""" This module contains class to define a RPC communications """ import logging from abc import abstractmethod from datetime import date, datetime, timedelta, timezone from math import isnan from typing import Any, Dict, Generator, List, Optional, Sequence, Tuple, Union import psutil from dateutil.relativedelta import relativedelta from dateutil.tz import tzlocal from numpy import inf, int64, mean, nan from pandas import DataFrame, NaT from sqlalchemy import func, select from freqtrade import __version__ from freqtrade.configuration.timerange import TimeRange from freqtrade.constants import CANCEL_REASON, DEFAULT_DATAFRAME_COLUMNS, Config from freqtrade.data.history import load_data from freqtrade.data.metrics import DrawDownResult, calculate_expectancy, calculate_max_drawdown from freqtrade.enums import ( CandleType, ExitCheckTuple, ExitType, MarketDirection, SignalDirection, State, TradingMode, ) from freqtrade.exceptions import ExchangeError, PricingError from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs from freqtrade.exchange.types import Tickers from freqtrade.loggers import bufferHandler from freqtrade.persistence import KeyStoreKeys, KeyValueStore, PairLocks, Trade from freqtrade.persistence.models import PairLock from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist from freqtrade.rpc.fiat_convert import CryptoToFiatConverter from freqtrade.rpc.rpc_types import RPCSendMsg from freqtrade.util import decimals_per_coin, dt_now, dt_ts_def, format_date, shorten_date from freqtrade.util.datetime_helpers import dt_humanize_delta from freqtrade.wallets import PositionWallet, Wallet logger = logging.getLogger(__name__) class RPCException(Exception): """ Should be raised with a rpc-formatted message in an _rpc_* method if the required state is wrong, i.e.: raise RPCException('*Status:* `no active trade`') """ def __init__(self, message: str) -> None: super().__init__(self) self.message = message def __str__(self): return self.message def __json__(self): return {"msg": self.message} class RPCHandler: def __init__(self, rpc: "RPC", config: Config) -> None: """ Initializes RPCHandlers :param rpc: instance of RPC Helper class :param config: Configuration object :return: None """ self._rpc = rpc self._config: Config = config @property def name(self) -> str: """Returns the lowercase name of the implementation""" return self.__class__.__name__.lower() @abstractmethod def cleanup(self) -> None: """Cleanup pending module resources""" @abstractmethod def send_msg(self, msg: RPCSendMsg) -> None: """Sends a message to all registered rpc modules""" class RPC: """ RPC class can be used to have extra feature, like bot data, and access to DB data """ # Bind _fiat_converter if needed _fiat_converter: Optional[CryptoToFiatConverter] = None def __init__(self, freqtrade) -> None: """ Initializes all enabled rpc modules :param freqtrade: Instance of a freqtrade bot :return: None """ self._freqtrade = freqtrade self._config: Config = freqtrade.config if self._config.get("fiat_display_currency"): self._fiat_converter = CryptoToFiatConverter(self._config) @staticmethod def _rpc_show_config( config, botstate: Union[State, str], strategy_version: Optional[str] = None ) -> Dict[str, Any]: """ Return a dict of config options. Explicitly does NOT return the full config to avoid leakage of sensitive information via rpc. """ val = { "version": __version__, "strategy_version": strategy_version, "dry_run": config["dry_run"], "trading_mode": config.get("trading_mode", "spot"), "short_allowed": config.get("trading_mode", "spot") != "spot", "stake_currency": config["stake_currency"], "stake_currency_decimals": decimals_per_coin(config["stake_currency"]), "stake_amount": str(config["stake_amount"]), "available_capital": config.get("available_capital"), "max_open_trades": ( config.get("max_open_trades", 