freqtrade/persistence/trade_model.py
"""
This module contains the class to persist trades into SQLite
"""
import logging
from collections import defaultdict
from dataclasses import dataclass
from datetime import datetime, timedelta, timezone
from math import isclose
from typing import Any, ClassVar, Dict, List, Optional, Sequence, cast
from sqlalchemy import (Enum, Float, ForeignKey, Integer, ScalarResult, Select, String,
UniqueConstraint, desc, func, select)
from sqlalchemy.orm import Mapped, lazyload, mapped_column, relationship, validates
from typing_extensions import Self
from freqtrade.constants import (CANCELED_EXCHANGE_STATES, CUSTOM_TAG_MAX_LENGTH,
DATETIME_PRINT_FORMAT, MATH_CLOSE_PREC, NON_OPEN_EXCHANGE_STATES,
BuySell, LongShort)
from freqtrade.enums import ExitType, TradingMode
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.exchange import (ROUND_DOWN, ROUND_UP, amount_to_contract_precision,
price_to_precision)
from freqtrade.leverage import interest
from freqtrade.misc import safe_value_fallback
from freqtrade.persistence.base import ModelBase, SessionType
from freqtrade.persistence.custom_data import CustomDataWrapper, _CustomData
from freqtrade.util import FtPrecise, dt_from_ts, dt_now, dt_ts, dt_ts_none
logger = logging.getLogger(__name__)
@dataclass
class ProfitStruct:
profit_abs: float
profit_ratio: float
total_profit: float
total_profit_ratio: float
class Order(ModelBase):
"""
Order database model
Keeps a record of all orders placed on the exchange
One to many relationship with Trades:
- One trade can have many orders
- One Order can only be associated with one Trade
Mirrors CCXT Order structure
"""
__tablename__ = 'orders'
__allow_unmapped__ = True
session: ClassVar[SessionType]
# Uniqueness should be ensured over pair, order_id
# its likely that order_id is unique per Pair on some exchanges.
__table_args__ = (UniqueConstraint('ft_pair', 'order_id', name="_order_pair_order_id"),)
id: Mapped[int] = mapped_column(Integer, primary_key=True)
ft_trade_id: Mapped[int] = mapped_column(Integer, ForeignKey('trades.id'), index=True)
_trade_live: Mapped["Trade"] = relationship("Trade", back_populates="orders", lazy="immediate")
_trade_bt: "LocalTrade" = None # type: ignore
# order_side can only be 'buy', 'sell' or 'stoploss'
ft_order_side: Mapped[str] = mapped_column(String(25), nullable=False)
ft_pair: Mapped[str] = mapped_column(String(25), nullable=False)
ft_is_open: Mapped[bool] = mapped_column(nullable=False, default=True, index=True)
ft_amount: Mapped[float] = mapped_column(Float(), nullable=False)
ft_price: Mapped[float] = mapped_column(Float(), nullable=False)
ft_cancel_reason: Mapped[str] = mapped_column(String(CUSTOM_TAG_MAX_LENGTH), nullable=True)
order_id: Mapped[str] = mapped_column(String(255), nullable=False, index=True)
status: Mapped[Optional[str]] = mapped_column(String(255), nullable=True)
symbol: Mapped[Optional[str]] = mapped_column(String(25), nullable=True)
order_type: Mapped[Optional[str]] = mapped_column(String(50), nullable=True)
side: Mapped[str] = mapped_column(String(25), nullable=True)
price: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
average: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
amount: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
filled: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
remaining: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
cost: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
stop_price: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
order_date: Mapped[datetime] = mapped_column(nullable=True, default=dt_now)
order_filled_date: Mapped[Optional[datetime]] = mapped_column(nullable=True)
order_update_date: Mapped[Optional[datetime]] = mapped_column(nullable=True)
funding_fee: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
ft_fee_base: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
ft_order_tag: Mapped[Optional[str]] = mapped_column(String(CUSTOM_TAG_MAX_LENGTH),
nullable=True)
@property
def order_date_utc(self) -> datetime:
""" Order-date with UTC timezoneinfo"""
return self.order_date.replace(tzinfo=timezone.utc)
@property
def order_filled_utc(self) -> Optional[datetime]:
""" last order-date with UTC timezoneinfo"""
return (
self.order_filled_date.replace(tzinfo=timezone.utc) if self.order_filled_date else None
)
@property
def safe_amount(self) -> float:
return self.amount or self.ft_amount
@property
def safe_placement_price(self) -> float:
"""Price at which the order was placed"""
return self.price or self.stop_price or self.ft_price
@property
def safe_price(self) -> float:
return self.average or self.price or self.stop_price or self.ft_price
@property
def safe_filled(self) -> float:
return self.filled if self.filled is not None else 0.0
@property
def safe_cost(self) -> float:
return self.cost or 0.0
@property
def safe_remaining(self) -> float:
return (
self.remaining if self.remaining is not None else
self.safe_amount - (self.filled or 0.0)
)
@property
def safe_fee_base(self) -> float:
return self.ft_fee_base or 0.0
@property
def safe_amount_after_fee(self) -> float:
return self.safe_filled - self.safe_fee_base
