
2022-07-31 12:19:04 +00:00
|
|
|
profit_ratio = (1 - (close_trade_value / open_trade_value)) * leverage
|
2022-05-08 15:45:20 +00:00
|
|
|
else:
|
2022-07-31 12:19:04 +00:00
|
|
|
profit_ratio = ((close_trade_value / open_trade_value) - 1) * leverage
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
return float(f"{profit_ratio:.8f}")
|
|
|
|
|
2022-08-15 06:43:58 +00:00
|
|
|
def recalc_trade_from_orders(self, *, is_closing: bool = False):
|
2022-08-11 04:51:34 +00:00
|
|
|
ZERO = FtPrecise(0.0)
|
|
|
|
current_amount = FtPrecise(0.0)
|
|
|
|
current_stake = FtPrecise(0.0)
|
2022-12-27 17:08:20 +00:00
|
|
|
max_stake_amount = FtPrecise(0.0)
|
2022-07-31 12:19:04 +00:00
|
|
|
total_stake = 0.0 # Total stake after all buy orders (does not subtract!)
|
2022-08-11 04:51:34 +00:00
|
|
|
avg_price = FtPrecise(0.0)
|
2022-07-31 12:19:04 +00:00
|
|
|
close_profit = 0.0
|
|
|
|
close_profit_abs = 0.0
|
2022-08-24 18:36:08 +00:00
|
|
|
profit = None
|
2022-09-02 04:51:30 +00:00
|
|
|
# Reset funding fees
|
|
|
|
self.funding_fees = 0.0
|
|
|
|
funding_fees = 0.0
|
|
|
|
ordercount = len(self.orders) - 1
|
|
|
|
for i, o in enumerate(self.orders):
|
2022-07-31 12:19:04 +00:00
|
|
|
if o.ft_is_open or not o.filled:
|
2022-05-08 15:45:20 +00:00
|
|
|
continue
|
2022-09-02 04:51:30 +00:00
|
|
|
funding_fees += (o.funding_fee or 0.0)
|
2022-08-11 04:51:34 +00:00
|
|
|
tmp_amount = FtPrecise(o.safe_amount_after_fee)
|
|
|
|
tmp_price = FtPrecise(o.safe_price)
|
2022-07-31 12:19:04 +00:00
|
|
|
|
|
|
|
is_exit = o.ft_order_side != self.entry_side
|
2022-08-11 04:51:34 +00:00
|
|
|
side = FtPrecise(-1 if is_exit else 1)
|
|
|
|
if tmp_amount > ZERO and tmp_price is not None:
|
2022-07-31 12:19:04 +00:00
|
|
|
current_amount += tmp_amount * side
|
|
|
|
price = avg_price if is_exit else tmp_price
|
|
|
|
current_stake += price * tmp_amount * side
|
|
|
|
|
2022-08-11 04:51:34 +00:00
|
|
|
if current_amount > ZERO:
|
2022-07-31 12:19:04 +00:00
|
|
|
avg_price = current_stake / current_amount
|
|
|
|
|
|
|
|
if is_exit:
|
2022-09-02 04:51:30 +00:00
|
|
|
# Process exits
|
|
|
|
if i == ordercount and is_closing:
|
2022-09-03 13:18:09 +00:00
|
|
|
# Apply funding fees only to the last closing order
|
2022-09-02 04:51:30 +00:00
|
|
|
self.funding_fees = funding_fees
|
|
|
|
|
2022-07-31 12:19:04 +00:00
|
|
|
exit_rate = o.safe_price
|
|
|
|
exit_amount = o.safe_amount_after_fee
|
2022-08-11 04:51:34 +00:00
|
|
|
profit = self.calc_profit(rate=exit_rate, amount=exit_amount,
|
|
|
|
open_rate=float(avg_price))
|
2022-07-31 12:19:04 +00:00
|
|
|
close_profit_abs += profit
|
|
|
|
close_profit = self.calc_profit_ratio(
|
|
|
|
exit_rate, amount=exit_amount, open_rate=avg_price)
|
|
|
|
else:
|
|
|
|
total_stake = total_stake + self._calc_open_trade_value(tmp_amount, price)
|
2022-12-27 17:08:20 +00:00
|
|
|
max_stake_amount += (tmp_amount * price)
|
2022-09-02 04:51:30 +00:00
|
|
|
self.funding_fees = funding_fees
|
2022-12-27 17:08:20 +00:00
|
|
|
self.max_stake_amount = float(max_stake_amount)
|
2022-07-31 12:19:04 +00:00
|
|
|
|
|
|
|
if close_profit:
|
|
|
|
self.close_profit = close_profit
|
|
|
|
self.realized_profit = close_profit_abs
|
|
|
|
self.close_profit_abs = profit
|
2022-05-08 15:45:20 +00:00
|
|
|
|
2022-08-25 05:08:22 +00:00
|
|
|
current_amount_tr = amount_to_contract_precision(
|
|
|
|
float(current_amount), self.amount_precision, self.precision_mode, self.contract_size)
|
2022-08-16 06:21:02 +00:00
|
|
|
if current_amount_tr > 0.0:
|
2022-07-31 12:19:04 +00:00
|
|
|
# Trade is still open
|
2022-05-08 15:45:20 +00:00
|
|
|
# Leverage not updated, as we don't allow changing leverage through DCA at the moment.
|
2022-08-16 16:16:23 +00:00
|
|
|
self.open_rate = float(current_stake / current_amount)
|
2022-08-16 06:21:02 +00:00
|
|
|
self.amount = current_amount_tr
|
2022-08-11 04:51:34 +00:00
|
|
|
self.stake_amount = float(current_stake) / (self.leverage or 1.0)
|
|
|
|
self.fee_open_cost = self.fee_open * float(current_stake)
|
2022-05-08 15:45:20 +00:00
|
|
|
self.recalc_open_trade_value()
|
|
|
|
if self.stop_loss_pct is not None and self.open_rate is not None:
|
|
|
|
self.adjust_stop_loss(self.open_rate, self.stop_loss_pct)
|
2022-07-31 12:19:04 +00:00
|
|
|
elif is_closing and total_stake > 0:
|
|
|
|
# Close profit abs / maximum owned
|
|
|
|
# Fees are considered as they are part of close_profit_abs
|
|
|
|
self.close_profit = (close_profit_abs / total_stake) * self.leverage
|
2022-08-24 18:36:08 +00:00
|
|
|
self.close_profit_abs = close_profit_abs
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
def select_order_by_order_id(self, order_id: str) -> Optional[Order]:
|
|
|
|
"""
|
|
|
|
Finds order object by Order id.