0) if config.get("max_open_trades", 0) != float("inf") else -1 ), "minimal_roi": config["minimal_roi"].copy() if "minimal_roi" in config else {}, "stoploss": config.get("stoploss"), "stoploss_on_exchange": config.get("order_types", {}).get( "stoploss_on_exchange", False ), "trailing_stop": config.get("trailing_stop"), "trailing_stop_positive": config.get("trailing_stop_positive"), "trailing_stop_positive_offset": config.get("trailing_stop_positive_offset"), "trailing_only_offset_is_reached": config.get("trailing_only_offset_is_reached"), "unfilledtimeout": config.get("unfilledtimeout"), "use_custom_stoploss": config.get("use_custom_stoploss"), "order_types": config.get("order_types"), "bot_name": config.get("bot_name", "freqtrade"), "timeframe": config.get("timeframe"), "timeframe_ms": timeframe_to_msecs(config["timeframe"]) if "timeframe" in config else 0, "timeframe_min": ( timeframe_to_minutes(config["timeframe"]) if "timeframe" in config else 0 ), "exchange": config["exchange"]["name"], "strategy": config["strategy"], "force_entry_enable": config.get("force_entry_enable", False), "exit_pricing": config.get("exit_pricing", {}), "entry_pricing": config.get("entry_pricing", {}), "state": str(botstate), "runmode": config["runmode"].value, "position_adjustment_enable": config.get("position_adjustment_enable", False), "max_entry_position_adjustment": ( config.get("max_entry_position_adjustment", -1) if config.get("max_entry_position_adjustment") != float("inf") else -1 ), } return val def _rpc_trade_status(self, trade_ids: Optional[List[int]] = None) -> List[Dict[str, Any]]: """ Below follows the RPC backend it is prefixed with rpc_ to raise awareness that it is a remotely exposed function """ # Fetch open trades if trade_ids: trades: Sequence[Trade] = Trade.get_trades(trade_filter=Trade.id.in_(trade_ids)).all() else: trades = Trade.get_open_trades() if not trades: raise RPCException("no active trade") else: results = [] for trade in trades: current_profit_fiat: Optional[float] = None total_profit_fiat: Optional[float] = None # prepare open orders details oo_details: Optional[str] = "" oo_details_lst = [ f"({oo.order_type} {oo.side} rem={oo.safe_remaining:.8f})" for oo in trade.open_orders if oo.ft_order_side not in ["stoploss"] ] oo_details = ", ".join(oo_details_lst) total_profit_abs = 0.0 total_profit_ratio: Optional[float] = None # calculate profit and send message to user if trade.is_open: try: current_rate = self._freqtrade.exchange.get_rate( trade.pair, side="exit", is_short=trade.is_short, refresh=False ) except (ExchangeError, PricingError): current_rate = nan if len(trade.select_filled_orders(trade.entry_side)) > 0: current_profit = current_profit_abs = current_profit_fiat = nan if not isnan(current_rate): prof = trade.calculate_profit(current_rate) current_profit = prof.profit_ratio current_profit_abs = prof.profit_abs total_profit_abs = prof.total_profit total_profit_ratio = prof.total_profit_ratio else: current_profit = current_profit_abs = current_profit_fiat = 0.0 else: # Closed trade ... current_rate = trade.close_rate current_profit = trade.close_profit or 0.0 current_profit_abs = trade.close_profit_abs or 0.0 # Calculate fiat profit if not isnan(current_profit_abs) and self._fiat_converter: current_profit_fiat = self._fiat_converter.convert_amount( current_profit_abs, self._freqtrade.config["stake_currency"], self._freqtrade.config["fiat_display_currency"], ) total_profit_fiat = self._fiat_converter.convert_amount( total_profit_abs, self._freqtrade.config["stake_currency"], self._freqtrade.config["fiat_display_currency"], ) # Calculate guaranteed profit (in case of trailing stop) stop_entry = trade.calculate_profit(trade.stop_loss) stoploss_entry_dist = stop_entry.profit_abs stoploss_entry_dist_ratio = stop_entry.profit_ratio # calculate distance to stoploss stoploss_current_dist = trade.stop_loss - current_rate stoploss_current_dist_ratio = stoploss_current_dist / current_rate trade_dict = trade.to_json() trade_dict.update( dict( close_profit=trade.close_profit if not trade.is_open else None, current_rate=current_rate, profit_ratio=current_profit, profit_pct=round(current_profit * 100, 2), profit_abs=current_profit_abs, profit_fiat=current_profit_fiat, total_profit_abs=total_profit_abs, total_profit_fiat=total_profit_fiat, total_profit_ratio=total_profit_ratio, stoploss_current_dist=stoploss_current_dist, stoploss_current_dist_ratio=round(stoploss_current_dist_ratio, 8), stoploss_current_dist_pct=round(stoploss_current_dist_ratio * 100, 2), stoploss_entry_dist=stoploss_entry_dist, stoploss_entry_dist_ratio=round(stoploss_entry_dist_ratio, 8), open_orders=oo_details, ) ) results.append(trade_dict) return results def _rpc_status_table( self, stake_currency: str, fiat_display_currency: str ) -> Tuple[List, List, float]: trades: List[Trade] = Trade.get_open_trades() nonspot = self._config.get("trading_mode", TradingMode.SPOT) != TradingMode.SPOT if not trades: raise RPCException("no active trade") else: trades_list = [] fiat_profit_sum = nan for trade in trades: # calculate profit and send message to user try: current_rate = self._freqtrade.exchange.get_rate( trade.pair, side="exit", is_short=trade.is_short, refresh=False ) except (PricingError, ExchangeError): current_rate = nan trade_profit = nan profit_str = f"{nan:.2%}" else: if trade.nr_of_successful_entries > 0: profit = trade.calculate_profit(current_rate) trade_profit = profit.profit_abs profit_str = f"{profit.profit_ratio:.2%}" else: trade_profit = 0.0 profit_str = f"{0.0:.2f}" direction_str = ("S" if trade.is_short else "L") if nonspot else "" if self._fiat_converter: fiat_profit = self._fiat_converter.convert_amount( trade_profit, stake_currency, fiat_display_currency ) if not isnan(fiat_profit): profit_str += f" ({fiat_profit:.2f})" fiat_profit_sum = ( fiat_profit if isnan(fiat_profit_sum) else fiat_profit_sum + fiat_profit ) else: profit_str += f" ({trade_profit:.2f})" fiat_profit_sum = ( trade_profit if isnan(fiat_profit_sum) else fiat_profit_sum + trade_profit ) active_attempt_side_symbols = [ "*" if (oo and oo.ft_order_side == trade.entry_side) else "**" for oo in trade.open_orders ] # example: '*.**.**' trying to enter, exit and exit with 3 different orders active_attempt_side_symbols_str = ".".join(active_attempt_side_symbols) detail_trade = [ f"{trade.id} {direction_str}", trade.pair + active_attempt_side_symbols_str, shorten_date(dt_humanize_delta(trade.open_date_utc)), profit_str, ] if self._config.get("position_adjustment_enable", False): max_entry_str = "" if self._config.get("max_entry_position_adjustment", -1) > 0: max_entry_str = f"/{self._config['max_entry_position_adjustment'] + 1}" filled_entries = trade.nr_of_successful_entries detail_trade.append(f"{filled_entries}{max_entry_str}") trades_list.append(detail_trade) profitcol = "Profit" if self._fiat_converter: profitcol += " (" + fiat_display_currency + ")" else: profitcol += " (" + stake_currency + ")" columns = ["ID L/S" if nonspot else "ID", "Pair", "Since", profitcol] if self._config.get("position_adjustment_enable", False): columns.append("# Entries") return trades_list, columns, fiat_profit_sum def _rpc_timeunit_profit( self, timescale: int, stake_currency: str, fiat_display_currency: str, timeunit: str = "days", ) -> Dict[str, Any]: """ :param timeunit: Valid entries are 'days', 'weeks', 'months' """ start_date = datetime.now(timezone.utc).date() if timeunit == "weeks": # weekly start_date = start_date - timedelta(days=start_date.weekday()) # Monday if timeunit == "months": start_date = start_date.replace(day=1) def time_offset(step: int): if timeunit == "months": return relativedelta(months=step) return timedelta(**{timeunit: step}) if not (isinstance(timescale, int) and timescale > 0): raise RPCException("timescale must be an integer greater than 0") profit_units: Dict[date, Dict] = {} daily_stake = self._freqtrade.wallets.get_total_stake_amount() for day in range(0, timescale): profitday = start_date - time_offset(day) # Only query for necessary columns for performance reasons. trades = Trade.session.execute( select(Trade.close_profit_abs) .filter( Trade.is_open.is_(False), Trade.close_date >= profitday, Trade.close_date < (profitday + time_offset(1)), ) .order_by(Trade.close_date) ).all() curdayprofit = sum( trade.close_profit_abs for trade in trades if trade.close_profit_abs is not None ) # Calculate this periods starting balance daily_stake = daily_stake - curdayprofit profit_units[profitday] = { "amount": curdayprofit, "daily_stake": daily_stake, "rel_profit": round(curdayprofit / daily_stake, 8) if daily_stake > 0 else 0, "trades": len(trades), } data = [ { "date": key, "abs_profit": value["amount"], "starting_balance": value["daily_stake"], "rel_profit": value["rel_profit"], "fiat_value": ( self._fiat_converter.convert_amount( value["amount"], stake_currency, fiat_display_currency ) if self._fiat_converter else 0 ), "trade_count": value["trades"], } for key, value in profit_units.items() ] return { "stake_currency": stake_currency, "fiat_display_currency": fiat_display_currency, "data": data, } def _rpc_trade_history(self, limit: int, offset: int = 0, order_by_id: bool = False) -> Dict: """Returns the X last trades""" order_by: Any = Trade.id if order_by_id else Trade.close_date.desc() if limit: trades = Trade.session.scalars( Trade.get_trades_query([Trade.is_open.is_(False)]) .order_by(order_by) .limit(limit) .offset(offset) ) else: trades = Trade.session.scalars( Trade.get_trades_query([Trade.is_open.is_(False)]).order_by(Trade.close_date.desc()) ) output = [trade.to_json() for trade in trades] total_trades = Trade.session.scalar( select(func.count(Trade.id)).filter(Trade.is_open.is_(False)) ) return { "trades": output, "trades_count": len(output), "offset": offset, "total_trades": total_trades, } def _rpc_stats(self) -> Dict[str, Any]: """ Generate generic stats for trades in database """ def trade_win_loss(trade): if trade.close_profit > 0: return "wins" elif trade.close_profit < 0: return "losses" else: return "draws" trades = Trade.get_trades([Trade.is_open.is_(False)], include_orders=False) # Duration dur: Dict[str, List[float]] = {"wins": [], "draws": [], "losses": []} # Exit reason exit_reasons = {} for trade in trades: if trade.exit_reason not in exit_reasons: exit_reasons[trade.exit_reason] = {"wins": 0, "losses": 0, "draws": 0} exit_reasons[trade.exit_reason][trade_win_loss(trade)] += 1 if trade.close_date is not None and trade.open_date is not None: trade_dur = (trade.close_date - trade.open_date).total_seconds() dur[trade_win_loss(trade)].append(trade_dur) wins_dur = sum(dur["wins"]) / len(dur["wins"]) if len(dur["wins"]) > 0 else None draws_dur = sum(dur["draws"]) / len(dur["draws"]) if len(dur["draws"]) > 0 else None losses_dur = sum(dur["losses"]) / len(dur["losses"]) if len(dur["losses"]) > 0 else None durations = {"wins": wins_dur, "draws": draws_dur, "losses": losses_dur} return {"exit_reasons": exit_reasons, "durations": durations} def _rpc_trade_statistics( self, stake_currency: str, fiat_display_currency: str, start_date: Optional[datetime] = None ) -> Dict[str, Any]: """Returns cumulative profit statistics""" start_date = datetime.fromtimestamp(0) if start_date is None else start_date trade_filter = ( Trade.is_open.is_(False) & (Trade.close_date >= start_date) ) | Trade.is_open.is_(True) trades: Sequence[Trade] = Trade.session.scalars( Trade.get_trades_query(trade_filter, include_orders=False).order_by(Trade.id) ).all() profit_all_coin = [] profit_all_ratio = [] profit_closed_coin = [] profit_closed_ratio = [] durations = [] winning_trades = 0 losing_trades = 0 winning_profit = 0.0 losing_profit = 0.0 for trade in trades: current_rate: float = 0.0 if trade.close_date: durations.append((trade.close_date - trade.open_date).total_seconds()) if not trade.is_open: profit_ratio = trade.close_profit or 0.0 profit_abs = trade.close_profit_abs or 0.0 profit_closed_coin.append(profit_abs) profit_closed_ratio.append(profit_ratio) if profit_ratio >= 0: winning_trades += 1 winning_profit += profit_abs else: losing_trades += 1 losing_profit += profit_abs else: # Get current rate if len(trade.select_filled_orders(trade.entry_side)) == 0: # Skip trades with no filled orders continue try: current_rate = self._freqtrade.exchange.get_rate( trade.pair, side="exit", is_short=trade.is_short, refresh=False ) except (PricingError, ExchangeError): current_rate = nan profit_ratio = nan profit_abs = nan else: _profit = trade.calculate_profit(trade.close_rate or current_rate) profit_ratio = _profit.profit_ratio profit_abs = _profit.total_profit profit_all_coin.append(profit_abs) profit_all_ratio.append(profit_ratio) closed_trade_count = len([t for t in trades if not t.is_open]) best_pair = Trade.get_best_pair(start_date) trading_volume = Trade.get_trading_volume(start_date) # Prepare data to display profit_closed_coin_sum = round(sum(profit_closed_coin), 8) profit_closed_ratio_mean = float(mean(profit_closed_ratio) if profit_closed_ratio else 0.0) profit_closed_ratio_sum = sum(profit_closed_ratio) if profit_closed_ratio else 0.0 profit_closed_fiat = ( self._fiat_converter.convert_amount( profit_closed_coin_sum, stake_currency, fiat_display_currency ) if self._fiat_converter else 0 ) profit_all_coin_sum = round(sum(profit_all_coin), 8) profit_all_ratio_mean = float(mean(profit_all_ratio) if profit_all_ratio else 0.0) # Doing the sum is not right - overall profit needs to be based on initial capital profit_all_ratio_sum = sum(profit_all_ratio) if profit_all_ratio else 0.0 starting_balance = self._freqtrade.wallets.get_starting_balance() profit_closed_ratio_fromstart = 0 profit_all_ratio_fromstart = 0 if starting_balance: profit_closed_ratio_fromstart = profit_closed_coin_sum / starting_balance profit_all_ratio_fromstart = profit_all_coin_sum / starting_balance profit_factor = winning_profit / abs(losing_profit) if losing_profit else float("inf") winrate = (winning_trades / closed_trade_count) if closed_trade_count > 0 else 0 trades_df = DataFrame( [ { "close_date": format_date(trade.close_date), "close_date_dt": trade.close_date, "profit_abs": trade.close_profit_abs, } for trade in trades if not trade.is_open and trade.close_date ] ) expectancy, expectancy_ratio = calculate_expectancy(trades_df) drawdown = DrawDownResult() if len(trades_df) > 0: try: drawdown = calculate_max_drawdown( trades_df, value_col="profit_abs", date_col="close_date_dt", starting_balance=starting_balance, ) except ValueError: # ValueError if no losing trade. pass profit_all_fiat = ( self._fiat_converter.convert_amount( profit_all_coin_sum, stake_currency, fiat_display_currency ) if self._fiat_converter else 0 ) first_date = trades[0].open_date_utc if trades else None last_date = trades[-1].open_date_utc if trades else None num = float(len(durations) or 1) bot_start = KeyValueStore.get_datetime_value(KeyStoreKeys.BOT_START_TIME) return { "profit_closed_coin": profit_closed_coin_sum, "profit_closed_percent_mean": round(profit_closed_ratio_mean * 100, 2), "profit_closed_ratio_mean": profit_closed_ratio_mean, "profit_closed_percent_sum": round(profit_closed_ratio_sum * 100, 2), "profit_closed_ratio_sum": profit_closed_ratio_sum, "profit_closed_ratio": profit_closed_ratio_fromstart, "profit_closed_percent": round(profit_closed_ratio_fromstart * 100, 2), "profit_closed_fiat": profit_closed_fiat, "profit_all_coin": profit_all_coin_sum, "profit_all_percent_mean": round(profit_all_ratio_mean * 100, 2), "profit_all_ratio_mean": profit_all_ratio_mean, "profit_all_percent_sum": round(profit_all_ratio_sum * 100, 2), "profit_all_ratio_sum": profit_all_ratio_sum, "profit_all_ratio": profit_all_ratio_fromstart, "profit_all_percent": round(profit_all_ratio_fromstart * 100, 2), "profit_all_fiat": profit_all_fiat, "trade_count": len(trades), "closed_trade_count": closed_trade_count, "first_trade_date": format_date(first_date), "first_trade_humanized": dt_humanize_delta(first_date) if first_date else "", "first_trade_timestamp": dt_ts_def(first_date, 0), "latest_trade_date": format_date(last_date), "latest_trade_humanized": dt_humanize_delta(last_date) if last_date else "", "latest_trade_timestamp": dt_ts_def(last_date, 0), "avg_duration": str(timedelta(seconds=sum(durations) / num)).split(".")[0], "best_pair": best_pair[0] if best_pair else "", "best_rate": round(best_pair[1] * 100, 2) if best_pair else 0, # Deprecated "best_pair_profit_ratio": best_pair[1] if best_pair else 0, "winning_trades": winning_trades, "losing_trades": losing_trades, "profit_factor": profit_factor, "winrate": winrate, "expectancy": expectancy, "expectancy_ratio": expectancy_ratio, "max_drawdown": drawdown.relative_account_drawdown, "max_drawdown_abs": drawdown.drawdown_abs, "max_drawdown_start": format_date(drawdown.high_date), "max_drawdown_start_timestamp": dt_ts_def(drawdown.high_date), "max_drawdown_end": format_date(drawdown.low_date), "max_drawdown_end_timestamp": dt_ts_def(drawdown.low_date), "drawdown_high": drawdown.high_value, "drawdown_low": drawdown.low_value, "trading_volume": trading_volume, "bot_start_timestamp": dt_ts_def(bot_start, 0), "bot_start_date": format_date(bot_start), } def __balance_get_est_stake( self, coin: str, stake_currency: str, amount: float, balance: Wallet, tickers ) -> Tuple[float, float]: est_stake = 0.0 est_bot_stake = 0.0 if coin == stake_currency: est_stake = balance.total if self._config.get("trading_mode", TradingMode.SPOT) != TradingMode.SPOT: # in Futures, "total" includes the locked stake, and therefore all positions est_stake = balance.free est_bot_stake = amount else: pair = self._freqtrade.exchange.get_valid_pair_combination(coin, stake_currency) rate: Optional[float] = tickers.get(pair, {}).get("last", None) if rate: if pair.startswith(stake_currency) and not pair.endswith(stake_currency): rate = 1.0 / rate