@property
def trade(self) -> "LocalTrade":
return self._trade_bt or self._trade_live
@property
def stake_amount(self) -> float:
""" Amount in stake currency used for this order"""
return self.safe_amount * self.safe_price / self.trade.leverage
def __repr__(self):
return (f"Order(id={self.id}, trade={self.ft_trade_id}, order_id={self.order_id}, "
f"side={self.side}, filled={self.safe_filled}, price={self.safe_price}, "
f"status={self.status}, date={self.order_date_utc:{DATETIME_PRINT_FORMAT}})")
def update_from_ccxt_object(self, order):
"""
Update Order from ccxt response
Only updates if fields are available from ccxt -
"""
if self.order_id != str(order['id']):
raise DependencyException("Order-id's don't match")
self.status = safe_value_fallback(order, 'status', default_value=self.status)
self.symbol = safe_value_fallback(order, 'symbol', default_value=self.symbol)
self.order_type = safe_value_fallback(order, 'type', default_value=self.order_type)
self.side = safe_value_fallback(order, 'side', default_value=self.side)
self.price = safe_value_fallback(order, 'price', default_value=self.price)
self.amount = safe_value_fallback(order, 'amount', default_value=self.amount)
self.filled = safe_value_fallback(order, 'filled', default_value=self.filled)
self.average = safe_value_fallback(order, 'average', default_value=self.average)
self.remaining = safe_value_fallback(order, 'remaining', default_value=self.remaining)
self.cost = safe_value_fallback(order, 'cost', default_value=self.cost)
self.stop_price = safe_value_fallback(order, 'stopPrice', default_value=self.stop_price)
order_date = safe_value_fallback(order, 'timestamp')
if order_date:
self.order_date = datetime.fromtimestamp(order_date / 1000, tz=timezone.utc)
elif not self.order_date:
self.order_date = dt_now()
self.ft_is_open = True
if self.status in NON_OPEN_EXCHANGE_STATES:
self.ft_is_open = False
if (order.get('filled', 0.0) or 0.0) > 0 and not self.order_filled_date:
self.order_filled_date = dt_from_ts(
safe_value_fallback(order, 'lastTradeTimestamp', default_value=dt_ts())
)
self.order_update_date = datetime.now(timezone.utc)
def to_ccxt_object(self, stopPriceName: str = 'stopPrice') -> Dict[str, Any]:
order: Dict[str, Any] = {
'id': self.order_id,
'symbol': self.ft_pair,
'price': self.price,
'average': self.average,
'amount': self.amount,
'cost': self.cost,
'type': self.order_type,
'side': self.ft_order_side,
'filled': self.filled,
'remaining': self.remaining,
'datetime': self.order_date_utc.strftime('%Y-%m-%dT%H:%M:%S.%f'),
'timestamp': int(self.order_date_utc.timestamp() * 1000),
'status': self.status,
'fee': None,
'info': {},
}
if self.ft_order_side == 'stoploss':
order.update({
stopPriceName: self.stop_price,
'ft_order_type': 'stoploss',
})
return order
def to_json(self, entry_side: str, minified: bool = False) -> Dict[str, Any]:
"""
:param minified: If True, only return a subset of the data is returned.
Only used for backtesting.
"""
resp = {
'amount': self.safe_amount,
'safe_price': self.safe_price,
'ft_order_side': self.ft_order_side,
'order_filled_timestamp': dt_ts_none(self.order_filled_utc),
'ft_is_entry': self.ft_order_side == entry_side,
'ft_order_tag': self.ft_order_tag,
}
if not minified:
resp.update({
'pair': self.ft_pair,
'order_id': self.order_id,
'status': self.status,
'average': round(self.average, 8) if self.average else 0,
'cost': self.cost if self.cost else 0,
'filled': self.filled,
'is_open': self.ft_is_open,
'order_date': self.order_date.strftime(DATETIME_PRINT_FORMAT)
if self.order_date else None,
'order_timestamp': int(self.order_date.replace(
tzinfo=timezone.utc).timestamp() * 1000) if self.order_date else None,
'order_filled_date': self.order_filled_date.strftime(DATETIME_PRINT_FORMAT)
if self.order_filled_date else None,
'order_type': self.order_type,
'price': self.price,
'remaining': self.remaining,
'ft_fee_base': self.ft_fee_base,
'funding_fee': self.funding_fee,
})
return resp
def close_bt_order(self, close_date: datetime, trade: 'LocalTrade'):
self.order_filled_date = close_date
self.filled = self.amount
self.remaining = 0
self.status = 'closed'
self.ft_is_open = False
# Assign funding fees to Order.
# Assumes backtesting will use date_last_filled_utc to calculate future funding fees.
self.funding_fee = trade.funding_fee_running
trade.funding_fee_running = 0.0
if (self.ft_order_side == trade.entry_side and self.price):
trade.open_rate = self.price
trade.recalc_trade_from_orders()
if trade.nr_of_successful_entries == 1:
trade.initial_stop_loss_pct = None
trade.is_stop_loss_trailing = False
trade.adjust_stop_loss(trade.open_rate, trade.stop_loss_pct)
@staticmethod
def update_orders(orders: List['Order'], order: Dict[str, Any]):
"""
Get all non-closed orders - useful when trying to batch-update orders
"""
if not isinstance(order, dict):
logger.warning(f"{order} is not a valid response object.")
return
filtered_orders = [o for o in orders if o.order_id == order.get('id')]
if filtered_orders:
oobj = filtered_orders[0]
oobj.update_from_ccxt_object(order)
Trade.commit()
else:
logger.warning(f"Did not find order for {order}.")