|
|
|
|
:param order_id: Exchange order id
|
|
|
|
"""
|
|
|
|
for o in self.orders:
|
|
|
|
if o.order_id == order_id:
|
|
|
|
return o
|
|
|
|
return None
|
|
|
|
|
2022-05-25 10:13:37 +00:00
|
|
|
def select_order(self, order_side: Optional[str] = None,
|
2023-01-08 10:24:04 +00:00
|
|
|
is_open: Optional[bool] = None, only_filled: bool = False) -> Optional[Order]:
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
|
|
|
Finds latest order for this orderside and status
|
|
|
|
:param order_side: ft_order_side of the order (either 'buy', 'sell' or 'stoploss')
|
|
|
|
:param is_open: Only search for open orders?
|
2023-01-08 10:24:04 +00:00
|
|
|
:param only_filled: Only search for Filled orders (only valid with is_open=False).
|
2022-05-08 15:45:20 +00:00
|
|
|
:return: latest Order object if it exists, else None
|
|
|
|
"""
|
|
|
|
orders = self.orders
|
|
|
|
if order_side:
|
2022-07-31 12:19:04 +00:00
|
|
|
orders = [o for o in orders if o.ft_order_side == order_side]
|
2022-05-08 15:45:20 +00:00
|
|
|
if is_open is not None:
|
|
|
|
orders = [o for o in orders if o.ft_is_open == is_open]
|
2023-01-08 10:24:04 +00:00
|
|
|
if is_open is False and only_filled:
|
|
|
|
orders = [o for o in orders if o.filled and o.status in NON_OPEN_EXCHANGE_STATES]
|
2022-05-08 15:45:20 +00:00
|
|
|
if len(orders) > 0:
|
|
|
|
return orders[-1]
|
|
|
|
else:
|
|
|
|
return None
|
|
|
|
|
|
|
|
def select_filled_orders(self, order_side: Optional[str] = None) -> List['Order']:
|
|
|
|
"""
|
|
|
|
Finds filled orders for this orderside.
|
|
|
|
:param order_side: Side of the order (either 'buy', 'sell', or None)
|
|
|
|
:return: array of Order objects
|
|
|
|
"""
|
|
|
|
return [o for o in self.orders if ((o.ft_order_side == order_side) or (order_side is None))
|
2022-07-31 12:19:04 +00:00
|
|
|
and o.ft_is_open is False
|
|
|
|
and o.filled
|
|
|
|
and o.status in NON_OPEN_EXCHANGE_STATES]
|
2022-05-08 15:45:20 +00:00
|
|
|
|
2022-05-24 18:31:45 +00:00
|
|
|
def select_filled_or_open_orders(self) -> List['Order']:
|
|
|
|
"""
|
|
|
|
Finds filled or open orders
|
|
|
|
:param order_side: Side of the order (either 'buy', 'sell', or None)
|
|
|
|
:return: array of Order objects
|
|
|
|
"""
|
|
|
|
return [o for o in self.orders if
|
|
|
|
(
|
|
|
|
o.ft_is_open is False
|
|
|
|
and (o.filled or 0) > 0
|
|
|
|
and o.status in NON_OPEN_EXCHANGE_STATES
|
|
|
|
)
|
|
|
|
or (o.ft_is_open is True and o.status is not None)
|
|
|
|
]
|
|
|
|
|
2022-05-08 15:45:20 +00:00
|
|
|
@property
|
|
|
|
def nr_of_successful_entries(self) -> int:
|
|
|
|
"""
|
|
|
|
Helper function to count the number of entry orders that have been filled.
|
|
|
|
:return: int count of entry orders that have been filled for this trade.
|
|
|
|
"""
|
|
|
|
|
|
|
|
return len(self.select_filled_orders(self.entry_side))
|
|
|
|
|
|
|
|
@property
|
|
|
|
def nr_of_successful_exits(self) -> int:
|
|
|
|
"""
|
|
|
|
Helper function to count the number of exit orders that have been filled.
|
|
|
|
:return: int count of exit orders that have been filled for this trade.
|
|
|
|
"""
|
|
|
|
return len(self.select_filled_orders(self.exit_side))
|
|
|
|
|
|
|
|
@property
|
|
|
|
def nr_of_successful_buys(self) -> int:
|
|
|
|
"""
|
|
|
|
Helper function to count the number of buy orders that have been filled.
|
|
|
|
WARNING: Please use nr_of_successful_entries for short support.
|
|
|
|
:return: int count of buy orders that have been filled for this trade.
|
|
|
|
"""
|
|
|
|
|
|
|
|
return len(self.select_filled_orders('buy'))
|
|
|
|
|
|
|
|
@property
|
|
|
|
def nr_of_successful_sells(self) -> int:
|
|
|
|
"""
|
|
|
|
Helper function to count the number of sell orders that have been filled.
|
|
|
|
WARNING: Please use nr_of_successful_exits for short support.
|
|
|
|
:return: int count of sell orders that have been filled for this trade.
|
|
|
|
"""
|
|
|
|
return len(self.select_filled_orders('sell'))
|
|
|
|
|
|
|
|
@property
|
2023-02-28 06:27:01 +00:00
|
|
|
def sell_reason(self) -> Optional[str]:
|
2022-05-08 15:45:20 +00:00
|
|
|
""" DEPRECATED! Please use exit_reason instead."""
|
|
|
|
return self.exit_reason
|
|
|
|
|
2023-02-16 09:02:57 +00:00
|
|
|
@property
|
|
|
|
def safe_close_rate(self) -> float:
|
|
|
|
return self.close_rate or self.close_rate_requested or 0.0
|
|
|
|
|
2022-05-08 15:45:20 +00:00
|
|
|
@staticmethod
|
2023-01-21 14:01:56 +00:00
|
|
|
def get_trades_proxy(*, pair: Optional[str] = None, is_open: Optional[bool] = None,
|
|
|
|
open_date: Optional[datetime] = None,
|
|
|
|
close_date: Optional[datetime] = None,
|
2022-05-08 15:45:20 +00:00
|
|
|
) -> List['LocalTrade']:
|
|
|
|
"""
|
|
|
|
Helper function to query Trades.
