"""Kraken exchange subclass""" import logging from datetime import datetime from typing import Any, Dict, List, Optional, Tuple import ccxt from pandas import DataFrame from freqtrade.constants import BuySell from freqtrade.enums import MarginMode, TradingMode from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError from freqtrade.exchange import Exchange from freqtrade.exchange.common import retrier from freqtrade.exchange.types import Tickers logger = logging.getLogger(__name__) class Kraken(Exchange): _params: Dict = {"trading_agreement": "agree"} _ft_has: Dict = { "stoploss_on_exchange": True, "stop_price_param": "stopLossPrice", "stop_price_prop": "stopLossPrice", "stoploss_order_types": {"limit": "limit", "market": "market"}, "order_time_in_force": ["GTC", "IOC", "PO"], "ohlcv_candle_limit": 720, "ohlcv_has_history": False, "trades_pagination": "id", "trades_pagination_arg": "since", "trades_pagination_overlap": False, "mark_ohlcv_timeframe": "4h", } _supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [ # TradingMode.SPOT always supported and not required in this list # (TradingMode.MARGIN, MarginMode.CROSS), # (TradingMode.FUTURES, MarginMode.CROSS) ] 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: Optional[List[str]] = None, cached: bool = False) -> Tickers: # 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"], # 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 except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.OperationFailed, 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 def _set_leverage( self, leverage: float, pair: Optional[str] = None, accept_fail: bool = False, ): """ Kraken set's the leverage as an option in the order object, so we need to add it to params """ return def _get_params( self, side: BuySell, ordertype: str, leverage: float, reduceOnly: bool, time_in_force: str = "GTC", ) -> Dict: params = super()._get_params( side=side, ordertype=ordertype, leverage=leverage, reduceOnly=reduceOnly, time_in_force=time_in_force, ) if leverage > 1.0: params["leverage"] = round(leverage) if time_in_force == "PO": params.pop("timeInForce", None) params["postOnly"] = True return params def calculate_funding_fees( self, df: DataFrame, amount: float, is_short: bool, open_date: datetime, close_date: datetime, time_in_ratio: Optional[float] = None, ) -> float: """ # ! 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) return fees if is_short else -fees def _get_trade_pagination_next_value(self, trades: List[Dict]): """ Extract pagination id for the next "from_id" value Applies only to fetch_trade_history by id. """ if len(trades) > 0: if isinstance(trades[-1].get("info"), list) and len(trades[-1].get("info", [])) > 7: # Trade response's "last" value. return trades[-1].get("info", [])[-1] # Fall back to timestamp if info is somehow empty. return trades[-1].get("timestamp") return None def _valid_trade_pagination_id(self, pair: str, from_id: str) -> bool: """ Verify trade-pagination id is valid. Workaround for odd Kraken issue where ID is sometimes wrong. """ # Regular id's are in timestamp format 1705443695120072285 # If the id is smaller than 19 characters, it's not a valid timestamp. if len(from_id) >= 19: return True logger.debug(f"{pair} - trade-pagination id is not valid. Fallback to timestamp.") return False