stable/freqtrade/exchange/kraken.py

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""" Kraken exchange subclass """
import logging
from datetime import datetime
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from typing import Any, Dict, List, Optional, Tuple
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import ccxt
from pandas import DataFrame
from freqtrade.enums import MarginMode, TradingMode
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from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
OperationalException, TemporaryError)
from freqtrade.exchange import Exchange
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from freqtrade.exchange.common import retrier
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logger = logging.getLogger(__name__)
class Kraken(Exchange):
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_params: Dict = {"trading_agreement": "agree"}
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_ft_has: Dict = {
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"stoploss_on_exchange": True,
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"ohlcv_candle_limit": 720,
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"trades_pagination": "id",
"trades_pagination_arg": "since",
"mark_ohlcv_timeframe": "4h",
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}
_supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [
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# TradingMode.SPOT always supported and not required in this list
# (TradingMode.MARGIN, MarginMode.CROSS),
# (TradingMode.FUTURES, MarginMode.CROSS)
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]
def market_is_tradable(self, market: Dict[str, Any]) -> bool:
"""
Check if the market symbol is tradable by Freqtrade.
Default checks + check if pair is darkpool pair.
"""
parent_check = super().market_is_tradable(market)
return (parent_check and
market.get('darkpool', False) is False)
def get_tickers(self, symbols: List[str] = None, cached: bool = False) -> Dict:
# Only fetch tickers for current stake currency
# Otherwise the request for kraken becomes too large.
symbols = list(self.get_markets(quote_currencies=[self._config['stake_currency']]))
return super().get_tickers(symbols=symbols, cached=cached)
@retrier
def get_balances(self) -> dict:
if self._config['dry_run']:
return {}
try:
balances = self._api.fetch_balance()
# Remove additional info from ccxt results
balances.pop("info", None)
balances.pop("free", None)
balances.pop("total", None)
balances.pop("used", None)
orders = self._api.fetch_open_orders()
order_list = [(x["symbol"].split("/")[0 if x["side"] == "sell" else 1],
x["remaining"] if x["side"] == "sell" else x["remaining"] * x["price"],
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# Don't remove the below comment, this can be important for debugging
# x["side"], x["amount"],
) for x in orders]
for bal in balances:
if not isinstance(balances[bal], dict):
continue
balances[bal]['used'] = sum(order[1] for order in order_list if order[0] == bal)
balances[bal]['free'] = balances[bal]['total'] - balances[bal]['used']
return balances
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except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get balance due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
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def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
"""
Verify stop_loss against stoploss-order value (limit or price)
Returns True if adjustment is necessary.
"""
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return (order['type'] in ('stop-loss', 'stop-loss-limit') and (
(side == "sell" and stop_loss > float(order['price'])) or
(side == "buy" and stop_loss < float(order['price']))
))
@retrier(retries=0)
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def stoploss(self, pair: str, amount: float, stop_price: float,
order_types: Dict, side: str, leverage: float) -> Dict:
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"""
Creates a stoploss market order.
Stoploss market orders is the only stoploss type supported by kraken.
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TODO: investigate if this can be combined with generic implementation
(careful, prices are reversed)
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"""
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params = self._params.copy()
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if self.trading_mode == TradingMode.FUTURES:
params.update({'reduceOnly': True})
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if order_types.get('stoploss', 'market') == 'limit':
ordertype = "stop-loss-limit"
limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
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if side == "sell":
limit_rate = stop_price * limit_price_pct
else:
limit_rate = stop_price * (2 - limit_price_pct)
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params['price2'] = self.price_to_precision(pair, limit_rate)
else:
ordertype = "stop-loss"
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stop_price = self.price_to_precision(pair, stop_price)
if self._config['dry_run']:
dry_order = self.create_dry_run_order(
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pair, ordertype, side, amount, stop_price, leverage, stop_loss=True)
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return dry_order
try:
amount = self.amount_to_precision(pair, amount)
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order = self._api.create_order(symbol=pair, type=ordertype, side=side,
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amount=amount, price=stop_price, params=params)
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self._log_exchange_response('create_stoploss_order', order)
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logger.info('stoploss order added for %s. '
'stop price: %s.', pair, stop_price)
return order
except ccxt.InsufficientFunds as e:
raise InsufficientFundsError(
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f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
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f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
f'Message: {e}') from e
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
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f'Could not create {ordertype} {side} order on market {pair}. '
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f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
f'Message: {e}') from e
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except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
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except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
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f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
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except ccxt.BaseError as e:
raise OperationalException(e) from e
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def _set_leverage(
self,
leverage: float,
pair: Optional[str] = None,
trading_mode: Optional[TradingMode] = None
):
"""
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Kraken set's the leverage as an option in the order object, so we need to
add it to params
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"""
return
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def _get_params(
self,
ordertype: str,
leverage: float,
reduceOnly: bool,
time_in_force: str = 'gtc'
) -> Dict:
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params = super()._get_params(
ordertype=ordertype,
leverage=leverage,
reduceOnly=reduceOnly,
time_in_force=time_in_force,
)
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if leverage > 1.0:
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params['leverage'] = round(leverage)
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return params
def calculate_funding_fees(
self,
df: DataFrame,
amount: float,
is_short: bool,
open_date: datetime,
close_date: Optional[datetime] = None,
time_in_ratio: Optional[float] = None
) -> float:
"""
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# ! This method will always error when run by Freqtrade because time_in_ratio is never
# ! passed to _get_funding_fee. For kraken futures to work in dry run and backtesting
# ! functionality must be added that passes the parameter time_in_ratio to
# ! _get_funding_fee when using Kraken
calculates the sum of all funding fees that occurred for a pair during a futures trade
:param df: Dataframe containing combined funding and mark rates
as `open_fund` and `open_mark`.
:param amount: The quantity of the trade
:param is_short: trade direction
:param open_date: The date and time that the trade started
:param close_date: The date and time that the trade ended
:param time_in_ratio: Not used by most exchange classes
"""
if not time_in_ratio:
raise OperationalException(
f"time_in_ratio is required for {self.name}._get_funding_fee")
fees: float = 0
if not df.empty:
df = df[(df['date'] >= open_date) & (df['date'] <= close_date)]
fees = sum(df['open_fund'] * df['open_mark'] * amount * time_in_ratio)
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return fees if is_short else -fees