|
|
|
|
Returns a List of trades, filtered on the parameters given.
|
|
|
|
In live mode, converts the filter to a database query and returns all rows
|
|
|
|
In Backtest mode, uses filters on Trade.trades to get the result.
|
|
|
|
|
2023-03-15 06:23:54 +00:00
|
|
|
:param pair: Filter by pair
|
|
|
|
:param is_open: Filter by open/closed status
|
|
|
|
:param open_date: Filter by open_date (filters via trade.open_date > input)
|
|
|
|
:param close_date: Filter by close_date (filters via trade.close_date > input)
|
|
|
|
Will implicitly only return closed trades.
|
2022-05-08 15:45:20 +00:00
|
|
|
:return: unsorted List[Trade]
|
|
|
|
"""
|
|
|
|
|
|
|
|
# Offline mode - without database
|
|
|
|
if is_open is not None:
|
|
|
|
if is_open:
|
|
|
|
sel_trades = LocalTrade.trades_open
|
|
|
|
else:
|
|
|
|
sel_trades = LocalTrade.trades
|
|
|
|
|
|
|
|
else:
|
|
|
|
# Not used during backtesting, but might be used by a strategy
|
|
|
|
sel_trades = list(LocalTrade.trades + LocalTrade.trades_open)
|
|
|
|
|
|
|
|
if pair:
|
|
|
|
sel_trades = [trade for trade in sel_trades if trade.pair == pair]
|
|
|
|
if open_date:
|
|
|
|
sel_trades = [trade for trade in sel_trades if trade.open_date > open_date]
|
|
|
|
if close_date:
|
|
|
|
sel_trades = [trade for trade in sel_trades if trade.close_date
|
|
|
|
and trade.close_date > close_date]
|
|
|
|
|
|
|
|
return sel_trades
|
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def close_bt_trade(trade):
|
|
|
|
LocalTrade.trades_open.remove(trade)
|
2022-10-16 11:34:58 +00:00
|
|
|
LocalTrade.bt_trades_open_pp[trade.pair].remove(trade)
|
|
|
|
LocalTrade.bt_open_open_trade_count -= 1
|
2022-05-08 15:45:20 +00:00
|
|
|
LocalTrade.trades.append(trade)
|
|
|
|
LocalTrade.total_profit += trade.close_profit_abs
|
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def add_bt_trade(trade):
|
|
|
|
if trade.is_open:
|
|
|
|
LocalTrade.trades_open.append(trade)
|
2022-10-16 11:34:58 +00:00
|
|
|
LocalTrade.bt_trades_open_pp[trade.pair].append(trade)
|
|
|
|
LocalTrade.bt_open_open_trade_count += 1
|
2022-05-08 15:45:20 +00:00
|
|
|
else:
|
|
|
|
LocalTrade.trades.append(trade)
|
|
|
|
|
2022-10-16 11:19:42 +00:00
|
|
|
@staticmethod
|
|
|
|
def remove_bt_trade(trade):
|
|
|
|
LocalTrade.trades_open.remove(trade)
|
2022-10-16 11:34:58 +00:00
|
|
|
LocalTrade.bt_trades_open_pp[trade.pair].remove(trade)
|
|
|
|
LocalTrade.bt_open_open_trade_count -= 1
|
2022-10-16 11:19:42 +00:00
|
|
|
|
2022-05-08 15:45:20 +00:00
|
|
|
@staticmethod
|
|
|
|
def get_open_trades() -> List[Any]:
|
|
|
|
"""
|
2023-03-01 06:23:26 +00:00
|
|
|
Retrieve open trades
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
|
|
|
return Trade.get_trades_proxy(is_open=True)
|
|
|
|
|
2022-08-21 08:03:04 +00:00
|
|
|
@staticmethod
|
|
|
|
def get_open_trade_count() -> int:
|
|
|
|
"""
|
|
|
|
get open trade count
|
|
|
|
"""
|
|
|
|
if Trade.use_db:
|
2023-03-15 20:12:06 +00:00
|
|
|
return Trade.session.execute(
|
2023-03-15 20:00:30 +00:00
|
|
|
select(func.count(Trade.id)).filter(Trade.is_open.is_(True))
|
2023-03-15 20:09:25 +00:00
|
|
|
).scalar_one()
|
2022-08-21 08:03:04 +00:00
|
|
|
else:
|
2022-10-16 11:34:58 +00:00
|
|
|
return LocalTrade.bt_open_open_trade_count
|
2022-08-21 08:03:04 +00:00
|
|
|
|
2022-05-08 15:45:20 +00:00
|
|
|
@staticmethod
|
|
|
|
def stoploss_reinitialization(desired_stoploss):
|
|
|
|
"""
|
|
|
|
Adjust initial Stoploss to desired stoploss for all open trades.
|
|
|
|
"""
|
|
|
|
for trade in Trade.get_open_trades():
|
|
|
|
logger.info("Found open trade: %s", trade)
|
|
|
|
|
|
|
|
# skip case if trailing-stop changed the stoploss already.
|
|
|
|
if (trade.stop_loss == trade.initial_stop_loss
|
|
|
|
and trade.initial_stop_loss_pct != desired_stoploss):
|
|
|
|
# Stoploss value got changed
|
|
|
|
|
|
|
|
logger.info(f"Stoploss for {trade} needs adjustment...")
|
|
|
|
# Force reset of stoploss
|
|
|
|
trade.stop_loss = None
|
|
|
|
trade.initial_stop_loss_pct = None
|
|
|
|
trade.adjust_stop_loss(trade.open_rate, desired_stoploss)
|
|
|
|
logger.info(f"New stoploss: {trade.stop_loss}.")
|
|
|
|
|
|
|
|
|
2023-02-16 07:04:45 +00:00
|
|
|
class Trade(ModelBase, LocalTrade):
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
|
|
|
Trade database model.