@classmethod
def parse_from_ccxt_object(
cls, order: Dict[str, Any], pair: str, side: str,
amount: Optional[float] = None, price: Optional[float] = None) -> Self:
"""
Parse an order from a ccxt object and return a new order Object.
Optional support for overriding amount and price is only used for test simplification.
"""
o = cls(
order_id=str(order['id']),
ft_order_side=side,
ft_pair=pair,
ft_amount=amount if amount else order['amount'],
ft_price=price if price else order['price'],
)
o.update_from_ccxt_object(order)
return o
@staticmethod
def get_open_orders() -> Sequence['Order']:
"""
Retrieve open orders from the database
:return: List of open orders
"""
return Order.session.scalars(select(Order).filter(Order.ft_is_open.is_(True))).all()
@staticmethod
def order_by_id(order_id: str) -> Optional['Order']:
"""
Retrieve order based on order_id
:return: Order or None
"""
return Order.session.scalars(select(Order).filter(Order.order_id == order_id)).first()
class LocalTrade:
"""
Trade database model.
Used in backtesting - must be aligned to Trade model!
"""
use_db: bool = False
# Trades container for backtesting
trades: List['LocalTrade'] = []
trades_open: List['LocalTrade'] = []
# Copy of trades_open - but indexed by pair
bt_trades_open_pp: Dict[str, List['LocalTrade']] = defaultdict(list)
bt_open_open_trade_count: int = 0
total_profit: float = 0
realized_profit: float = 0
id: int = 0
orders: List[Order] = []
exchange: str = ''
pair: str = ''
base_currency: Optional[str] = ''
stake_currency: Optional[str] = ''
is_open: bool = True
fee_open: float = 0.0
fee_open_cost: Optional[float] = None
fee_open_currency: Optional[str] = ''
fee_close: Optional[float] = 0.0
fee_close_cost: Optional[float] = None
fee_close_currency: Optional[str] = ''
open_rate: float = 0.0
open_rate_requested: Optional[float] = None
# open_trade_value - calculated via _calc_open_trade_value
open_trade_value: float = 0.0
close_rate: Optional[float] = None
close_rate_requested: Optional[float] = None
close_profit: Optional[float] = None
close_profit_abs: Optional[float] = None
stake_amount: float = 0.0
max_stake_amount: Optional[float] = 0.0
amount: float = 0.0
amount_requested: Optional[float] = None
open_date: datetime
close_date: Optional[datetime] = None
# absolute value of the stop loss
stop_loss: float = 0.0
# percentage value of the stop loss
stop_loss_pct: Optional[float] = 0.0
# absolute value of the initial stop loss
initial_stop_loss: Optional[float] = 0.0
# percentage value of the initial stop loss
initial_stop_loss_pct: Optional[float] = None
is_stop_loss_trailing: bool = False
# absolute value of the highest reached price
max_rate: Optional[float] = None
# Lowest price reached
min_rate: Optional[float] = None
exit_reason: Optional[str] = ''
exit_order_status: Optional[str] = ''
strategy: Optional[str] = ''
enter_tag: Optional[str] = None
timeframe: Optional[int] = None
trading_mode: TradingMode = TradingMode.SPOT
amount_precision: Optional[float] = None
price_precision: Optional[float] = None
precision_mode: Optional[int] = None
contract_size: Optional[float] = None
# Leverage trading properties
liquidation_price: Optional[float] = None
is_short: bool = False
leverage: float = 1.0
# Margin trading properties
interest_rate: float = 0.0
# Futures properties
funding_fees: Optional[float] = None
# Used to keep running funding fees - between the last filled order and now
# Shall not be used for calculations!
funding_fee_running: Optional[float] = None
@property
def stoploss_or_liquidation(self) -> float:
if self.liquidation_price:
if self.is_short:
return min(self.stop_loss, self.liquidation_price)
else:
return max(self.stop_loss, self.liquidation_price)
return self.stop_loss
@property
def buy_tag(self) -> Optional[str]:
"""
Compatibility between buy_tag (old) and enter_tag (new)
Consider buy_tag deprecated
"""
return self.enter_tag
@property
def has_no_leverage(self) -> bool:
"""Returns true if this is a non-leverage, non-short trade"""
return ((self.leverage == 1.0 or self.leverage is None) and not self.is_short)
@property
def borrowed(self) -> float:
"""
The amount of currency borrowed from the exchange for leverage trades
If a long trade, the amount is in base currency
If a short trade, the amount is in the other currency being traded
"""
if self.has_no_leverage:
return 0.0
elif not self.is_short:
return (self.amount * self.open_rate) * ((self.leverage - 1) / self.leverage)
else:
return self.amount
@property
def _date_last_filled_utc(self) -> Optional[datetime]:
""" Date of the last filled order"""
orders = self.select_filled_orders()
if orders:
return max(o.order_filled_utc for o in orders if o.order_filled_utc)
return None
@property
def date_last_filled_utc(self) -> datetime:
""" Date of the last filled order - or open_date if no orders are filled"""
dt_last_filled = self._date_last_filled_utc
if not dt_last_filled:
return self.open_date_utc