|
|
|
|
Also handles updating and querying trades
|
|
|
|
|
|
|
|
Note: Fields must be aligned with LocalTrade class
|
|
|
|
"""
|
|
|
|
__tablename__ = 'trades'
|
2023-03-15 20:12:06 +00:00
|
|
|
session: ClassVar[SessionType]
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
use_db: bool = True
|
|
|
|
|
2023-03-01 18:48:15 +00:00
|
|
|
id: Mapped[int] = mapped_column(Integer, primary_key=True) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
|
2023-02-16 07:27:57 +00:00
|
|
|
orders: Mapped[List[Order]] = relationship(
|
|
|
|
"Order", order_by="Order.id", cascade="all, delete-orphan", lazy="selectin",
|
2023-03-01 18:48:15 +00:00
|
|
|
innerjoin=True) # type: ignore
|
|
|
|
|
|
|
|
exchange: Mapped[str] = mapped_column(String(25), nullable=False) # type: ignore
|
|
|
|
pair: Mapped[str] = mapped_column(String(25), nullable=False, index=True) # type: ignore
|
|
|
|
base_currency: Mapped[Optional[str]] = mapped_column(String(25), nullable=True) # type: ignore
|
|
|
|
stake_currency: Mapped[Optional[str]] = mapped_column(String(25), nullable=True) # type: ignore
|
|
|
|
is_open: Mapped[bool] = mapped_column(nullable=False, default=True, index=True) # type: ignore
|
|
|
|
fee_open: Mapped[float] = mapped_column(Float(), nullable=False, default=0.0) # type: ignore
|
|
|
|
fee_open_cost: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
|
|
|
|
fee_open_currency: Mapped[Optional[str]] = mapped_column(
|
|
|
|
String(25), nullable=True) # type: ignore
|
|
|
|
fee_close: Mapped[Optional[float]] = mapped_column(
|
|
|
|
Float(), nullable=False, default=0.0) # type: ignore
|
|
|
|
fee_close_cost: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
|
|
|
|
fee_close_currency: Mapped[Optional[str]] = mapped_column(
|
|
|
|
String(25), nullable=True) # type: ignore
|
|
|
|
open_rate: Mapped[float] = mapped_column(Float()) # type: ignore
|
|
|
|
open_rate_requested: Mapped[Optional[float]] = mapped_column(
|
|
|
|
Float(), nullable=True) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
# open_trade_value - calculated via _calc_open_trade_value
|
2023-03-01 18:48:15 +00:00
|
|
|
open_trade_value: Mapped[float] = mapped_column(Float(), nullable=True) # type: ignore
|
|
|
|
close_rate: Mapped[Optional[float]] = mapped_column(Float()) # type: ignore
|
|
|
|
close_rate_requested: Mapped[Optional[float]] = mapped_column(Float()) # type: ignore
|
|
|
|
realized_profit: Mapped[float] = mapped_column(
|
|
|
|
Float(), default=0.0, nullable=True) # type: ignore
|
|
|
|
close_profit: Mapped[Optional[float]] = mapped_column(Float()) # type: ignore
|
|
|
|
close_profit_abs: Mapped[Optional[float]] = mapped_column(Float()) # type: ignore
|
|
|
|
stake_amount: Mapped[float] = mapped_column(Float(), nullable=False) # type: ignore
|
|
|
|
max_stake_amount: Mapped[Optional[float]] = mapped_column(Float()) # type: ignore
|
|
|
|
amount: Mapped[float] = mapped_column(Float()) # type: ignore
|
|
|
|
amount_requested: Mapped[Optional[float]] = mapped_column(Float()) # type: ignore
|
|
|
|
open_date: Mapped[datetime] = mapped_column(
|
|
|
|
nullable=False, default=datetime.utcnow) # type: ignore
|
|
|
|
close_date: Mapped[Optional[datetime]] = mapped_column() # type: ignore
|
|
|
|
open_order_id: Mapped[Optional[str]] = mapped_column(String(255), nullable=True) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
# absolute value of the stop loss
|
2023-03-01 18:48:15 +00:00
|
|
|
stop_loss: Mapped[float] = mapped_column(Float(), nullable=True, default=0.0) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
# percentage value of the stop loss
|
2023-03-01 18:48:15 +00:00
|
|
|
stop_loss_pct: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
# absolute value of the initial stop loss
|
2023-03-01 18:48:15 +00:00
|
|
|
initial_stop_loss: Mapped[Optional[float]] = mapped_column(
|
|
|
|
Float(), nullable=True, default=0.0) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
# percentage value of the initial stop loss
|
2023-03-01 18:48:15 +00:00
|
|
|
initial_stop_loss_pct: Mapped[Optional[float]] = mapped_column(
|
|
|
|
Float(), nullable=True) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
# stoploss order id which is on exchange
|
2023-03-01 18:48:15 +00:00
|
|
|
stoploss_order_id: Mapped[Optional[str]] = mapped_column(
|
|
|
|
String(255), nullable=True, index=True) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
# last update time of the stoploss order on exchange
|
2023-03-01 18:48:15 +00:00
|
|
|
stoploss_last_update: Mapped[Optional[datetime]] = mapped_column(nullable=True) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
# absolute value of the highest reached price
|
2023-03-01 18:48:15 +00:00
|
|
|
max_rate: Mapped[Optional[float]] = mapped_column(
|
|
|
|
Float(), nullable=True, default=0.0) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
# Lowest price reached
|
2023-03-01 18:48:15 +00:00
|
|
|
min_rate: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
|
|
|
|
exit_reason: Mapped[Optional[str]] = mapped_column(String(100), nullable=True) # type: ignore
|
|
|
|
exit_order_status: Mapped[Optional[str]] = mapped_column(
|
|
|
|
String(100), nullable=True) # type: ignore
|
|
|
|
strategy: Mapped[Optional[str]] = mapped_column(String(100), nullable=True) # type: ignore
|
|
|
|