return max([self.open_date_utc, dt_last_filled])
@property
def date_entry_fill_utc(self) -> Optional[datetime]:
""" Date of the first filled order"""
orders = self.select_filled_orders(self.entry_side)
if (
orders
and len(filled_date := [o.order_filled_utc for o in orders if o.order_filled_utc])
):
return min(filled_date)
return None
@property
def open_date_utc(self):
return self.open_date.replace(tzinfo=timezone.utc)
@property
def stoploss_last_update_utc(self):
if self.has_open_sl_orders:
return max(o.order_date_utc for o in self.open_sl_orders)
return None
@property
def close_date_utc(self):
return self.close_date.replace(tzinfo=timezone.utc) if self.close_date else None
@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 ''
@property
def open_orders(self) -> List[Order]:
"""
All open orders for this trade excluding stoploss orders
"""
return [o for o in self.orders if o.ft_is_open and o.ft_order_side != 'stoploss']
@property
def has_open_orders(self) -> bool:
"""
True if there are open orders for this trade excluding stoploss orders
"""
open_orders_wo_sl = [
o for o in self.orders
if o.ft_order_side not in ['stoploss'] and o.ft_is_open
]
return len(open_orders_wo_sl) > 0
@property
def open_sl_orders(self) -> List[Order]:
"""
All open stoploss orders for this trade
"""
return [
o for o in self.orders
if o.ft_order_side in ['stoploss'] and o.ft_is_open
]
@property
def has_open_sl_orders(self) -> bool:
"""
True if there are open stoploss orders for this trade
"""
open_sl_orders = [
o for o in self.orders
if o.ft_order_side in ['stoploss'] and o.ft_is_open
]
return len(open_sl_orders) > 0
@property
def sl_orders(self) -> List[Order]:
"""
All stoploss orders for this trade
"""
return [
o for o in self.orders
if o.ft_order_side in ['stoploss']
]
@property
def open_orders_ids(self) -> List[str]:
open_orders_ids_wo_sl = [
oo.order_id for oo in self.open_orders
if oo.ft_order_side not in ['stoploss']
]
return open_orders_ids_wo_sl
def __init__(self, **kwargs):
for key in kwargs:
setattr(self, key, kwargs[key])
self.recalc_open_trade_value()
self.orders = []
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_utc.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})'
)
def to_json(self, minified: bool = False) -> Dict[str, Any]:
"""
:param minified: If True, only return a subset of the data is returned.
Only used for backtesting.
:return: Dictionary with trade data
"""
filled_or_open_orders = self.select_filled_or_open_orders()
orders_json = [order.to_json(self.entry_side, minified) for order in filled_or_open_orders]
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),
'max_stake_amount': round(self.max_stake_amount, 8) if self.max_stake_amount else None,
'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': dt_ts_none(self.open_date_utc),
'open_fill_date': (self.date_entry_fill_utc.strftime(DATETIME_PRINT_FORMAT)
if self.date_entry_fill_utc else None),
'open_fill_timestamp': dt_ts_none(self.date_entry_fill_utc),
'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': dt_ts_none(self.close_date_utc),
'realized_profit': self.realized_profit or 0.0,
# Close-profit corresponds to relative realized_profit ratio
'realized_profit_ratio': self.close_profit or None,
'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_last_update': (self.stoploss_last_update_utc.strftime(DATETIME_PRINT_FORMAT)
if self.stoploss_last_update_utc else None),
'stoploss_last_update_timestamp': dt_ts_none(self.stoploss_last_update_utc),
'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,
'amount_precision': self.amount_precision,
'price_precision': self.price_precision,
'precision_mode': self.precision_mode,
'contract_size': self.contract_size,
'has_open_orders': self.has_open_orders,
'orders': orders_json,
}
@staticmethod
def reset_trades() -> None:
"""
Resets all trades. Only active for backtesting mode.
"""
LocalTrade.trades = []
LocalTrade.trades_open = []
LocalTrade.bt_trades_open_pp = defaultdict(list)
LocalTrade.bt_open_open_trade_count = 0
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)
def set_liquidation_price(self, liquidation_price: Optional[float]):
"""
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
def set_funding_fees(self, funding_fee: float) -> None:
"""
Assign funding fees to Trade.
"""
if funding_fee is None:
return
self.funding_fee_running = funding_fee
prior_funding_fees = sum([o.funding_fee for o in self.orders if o.funding_fee])
self.funding_fees = prior_funding_fees + funding_fee
def __set_stop_loss(self, stop_loss: float, percent: float):
"""
Method used internally to set self.stop_loss.
"""
if not self.stop_loss:
self.initial_stop_loss = stop_loss
self.stop_loss = stop_loss
self.stop_loss_pct = -1 * abs(percent)
def adjust_stop_loss(self, current_price: float, stoploss: Optional[float],
initial: bool = False, allow_refresh: bool = False) -> None:
"""
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.