enter_tag: Mapped[Optional[str]] = mapped_column(String(100), nullable=True) # type: ignore
|
|
|
|
timeframe: Mapped[Optional[int]] = mapped_column(Integer, nullable=True) # type: ignore
|
|
|
|
|
|
|
|
trading_mode: Mapped[TradingMode] = mapped_column(
|
|
|
|
Enum(TradingMode), nullable=True) # type: ignore
|
|
|
|
amount_precision: Mapped[Optional[float]] = mapped_column(
|
|
|
|
Float(), nullable=True) # type: ignore
|
|
|
|
price_precision: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
|
|
|
|
precision_mode: Mapped[Optional[int]] = mapped_column(Integer, nullable=True) # type: ignore
|
|
|
|
contract_size: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
# Leverage trading properties
|
2023-03-01 18:48:15 +00:00
|
|
|
leverage: Mapped[float] = mapped_column(Float(), nullable=True, default=1.0) # type: ignore
|
|
|
|
is_short: Mapped[bool] = mapped_column(nullable=False, default=False) # type: ignore
|
|
|
|
liquidation_price: Mapped[Optional[float]] = mapped_column(
|
|
|
|
Float(), nullable=True) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
# Margin Trading Properties
|
2023-03-01 18:48:15 +00:00
|
|
|
interest_rate: Mapped[float] = mapped_column(
|
|
|
|
Float(), nullable=False, default=0.0) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
# Futures properties
|
2023-03-01 18:48:15 +00:00
|
|
|
funding_fees: Mapped[Optional[float]] = mapped_column(
|
|
|
|
Float(), nullable=True, default=None) # type: ignore
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
def __init__(self, **kwargs):
|
|
|
|
super().__init__(**kwargs)
|
2022-07-31 12:19:04 +00:00
|
|
|
self.realized_profit = 0
|
2022-05-08 15:45:20 +00:00
|
|
|
self.recalc_open_trade_value()
|
|
|
|
|
|
|
|
def delete(self) -> None:
|
|
|
|
|
|
|
|
for order in self.orders:
|
2023-03-15 20:12:06 +00:00
|
|
|
Order.session.delete(order)
|
2022-05-08 15:45:20 +00:00
|
|
|
|
2023-03-15 20:12:06 +00:00
|
|
|
Trade.session.delete(self)
|
2022-05-08 15:45:20 +00:00
|
|
|
Trade.commit()
|
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def commit():
|
2023-03-15 20:12:06 +00:00
|
|
|
Trade.session.commit()
|
2022-05-08 15:45:20 +00:00
|
|
|
|
2022-08-06 13:08:13 +00:00
|
|
|
@staticmethod
|
|
|
|
def rollback():
|
2023-03-15 20:12:06 +00:00
|
|
|
Trade.session.rollback()
|
2022-08-06 13:08:13 +00:00
|
|
|
|
2022-05-08 15:45:20 +00:00
|
|
|
@staticmethod
|
2023-01-21 14:01:56 +00:00
|
|
|
def get_trades_proxy(*, pair: Optional[str] = None, is_open: Optional[bool] = None,
|
|
|
|
open_date: Optional[datetime] = None,
|
|
|
|
close_date: Optional[datetime] = None,
|
2023-03-01 06:23:26 +00:00
|
|
|
) -> List['LocalTrade']:
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
|
|
|
Helper function to query Trades.j
|
|
|
|
Returns a List of trades, filtered on the parameters given.
|
|
|
|
In live mode, converts the filter to a database query and returns all rows
|
|
|
|
In Backtest mode, uses filters on Trade.trades to get the result.
|
|
|
|
|
|
|
|
:return: unsorted List[Trade]
|
|
|
|
"""
|
|
|
|
if Trade.use_db:
|
|
|
|
trade_filter = []
|
|
|
|
if pair:
|
|
|
|
trade_filter.append(Trade.pair == pair)
|
|
|
|
if open_date:
|
|
|
|
trade_filter.append(Trade.open_date > open_date)
|
|
|
|
if close_date:
|
|
|
|
trade_filter.append(Trade.close_date > close_date)
|
|
|
|
if is_open is not None:
|
|
|
|
trade_filter.append(Trade.is_open.is_(is_open))
|
2023-03-01 06:23:26 +00:00
|
|
|
return cast(List[LocalTrade], Trade.get_trades(trade_filter).all())
|
2022-05-08 15:45:20 +00:00
|
|
|
else:
|
|
|
|
return LocalTrade.get_trades_proxy(
|
|
|
|
pair=pair, is_open=is_open,
|
|
|
|
open_date=open_date,
|
|
|
|
close_date=close_date
|
|
|
|
)
|
|
|
|
|
|
|
|
@staticmethod
|
2023-03-15 20:09:25 +00:00
|
|
|
def get_trades_query(trade_filter=None, include_orders: bool = True) -> Select:
|
2022-05-08 15:45:20 +00:00
|
|
|
"""
|
|
|
|
Helper function to query Trades using filters.
|
|
|
|
NOTE: Not supported in Backtesting.
|
|
|
|
:param trade_filter: Optional filter to apply to trades
|
|
|
|
Can be either a Filter object, or a List of filters
|
|
|
|
e.g. `(trade_filter=[Trade.id == trade_id, Trade.is_open.is_(True),])`
|
|
|
|
e.g. `(trade_filter=Trade.id == trade_id)`
|
|
|
|
:return: unsorted query object
|
|
|
|
"""
|
|
|
|
if not Trade.use_db:
|
|
|
|
raise NotImplementedError('`Trade.get_trades()` not supported in backtesting mode.')
|
|
|
|
if trade_filter is not None:
|
|
|
|
if not isinstance(trade_filter, list):
|
|
|
|
trade_filter = [trade_filter]
|
2023-03-15 20:00:30 +00:00
|
|
|
this_query = select(Trade).filter(*trade_filter)
|
2022-05-08 15:45:20 +00:00
|
|
|
else:
|
2023-03-15 20:00:30 +00:00
|
|
|
this_query = select(Trade)
|
2022-06-19 14:13:00 +00:00
|
|
|
if not include_orders:
|
|
|
|
# Don't load order relations
|
|
|
|
# Consider using noload or raiseload instead of lazyload
|
|
|
|
this_query = this_query.options(lazyload(Trade.orders))
|
|
|
|
return this_query
|
2022-05-08 15:45:20 +00:00
|
|
|
|
2023-03-15 20:00:30 +00:00
|
|
|
@staticmethod
|
2023-03-15 20:09:25 +00:00
|
|
|
def get_trades(trade_filter=None, include_orders: bool = True) -> ScalarResult['Trade']:
|
2023-03-15 20:00:30 +00:00
|
|
|
"""
|
|
|
|
Helper function to query Trades using filters.
|
|
|
|
NOTE: Not supported in Backtesting.
|
|
|
|
:param trade_filter: Optional filter to apply to trades
|
|
|
|
Can be either a Filter object, or a List of filters
|
|
|
|
e.g. `(trade_filter=[Trade.id == trade_id, Trade.is_open.is_(True),])`
|
|
|
|
e.g. `(trade_filter=Trade.id == trade_id)`
|
|
|
|
:return: unsorted query object
|
|
|
|
"""
|
2023-03-15 20:12:06 +00:00
|
|
|
return Trade.session.scalars(Trade.get_trades_query(trade_filter, include_orders))
|
2023-03-15 20:00:30 +00:00
|
|
|
|
2022-05-08 15:45:20 +00:00
|
|
|
@staticmethod
|
|
|
|
def get_open_order_trades() -> List['Trade']:
|
|
|
|
"""
|
|
|
|
Returns all open trades
|
|
|
|
NOTE: Not supported in Backtesting.
|
|
|
|
"""
|
2023-03-15 20:09:25 +00:00
|
|
|
return cast(List[Trade], Trade.get_trades(Trade.open_order_id.isnot(None)).all())
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def get_open_trades_without_assigned_fees():
|
|
|
|
"""
|
|
|
|
Returns all open trades which don't have open fees set correctly
|
|
|
|
NOTE: Not supported in Backtesting.
|
|
|
|
"""
|
|
|
|
return Trade.get_trades([Trade.fee_open_currency.is_(None),
|
|
|
|
Trade.orders.any(),
|
|
|
|
Trade.is_open.is_(True),
|
|
|
|
]).all()
|
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def get_closed_trades_without_assigned_fees():
|
|
|
|
"""
|
|
|
|
Returns all closed trades which don't have fees set correctly
|
|
|
|
NOTE: Not supported in Backtesting.
|
|
|
|
"""
|
|
|
|
return Trade.get_trades([Trade.fee_close_currency.is_(None),
|
|
|
|
Trade.orders.any(),
|
|
|
|
Trade.is_open.is_(False),
|
|
|
|
]).all()
|
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def get_total_closed_profit() -> float:
|
|
|
|
"""
|
|
|
|
Retrieves total realized profit
|
|
|
|
"""
|
|
|
|
if Trade.use_db:
|
2023-03-15 20:12:06 +00:00
|
|
|
total_profit: float = Trade.session.execute(
|
2023-03-15 20:00:30 +00:00
|
|
|
select(func.sum(Trade.close_profit_abs)).filter(Trade.is_open.is_(False))
|
2023-03-15 20:09:25 +00:00
|
|
|
).scalar_one()
|
2022-05-08 15:45:20 +00:00
|
|
|
else:
|
2023-03-15 20:09:25 +00:00
|
|
|
total_profit = sum(t.close_profit_abs # type: ignore
|
|
|
|
for t in LocalTrade.get_trades_proxy(is_open=False))
|
2022-05-08 15:45:20 +00:00
|
|
|
return total_profit or 0
|
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def total_open_trades_stakes() -> float:
|
|
|
|
"""
|
|
|
|
Calculates total invested amount in open trades
|
|
|
|
in stake currency
|
|
|
|
"""
|
|
|
|
if Trade.use_db:
|
2023-03-15 20:12:06 +00:00
|
|
|
total_open_stake_amount = Trade.session.scalar(
|
2023-03-15 20:00:30 +00:00
|
|
|
select(func.sum(Trade.stake_amount)).filter(Trade.is_open.is_(True))
|
|
|
|
)
|
2022-05-08 15:45:20 +00:00
|
|
|
else:
|
|
|
|
total_open_stake_amount = sum(
|
|
|
|
t.stake_amount for t in LocalTrade.get_trades_proxy(is_open=True))
|
|
|
|
return total_open_stake_amount or 0
|
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def get_overall_performance(minutes=None) -> List[Dict[str, Any]]:
|
|
|
|
"""
|
|
|
|
Returns List of dicts containing all Trades, including profit and trade count
|
|
|
|
NOTE: Not supported in Backtesting.
|
|
|
|
"""
|
2023-02-14 10:04:36 +00:00
|
|
|
filters: List = [Trade.is_open.is_(False)]
|
2022-05-08 15:45:20 +00:00
|
|
|
if minutes:
|
|
|
|
start_date = datetime.now(timezone.utc) - timedelta(minutes=minutes)
|
|
|
|
filters.append(Trade.close_date >= start_date)
|
2023-03-15 20:00:30 +00:00
|
|
|
|
2023-03-15 20:12:06 +00:00
|
|
|
pair_rates = Trade.session.execute(
|
2023-03-15 20:00:30 +00:00
|
|
|
select(
|
|
|
|
Trade.pair,
|
|
|
|
func.sum(Trade.close_profit).label('profit_sum'),
|
|
|
|
func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
|
|
|
|
func.count(Trade.pair).label('count')
|
|
|
|
).filter(*filters)
|
|
|
|
.group_by(Trade.pair)
|
|
|
|
.order_by(desc('profit_sum_abs'))
|
|
|
|
).all()
|
|
|
|
|
2022-05-08 15:45:20 +00:00
|
|
|
return [
|
|
|
|
{
|
|
|
|
'pair': pair,
|
|
|
|
'profit_ratio': profit,
|
|
|
|
'profit': round(profit * 100, 2), # Compatibility mode
|
|
|
|
'profit_pct': round(profit * 100, 2),
|
|
|
|
'profit_abs': profit_abs,
|
|
|
|
'count': count
|
|
|
|
}
|
|
|
|
for pair, profit, profit_abs, count in pair_rates
|
|
|
|
]
|
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def get_enter_tag_performance(pair: Optional[str]) -> List[Dict[str, Any]]:
|
|
|
|
"""
|
|
|
|
Returns List of dicts containing all Trades, based on buy tag performance
|
|
|
|
Can either be average for all pairs or a specific pair provided
|
|
|
|
NOTE: Not supported in Backtesting.