:param refresh: Called to refresh stop_loss, allows adjustment in both directions
"""
if stoploss is None or (initial and not (self.stop_loss is None or self.stop_loss == 0)):
# Don't modify if called with initial and nothing to do
return
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)))
stop_loss_norm = price_to_precision(new_loss, self.price_precision, self.precision_mode,
rounding_mode=ROUND_DOWN if self.is_short else ROUND_UP)
# no stop loss assigned yet
if self.initial_stop_loss_pct is None:
self.__set_stop_loss(stop_loss_norm, stoploss)
self.initial_stop_loss = price_to_precision(
stop_loss_norm, self.price_precision, self.precision_mode,
rounding_mode=ROUND_DOWN if self.is_short else ROUND_UP)
self.initial_stop_loss_pct = -1 * abs(stoploss)
# evaluate if the stop loss needs to be updated
else:
higher_stop = stop_loss_norm > self.stop_loss
lower_stop = stop_loss_norm < 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 (
allow_refresh
or (higher_stop and not self.is_short)
or (lower_stop and self.is_short)
):
logger.debug(f"{self.pair} - Adjusting stoploss...")
if not allow_refresh:
self.is_stop_loss_trailing = True
self.__set_stop_loss(stop_loss_norm, stoploss)
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: "
f"{float(self.stop_loss) - float(self.initial_stop_loss or 0.0):.8f}.")
def update_trade(self, order: Order, recalculating: bool = False) -> 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 != 'stoploss':
order.funding_fee = self.funding_fee_running
# Reset running funding fees
self.funding_fee_running = 0.0
order_type = order.order_type.upper() if order.order_type else None
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_type}_{payment} has been fulfilled for {self}.')
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_type}_{payment} has been fulfilled for {self}.')
elif order.ft_order_side == 'stoploss' and order.status not in ('open', ):
self.close_rate_requested = self.stop_loss
self.exit_reason = ExitType.STOPLOSS_ON_EXCHANGE.value
if self.is_open and order.safe_filled > 0:
logger.info(f'{order_type} is hit for {self}.')
else:
raise ValueError(f'Unknown order type: {order.order_type}')
if order.ft_order_side != self.entry_side:
amount_tr = amount_to_contract_precision(self.amount, self.amount_precision,
self.precision_mode, self.contract_size)
if (
isclose(order.safe_amount_after_fee, amount_tr, abs_tol=MATH_CLOSE_PREC)
or (not recalculating and order.safe_amount_after_fee > amount_tr)
):
# When recalculating a trade, only coming out to 0 can force a close
self.close(order.safe_price)
else:
self.recalc_trade_from_orders()
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 self._date_last_filled_utc or dt_now()
self.is_open = False
self.exit_order_status = 'closed'
self.recalc_trade_from_orders(is_closing=True)
if show_msg:
logger.info(f"Marking {self} as closed as the trade is fulfilled "
"and found no open orders for it.")
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_canceled_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
and o.status in CANCELED_EXCHANGE_STATES])
def _calc_open_trade_value(self, amount: float, open_rate: float) -> float:
"""
Calculate the open_rate including open_fee.
:return: Price in of the open trade incl. Fees
"""
open_trade = FtPrecise(amount) * FtPrecise(open_rate)
fees = open_trade * FtPrecise(self.fee_open)
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.
Must be called whenever open_rate, fee_open is changed.
"""
self.open_trade_value = self._calc_open_trade_value(self.amount, self.open_rate)
def calculate_interest(self) -> FtPrecise:
"""
Calculate interest for this trade. Only applicable for Margin trading.
"""
zero = FtPrecise(0.0)
# 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)
sec_per_hour = FtPrecise(3600)
total_seconds = FtPrecise((now - open_date).total_seconds())
hours = total_seconds / sec_per_hour or zero
rate = FtPrecise(self.interest_rate)
borrowed = FtPrecise(self.borrowed)
return interest(exchange_name=self.exchange, borrowed=borrowed, rate=rate, hours=hours)
def _calc_base_close(self, amount: FtPrecise, rate: float, fee: Optional[float]) -> FtPrecise:
close_trade = amount * FtPrecise(rate)
fees = close_trade * FtPrecise(fee or 0.0)
if self.is_short:
return close_trade + fees
else:
return close_trade - fees
def calc_close_trade_value(self, rate: float, amount: Optional[float] = None) -> float:
"""
Calculate the Trade's close value including fees
:param rate: rate to compare with.
:return: value in stake currency of the open trade
"""
if rate is None and not self.close_rate:
return 0.0
amount1 = FtPrecise(amount or self.amount)
trading_mode = self.trading_mode or TradingMode.SPOT
if trading_mode == TradingMode.SPOT:
return float(self._calc_base_close(amount1, rate, self.fee_close))
elif (trading_mode == TradingMode.MARGIN):
total_interest = self.calculate_interest()
if self.is_short:
amount1 = amount1 + total_interest
return float(self._calc_base_close(amount1, rate, self.fee_close))
else:
# Currency already owned for longs, no need to purchase
return float(self._calc_base_close(amount1, rate, self.fee_close) - total_interest)
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:
return float(self._calc_base_close(amount1, rate, self.fee_close)) - funding_fees
else:
return float(self._calc_base_close(amount1, rate, self.fee_close)) + funding_fees
else:
raise OperationalException(
f"{self.trading_mode.value} trading is not yet available using freqtrade")
def calc_profit(self, rate: float, amount: Optional[float] = None,
open_rate: Optional[float] = None) -> float:
"""
Calculate the absolute profit in stake currency between Close and Open trade
Deprecated - only available for backwards compatibility
:param rate: close rate to compare with.
: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.
:return: profit in stake currency as float
"""
prof = self.calculate_profit(rate, amount, open_rate)
return prof.profit_abs
def calculate_profit(self, rate: float, amount: Optional[float] = None,
open_rate: Optional[float] = None) -> ProfitStruct:
"""
Calculate profit metrics (absolute, ratio, total, total ratio).