|
|
|
|
"""
|
|
|
|
|
2023-02-14 10:04:36 +00:00
|
|
|
filters: List = [Trade.is_open.is_(False)]
|
2022-08-01 04:43:59 +00:00
|
|
|
if (pair is not None):
|
2022-05-08 15:45:20 +00:00
|
|
|
filters.append(Trade.pair == pair)
|
|
|
|
|
2023-03-15 20:12:06 +00:00
|
|
|
enter_tag_perf = Trade.session.execute(
|
2023-03-15 20:00:30 +00:00
|
|
|
select(
|
|
|
|
Trade.enter_tag,
|
|
|
|
func.sum(Trade.close_profit).label('profit_sum'),
|
|
|
|
func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
|
|
|
|
func.count(Trade.pair).label('count')
|
|
|
|
).filter(*filters)
|
|
|
|
.group_by(Trade.enter_tag)
|
|
|
|
.order_by(desc('profit_sum_abs'))
|
|
|
|
).all()
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
return [
|
|
|
|
{
|
|
|
|
'enter_tag': enter_tag if enter_tag is not None else "Other",
|
|
|
|
'profit_ratio': profit,
|
|
|
|
'profit_pct': round(profit * 100, 2),
|
|
|
|
'profit_abs': profit_abs,
|
|
|
|
'count': count
|
|
|
|
}
|
|
|
|
for enter_tag, profit, profit_abs, count in enter_tag_perf
|
|
|
|
]
|
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def get_exit_reason_performance(pair: Optional[str]) -> List[Dict[str, Any]]:
|
|
|
|
"""
|
|
|
|
Returns List of dicts containing all Trades, based on exit reason performance
|
|
|
|
Can either be average for all pairs or a specific pair provided
|
|
|
|
NOTE: Not supported in Backtesting.
|
|
|
|
"""
|
|
|
|
|
2023-02-14 10:04:36 +00:00
|
|
|
filters: List = [Trade.is_open.is_(False)]
|
2022-08-01 04:43:59 +00:00
|
|
|
if (pair is not None):
|
2022-05-08 15:45:20 +00:00
|
|
|
filters.append(Trade.pair == pair)
|
2023-03-15 20:12:06 +00:00
|
|
|
sell_tag_perf = Trade.session.execute(
|
2023-03-15 20:00:30 +00:00
|
|
|
select(
|
|
|
|
Trade.exit_reason,
|
|
|
|
func.sum(Trade.close_profit).label('profit_sum'),
|
|
|
|
func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
|
|
|
|
func.count(Trade.pair).label('count')
|
|
|
|
).filter(*filters)
|
|
|
|
.group_by(Trade.exit_reason)
|
|
|
|
.order_by(desc('profit_sum_abs'))
|
|
|
|
).all()
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
return [
|
|
|
|
{
|
|
|
|
'exit_reason': exit_reason if exit_reason is not None else "Other",
|
|
|
|
'profit_ratio': profit,
|
|
|
|
'profit_pct': round(profit * 100, 2),
|
|
|
|
'profit_abs': profit_abs,
|
|
|
|
'count': count
|
|
|
|
}
|
|
|
|
for exit_reason, profit, profit_abs, count in sell_tag_perf
|
|
|
|
]
|
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def get_mix_tag_performance(pair: Optional[str]) -> List[Dict[str, Any]]:
|
|
|
|
"""
|
|
|
|
Returns List of dicts containing all Trades, based on entry_tag + exit_reason performance
|
|
|
|
Can either be average for all pairs or a specific pair provided
|
|
|
|
NOTE: Not supported in Backtesting.
|
|
|
|
"""
|
|
|
|
|
2023-02-14 10:04:36 +00:00
|
|
|
filters: List = [Trade.is_open.is_(False)]
|
2022-08-01 04:43:59 +00:00
|
|
|
if (pair is not None):
|
2022-05-08 15:45:20 +00:00
|
|
|
filters.append(Trade.pair == pair)
|
2023-03-15 20:12:06 +00:00
|
|
|
mix_tag_perf = Trade.session.execute(
|
2023-03-15 20:00:30 +00:00
|
|
|
select(
|
|
|
|
Trade.id,
|
|
|
|
Trade.enter_tag,
|
|
|
|
Trade.exit_reason,
|
|
|
|
func.sum(Trade.close_profit).label('profit_sum'),
|
|
|
|
func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
|
|
|
|
func.count(Trade.pair).label('count')
|
|
|
|
).filter(*filters)
|
|
|
|
.group_by(Trade.id)
|
|
|
|
.order_by(desc('profit_sum_abs'))
|
|
|
|
).all()
|
2022-05-08 15:45:20 +00:00
|
|
|
|
|
|
|
return_list: List[Dict] = []
|
|
|
|
for id, enter_tag, exit_reason, profit, profit_abs, count in mix_tag_perf:
|
|
|
|
enter_tag = enter_tag if enter_tag is not None else "Other"
|
|
|
|
exit_reason = exit_reason if exit_reason is not None else "Other"
|
|
|
|
|
2022-08-01 04:43:59 +00:00
|
|
|
if (exit_reason is not None and enter_tag is not None):
|
2022-05-08 15:45:20 +00:00
|
|
|
mix_tag = enter_tag + " " + exit_reason
|
|
|
|
i = 0
|
|
|
|
if not any(item["mix_tag"] == mix_tag for item in return_list):
|
|
|
|
return_list.append({'mix_tag': mix_tag,
|
|
|
|
'profit': profit,
|
|
|
|
'profit_pct': round(profit * 100, 2),
|
|
|
|
'profit_abs': profit_abs,
|
|
|
|
'count': count})
|
|
|
|
else:
|
|
|
|
while i < len(return_list):
|
|
|
|
if return_list[i]["mix_tag"] == mix_tag:
|
|
|
|
return_list[i] = {
|
|
|
|
'mix_tag': mix_tag,
|
|
|
|
'profit': profit + return_list[i]["profit"],
|
|
|
|
'profit_pct': round(profit + return_list[i]["profit"] * 100, 2),
|
|
|
|
'profit_abs': profit_abs + return_list[i]["profit_abs"],
|
|
|
|
'count': 1 + return_list[i]["count"]}
|
|
|
|
i += 1
|
|
|
|
|
|
|
|
return return_list
|
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def get_best_pair(start_date: datetime = datetime.fromtimestamp(0)):
|
|
|
|
"""
|
|
|
|
Get best pair with closed trade.
|
|
|
|
NOTE: Not supported in Backtesting.