All calculations include fees.
:param rate: close rate to compare with.
: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.
:return: Profit structure, containing absolute and relative profits.
"""
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)
if self.is_short:
profit_abs = open_trade_value - close_trade_value
else:
profit_abs = close_trade_value - open_trade_value
try:
if self.is_short:
profit_ratio = (1 - (close_trade_value / open_trade_value)) * self.leverage
else:
profit_ratio = ((close_trade_value / open_trade_value) - 1) * self.leverage
profit_ratio = float(f"{profit_ratio:.8f}")
except ZeroDivisionError:
profit_ratio = 0.0
total_profit_abs = profit_abs + self.realized_profit
total_profit_ratio = (
(total_profit_abs / self.max_stake_amount) * self.leverage
if self.max_stake_amount else 0.0
)
total_profit_ratio = float(f"{total_profit_ratio:.8f}")
profit_abs = float(f"{profit_abs:.8f}")
return ProfitStruct(
profit_abs=profit_abs,
profit_ratio=profit_ratio,
total_profit=profit_abs + self.realized_profit,
total_profit_ratio=total_profit_ratio,
)
def calc_profit_ratio(
self, rate: float, amount: Optional[float] = None,
open_rate: Optional[float] = None) -> float:
"""
Calculates the profit as ratio (including fee).
:param rate: rate to compare with.
: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.
:return: profit ratio as float
"""
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)
short_close_zero = (self.is_short and close_trade_value == 0.0)
long_close_zero = (not self.is_short and open_trade_value == 0.0)
if (short_close_zero or long_close_zero):
return 0.0
else:
if self.is_short:
profit_ratio = (1 - (close_trade_value / open_trade_value)) * self.leverage
else:
profit_ratio = ((close_trade_value / open_trade_value) - 1) * self.leverage
return float(f"{profit_ratio:.8f}")
def recalc_trade_from_orders(self, *, is_closing: bool = False):
ZERO = FtPrecise(0.0)
current_amount = FtPrecise(0.0)
current_stake = FtPrecise(0.0)
max_stake_amount = FtPrecise(0.0)
total_stake = 0.0 # Total stake after all buy orders (does not subtract!)
avg_price = FtPrecise(0.0)
close_profit = 0.0
close_profit_abs = 0.0
# Reset funding fees
self.funding_fees = 0.0
funding_fees = 0.0
ordercount = len(self.orders) - 1
for i, o in enumerate(self.orders):
if o.ft_is_open or not o.filled:
continue
funding_fees += (o.funding_fee or 0.0)
tmp_amount = FtPrecise(o.safe_amount_after_fee)
tmp_price = FtPrecise(o.safe_price)
is_exit = o.ft_order_side != self.entry_side
side = FtPrecise(-1 if is_exit else 1)
if tmp_amount > ZERO and tmp_price is not None:
current_amount += tmp_amount * side
price = avg_price if is_exit else tmp_price
current_stake += price * tmp_amount * side
if current_amount > ZERO and not is_exit:
avg_price = current_stake / current_amount
if is_exit:
# Process exits
if i == ordercount and is_closing:
# Apply funding fees only to the last closing order
self.funding_fees = funding_fees
exit_rate = o.safe_price
exit_amount = o.safe_amount_after_fee
prof = self.calculate_profit(exit_rate, exit_amount, float(avg_price))
close_profit_abs += prof.profit_abs
if total_stake > 0:
# This needs to be calculated based on the last occurring exit to be aligned
# with realized_profit.
close_profit = (close_profit_abs / total_stake) * self.leverage
else:
total_stake = total_stake + self._calc_open_trade_value(tmp_amount, price)
max_stake_amount += (tmp_amount * price)
self.funding_fees = funding_fees
self.max_stake_amount = float(max_stake_amount)
if close_profit:
self.close_profit = close_profit
self.realized_profit = close_profit_abs
self.close_profit_abs = prof.profit_abs
current_amount_tr = amount_to_contract_precision(
float(current_amount), self.amount_precision, self.precision_mode, self.contract_size)
if current_amount_tr > 0.0:
# Trade is still open
# Leverage not updated, as we don't allow changing leverage through DCA at the moment.
self.open_rate = float(current_stake / current_amount)
self.amount = current_amount_tr
self.stake_amount = float(current_stake) / (self.leverage or 1.0)
self.fee_open_cost = self.fee_open * float(current_stake)
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)
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
self.close_profit_abs = close_profit_abs
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
def select_order(self, order_side: Optional[str] = None,
is_open: Optional[bool] = None, only_filled: bool = False) -> Optional[Order]:
"""
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?
:param only_filled: Only search for Filled orders (only valid with is_open=False).
:return: latest Order object if it exists, else None
"""
orders = self.orders
if order_side:
orders = [o for o in orders if o.ft_order_side == order_side]
if is_open is not None:
orders = [o for o in orders if o.ft_is_open == is_open]
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]
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 order side.
Will not return open orders which already partially filled.
: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))
and o.ft_is_open is False
and o.filled
and o.status in NON_OPEN_EXCHANGE_STATES]
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)
]
def set_custom_data(self, key: str, value: Any) -> None:
"""
Set custom data for this trade
:param key: key of the custom data
:param value: value of the custom data (must be JSON serializable)
"""
CustomDataWrapper.set_custom_data(trade_id=self.id, key=key, value=value)
def get_custom_data(self, key: str, default: Any = None) -> Any:
"""
Get custom data for this trade
:param key: key of the custom data
"""
data = CustomDataWrapper.get_custom_data(trade_id=self.id, key=key)
if data:
return data[0].value
return default
def get_custom_data_entry(self, key: str) -> Optional[_CustomData]:
"""
Get custom data for this trade
:param key: key of the custom data
"""
data = CustomDataWrapper.get_custom_data(trade_id=self.id, key=key)
if data:
return data[0]
return None
def get_all_custom_data(self) -> List[_CustomData]:
"""
Get all custom data for this trade
"""
return CustomDataWrapper.get_custom_data(trade_id=self.id)
@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
def sell_reason(self) -> Optional[str]:
""" DEPRECATED! Please use exit_reason instead."""
return self.exit_reason
@property
def safe_close_rate(self) -> float:
return self.close_rate or self.close_rate_requested or 0.0
@staticmethod
def get_trades_proxy(*, pair: Optional[str] = None, is_open: Optional[bool] = None,
open_date: Optional[datetime] = None,
close_date: Optional[datetime] = None,
) -> 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.
: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.
: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)
LocalTrade.bt_trades_open_pp[trade.pair].remove(trade)
LocalTrade.bt_open_open_trade_count -= 1
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)
LocalTrade.bt_trades_open_pp[trade.pair].append(trade)
LocalTrade.bt_open_open_trade_count += 1
else:
LocalTrade.trades.append(trade)
@staticmethod
def remove_bt_trade(trade):
LocalTrade.trades_open.remove(trade)
LocalTrade.bt_trades_open_pp[trade.pair].remove(trade)
LocalTrade.bt_open_open_trade_count -= 1
@staticmethod
def get_open_trades() -> List[Any]:
"""
Retrieve open trades
"""
return Trade.get_trades_proxy(is_open=True)
@staticmethod
def get_open_trade_count() -> int:
"""
get open trade count
"""
if Trade.use_db:
return Trade.session.execute(
select(func.count(Trade.id)).filter(Trade.is_open.is_(True))
).scalar_one()
else:
return LocalTrade.bt_open_open_trade_count
@staticmethod
def stoploss_reinitialization(desired_stoploss: float):
"""
Adjust initial Stoploss to desired stoploss for all open trades.
"""
trade: Trade
for trade in Trade.get_open_trades():
logger.info(f"Found open trade: {trade}")
# skip case if trailing-stop changed the stoploss already.
if (not trade.is_stop_loss_trailing
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 = 0.0
trade.initial_stop_loss_pct = None
trade.adjust_stop_loss(trade.open_rate, desired_stoploss)
logger.info(f"New stoploss: {trade.stop_loss}.")
@classmethod
def from_json(cls, json_str: str) -> Self:
"""
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 = cls(
__FROM_JSON=True,
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"],
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"],
amount_precision=data.get('amount_precision', None),
price_precision=data.get('price_precision', None),
precision_mode=data.get('precision_mode', None),
contract_size=data.get('contract_size', None),
)
for order in data["orders"]:
order_obj = Order(
amount=order["amount"],
ft_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"],
order_date=datetime.strptime(order["order_date"], DATETIME_PRINT_FORMAT),
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"],
ft_price=order["price"],
remaining=order["remaining"],
funding_fee=order.get("funding_fee", None),
ft_order_tag=order.get("ft_order_tag", None),
)
trade.orders.append(order_obj)
return trade
class Trade(ModelBase, LocalTrade):
"""
Trade database model.
Also handles updating and querying trades
Note: Fields must be aligned with LocalTrade class
"""
__tablename__ = 'trades'
session: ClassVar[SessionType]
use_db: bool = True
id: Mapped[int] = mapped_column(Integer, primary_key=True) # type: ignore
orders: Mapped[List[Order]] = relationship(
"Order", order_by="Order.id", cascade="all, delete-orphan", lazy="selectin",
innerjoin=True) # type: ignore
custom_data: Mapped[List[_CustomData]] = relationship(
"_CustomData", cascade="all, delete-orphan",
lazy="raise")
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
# open_trade_value - calculated via _calc_open_trade_value
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.now) # type: ignore
close_date: Mapped[Optional[datetime]] = mapped_column() # type: ignore
# absolute value of the stop loss
stop_loss: Mapped[float] = mapped_column(Float(), nullable=True, default=0.0) # type: ignore
# percentage value of the stop loss
stop_loss_pct: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
# absolute value of the initial stop loss
initial_stop_loss: Mapped[Optional[float]] = mapped_column(
Float(), nullable=True, default=0.0) # type: ignore
# percentage value of the initial stop loss
initial_stop_loss_pct: Mapped[Optional[float]] = mapped_column(
Float(), nullable=True) # type: ignore
is_stop_loss_trailing: Mapped[bool] = mapped_column(
nullable=False, default=False) # type: ignore
# absolute value of the highest reached price
max_rate: Mapped[Optional[float]] = mapped_column(
Float(), nullable=True, default=0.0) # type: ignore
# Lowest price reached
min_rate: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