|
|
|
|
:returns: Tuple containing (pair, profit_sum)
|
|
|
|
"""
|
2023-03-15 20:12:06 +00:00
|
|
|
best_pair = Trade.session.execute(
|
2023-03-15 20:00:30 +00:00
|
|
|
select(
|
|
|
|
Trade.pair,
|
|
|
|
func.sum(Trade.close_profit).label('profit_sum')
|
|
|
|
).filter(Trade.is_open.is_(False) & (Trade.close_date >= start_date))
|
|
|
|
.group_by(Trade.pair)
|
|
|
|
.order_by(desc('profit_sum'))
|
|
|
|
).first()
|
|
|
|
|
2022-05-08 15:45:20 +00:00
|
|
|
return best_pair
|
2022-06-18 09:40:32 +00:00
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def get_trading_volume(start_date: datetime = datetime.fromtimestamp(0)) -> float:
|
|
|
|
"""
|
|
|
|
Get Trade volume based on Orders
|
|
|
|
NOTE: Not supported in Backtesting.
|
|
|
|
:returns: Tuple containing (pair, profit_sum)
|
|
|
|
"""
|
2023-03-16 05:48:12 +00:00
|
|
|
trading_volume = Trade.session.execute(
|
|
|
|
select(
|
|
|
|
func.sum(Order.cost).label('volume')
|
|
|
|
).filter(
|
|
|
|
Order.order_filled_date >= start_date,
|
|
|
|
Order.status == 'closed'
|
|
|
|
)).scalar_one()
|
2022-06-18 09:40:32 +00:00
|
|
|
return trading_volume
|
2022-10-20 18:33:08 +00:00
|
|
|
|
|
|
|
@staticmethod
|
|
|
|
def from_json(json_str: str) -> 'Trade':
|
|
|
|
"""
|
|
|
|
Create a Trade instance from a json string.
|
|
|
|
|
|
|
|
Used for debugging purposes - please keep.
|
|
|
|
:param json_str: json string to parse
|
|
|
|
:return: Trade instance
|
|
|
|
"""
|
|
|
|
import rapidjson
|
|
|
|
data = rapidjson.loads(json_str)
|
|
|
|
trade = Trade(
|
|
|
|
id=data["trade_id"],
|
|
|
|
pair=data["pair"],
|
|
|
|
base_currency=data["base_currency"],
|
|
|
|
stake_currency=data["quote_currency"],
|
|
|
|
is_open=data["is_open"],
|
|
|
|
exchange=data["exchange"],
|
|
|
|
amount=data["amount"],
|
|
|
|
amount_requested=data["amount_requested"],
|
|
|
|
stake_amount=data["stake_amount"],
|
|
|
|
strategy=data["strategy"],
|
|
|
|
enter_tag=data["enter_tag"],
|
|
|
|
timeframe=data["timeframe"],
|
|
|
|
fee_open=data["fee_open"],
|
|
|
|
fee_open_cost=data["fee_open_cost"],
|
|
|
|
fee_open_currency=data["fee_open_currency"],
|
|
|
|
fee_close=data["fee_close"],
|
|
|
|
fee_close_cost=data["fee_close_cost"],
|
|
|
|
fee_close_currency=data["fee_close_currency"],
|
|
|
|
open_date=datetime.fromtimestamp(data["open_timestamp"] // 1000, tz=timezone.utc),
|
|
|
|
open_rate=data["open_rate"],
|
|
|
|
open_rate_requested=data["open_rate_requested"],
|
|
|
|
open_trade_value=data["open_trade_value"],
|
|
|
|
close_date=(datetime.fromtimestamp(data["close_timestamp"] // 1000, tz=timezone.utc)
|
|
|
|
if data["close_timestamp"] else None),
|
|
|
|
realized_profit=data["realized_profit"],
|
|
|
|
close_rate=data["close_rate"],
|
|
|
|
close_rate_requested=data["close_rate_requested"],
|
|
|
|
close_profit=data["close_profit"],
|
|
|
|
close_profit_abs=data["close_profit_abs"],
|
|
|
|
exit_reason=data["exit_reason"],
|
|
|
|
exit_order_status=data["exit_order_status"],
|
|
|
|
stop_loss=data["stop_loss_abs"],
|
|
|
|
stop_loss_pct=data["stop_loss_ratio"],
|
|
|
|
stoploss_order_id=data["stoploss_order_id"],
|
2023-03-25 19:26:56 +00:00
|
|
|
stoploss_last_update=(
|
|
|
|
datetime.fromtimestamp(data["stoploss_last_update_timestamp"] // 1000,
|
|
|
|
tz=timezone.utc)
|
|
|
|
if data["stoploss_last_update_timestamp"] else None),
|
2022-10-20 18:33:08 +00:00
|
|
|
initial_stop_loss=data["initial_stop_loss_abs"],
|
|
|
|
initial_stop_loss_pct=data["initial_stop_loss_ratio"],
|
|
|
|
min_rate=data["min_rate"],
|
|
|
|
max_rate=data["max_rate"],
|
|
|
|
leverage=data["leverage"],
|
|
|
|
interest_rate=data["interest_rate"],
|
|
|
|
liquidation_price=data["liquidation_price"],
|
|
|
|
is_short=data["is_short"],
|
|
|
|
trading_mode=data["trading_mode"],
|
|
|
|
funding_fees=data["funding_fees"],
|
|
|
|
open_order_id=data["open_order_id"],
|
|
|
|
)
|
|
|
|
for order in data["orders"]:
|
|
|
|
|
|
|
|
order_obj = Order(
|
|
|
|
amount=order["amount"],
|
|
|
|
ft_order_side=order["ft_order_side"],
|
|
|
|
ft_pair=order["pair"],
|
|
|
|
ft_is_open=order["is_open"],
|
|
|
|
order_id=order["order_id"],
|
|
|
|
status=order["status"],
|
|
|
|
average=order["average"],
|
|
|
|
cost=order["cost"],
|
|
|
|
filled=order["filled"],
|
2022-10-21 05:01:47 +00:00
|
|
|
order_date=datetime.strptime(order["order_date"], DATETIME_PRINT_FORMAT),
|
2022-10-20 18:33:08 +00:00
|
|
|
order_filled_date=(datetime.fromtimestamp(
|
|
|
|
order["order_filled_timestamp"] // 1000, tz=timezone.utc)
|
|
|
|
if order["order_filled_timestamp"] else None),
|
|
|
|
order_type=order["order_type"],
|
|
|
|
price=order["price"],
|
|
|
|
remaining=order["remaining"],
|
|
|
|
)
|
|
|
|
trade.orders.append(order_obj)
|
|
|
|
|
|
|
|
return trade
|