exit_reason: Mapped[Optional[str]] = mapped_column(
String(CUSTOM_TAG_MAX_LENGTH), 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(CUSTOM_TAG_MAX_LENGTH), 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
# Leverage trading properties
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
# Margin Trading Properties
interest_rate: Mapped[float] = mapped_column(
Float(), nullable=False, default=0.0) # type: ignore
# Futures properties
funding_fees: Mapped[Optional[float]] = mapped_column(
Float(), nullable=True, default=None) # type: ignore
funding_fee_running: Mapped[Optional[float]] = mapped_column(
Float(), nullable=True, default=None) # type: ignore
def __init__(self, **kwargs):
from_json = kwargs.pop('__FROM_JSON', None)
super().__init__(**kwargs)
if not from_json:
# Skip recalculation when loading from json
self.realized_profit = 0
self.recalc_open_trade_value()
@validates('enter_tag', 'exit_reason')
def validate_string_len(self, key, value):
max_len = getattr(self.__class__, key).prop.columns[0].type.length
if value and len(value) > max_len:
return value[:max_len]
return value
def delete(self) -> None:
for order in self.orders:
Order.session.delete(order)
CustomDataWrapper.delete_custom_data(trade_id=self.id)
Trade.session.delete(self)
Trade.commit()
@staticmethod
def commit():
Trade.session.commit()
@staticmethod
def rollback():
Trade.session.rollback()
@staticmethod
def get_trades_proxy(*, pair: Optional[str] = None, is_open: Optional[bool] = None,
open_date: Optional[datetime] = None,
close_date: Optional[datetime] = None,
) -> List['LocalTrade']:
"""
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))
return cast(List[LocalTrade], Trade.get_trades(trade_filter).all())
else:
return LocalTrade.get_trades_proxy(
pair=pair, is_open=is_open,
open_date=open_date,
close_date=close_date
)
@staticmethod
def get_trades_query(trade_filter=None, include_orders: bool = True) -> Select:
"""
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]
this_query = select(Trade).filter(*trade_filter)
else:
this_query = select(Trade)
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
@staticmethod
def get_trades(trade_filter=None, include_orders: bool = True) -> ScalarResult['Trade']:
"""
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
"""
query = Trade.get_trades_query(trade_filter, include_orders)
# this should remain split. if use_db is False, session is not available and the above will
# raise an exception.
return Trade.session.scalars(query)
@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:
total_profit = Trade.session.execute(
select(func.sum(Trade.close_profit_abs)).filter(Trade.is_open.is_(False))
).scalar_one()
else:
total_profit = sum(t.close_profit_abs # type: ignore
for t in LocalTrade.get_trades_proxy(is_open=False))
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:
total_open_stake_amount = Trade.session.scalar(
select(func.sum(Trade.stake_amount)).filter(Trade.is_open.is_(True))
)
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.
"""
filters: List = [Trade.is_open.is_(False)]
if minutes:
start_date = datetime.now(timezone.utc) - timedelta(minutes=minutes)
filters.append(Trade.close_date >= start_date)
pair_rates = Trade.session.execute(
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()
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.
"""
filters: List = [Trade.is_open.is_(False)]
if (pair is not None):
filters.append(Trade.pair == pair)
enter_tag_perf = Trade.session.execute(
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()
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.
"""
filters: List = [Trade.is_open.is_(False)]
if (pair is not None):
filters.append(Trade.pair == pair)
sell_tag_perf = Trade.session.execute(
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()
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.
"""
filters: List = [Trade.is_open.is_(False)]
if (pair is not None):
filters.append(Trade.pair == pair)
mix_tag_perf = Trade.session.execute(
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()
resp: 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"
if (exit_reason is not None and enter_tag is not None):
mix_tag = enter_tag + " " + exit_reason
i = 0
if not any(item["mix_tag"] == mix_tag for item in resp):
resp.append({'mix_tag': mix_tag,
'profit_ratio': profit,
'profit_pct': round(profit * 100, 2),
'profit_abs': profit_abs,
'count': count})
else:
while i < len(resp):
if resp[i]["mix_tag"] == mix_tag:
resp[i] = {
'mix_tag': mix_tag,
'profit_ratio': profit + resp[i]["profit_ratio"],
'profit_pct': round(profit + resp[i]["profit_ratio"] * 100, 2),
'profit_abs': profit_abs + resp[i]["profit_abs"],
'count': 1 + resp[i]["count"]
}
i += 1
return resp
@staticmethod
def get_best_pair(start_date: Optional[datetime] = None):
"""
Get best pair with closed trade.
NOTE: Not supported in Backtesting.
:returns: Tuple containing (pair, profit_sum)
"""
filters: List = [Trade.is_open.is_(False)]
if start_date:
filters.append(Trade.close_date >= start_date)
best_pair = Trade.session.execute(
select(
Trade.pair,
func.sum(Trade.close_profit).label('profit_sum')
).filter(*filters)
.group_by(Trade.pair)
.order_by(desc('profit_sum'))
).first()
return best_pair
@staticmethod
def get_trading_volume(start_date: Optional[datetime] = None) -> float:
"""
Get Trade volume based on Orders
NOTE: Not supported in Backtesting.
:returns: Tuple containing (pair, profit_sum)
"""
filters = [
Order.status == 'closed'
]
if start_date:
filters.append(Order.order_filled_date >= start_date)
trading_volume = Trade.session.execute(
select(
func.sum(Order.cost).label('volume')
).filter(
*filters
)).scalar_one()
return trading_volume or 0.0