est_stake = rate * balance.total est_bot_stake = rate * amount return est_stake, est_bot_stake def _rpc_balance(self, stake_currency: str, fiat_display_currency: str) -> Dict: """Returns current account balance per crypto""" currencies: List[Dict] = [] total = 0.0 total_bot = 0.0 try: tickers: Tickers = self._freqtrade.exchange.get_tickers(cached=True) except ExchangeError: raise RPCException("Error getting current tickers.") open_trades: List[Trade] = Trade.get_open_trades() open_assets: Dict[str, Trade] = {t.safe_base_currency: t for t in open_trades} self._freqtrade.wallets.update(require_update=False) starting_capital = self._freqtrade.wallets.get_starting_balance() starting_cap_fiat = ( self._fiat_converter.convert_amount( starting_capital, stake_currency, fiat_display_currency ) if self._fiat_converter else 0 ) coin: str balance: Wallet for coin, balance in self._freqtrade.wallets.get_all_balances().items(): if not balance.total: continue trade = open_assets.get(coin, None) is_bot_managed = coin == stake_currency or trade is not None trade_amount = trade.amount if trade else 0 if coin == stake_currency: trade_amount = self._freqtrade.wallets.get_available_stake_amount() try: est_stake, est_stake_bot = self.__balance_get_est_stake( coin, stake_currency, trade_amount, balance, tickers ) except ValueError: continue total += est_stake if is_bot_managed: total_bot += est_stake_bot currencies.append( { "currency": coin, "free": balance.free, "balance": balance.total, "used": balance.used, "bot_owned": trade_amount, "est_stake": est_stake or 0, "est_stake_bot": est_stake_bot if is_bot_managed else 0, "stake": stake_currency, "side": "long", "position": 0, "is_bot_managed": is_bot_managed, "is_position": False, } ) symbol: str position: PositionWallet for symbol, position in self._freqtrade.wallets.get_all_positions().items(): total += position.collateral total_bot += position.collateral currencies.append( { "currency": symbol, "free": 0, "balance": 0, "used": 0, "position": position.position, "est_stake": position.collateral, "est_stake_bot": position.collateral, "stake": stake_currency, "side": position.side, "is_bot_managed": True, "is_position": True, } ) value = ( self._fiat_converter.convert_amount(total, stake_currency, fiat_display_currency) if self._fiat_converter else 0 ) value_bot = ( self._fiat_converter.convert_amount(total_bot, stake_currency, fiat_display_currency) if self._fiat_converter else 0 ) trade_count = len(Trade.get_trades_proxy()) starting_capital_ratio = (total_bot / starting_capital) - 1 if starting_capital else 0.0 starting_cap_fiat_ratio = (value_bot / starting_cap_fiat) - 1 if starting_cap_fiat else 0.0 return { "currencies": currencies, "total": total, "total_bot": total_bot, "symbol": fiat_display_currency, "value": value, "value_bot": value_bot, "stake": stake_currency, "starting_capital": starting_capital, "starting_capital_ratio": starting_capital_ratio, "starting_capital_pct": round(starting_capital_ratio * 100, 2), "starting_capital_fiat": starting_cap_fiat, "starting_capital_fiat_ratio": starting_cap_fiat_ratio, "starting_capital_fiat_pct": round(starting_cap_fiat_ratio * 100, 2), "trade_count": trade_count, "note": "Simulated balances" if self._freqtrade.config["dry_run"] else "", } def _rpc_start(self) -> Dict[str, str]: """Handler for start""" if self._freqtrade.state == State.RUNNING: return {"status": "already running"} self._freqtrade.state = State.RUNNING return {"status": "starting trader ..."} def _rpc_stop(self) -> Dict[str, str]: """Handler for stop""" if self._freqtrade.state == State.RUNNING: self._freqtrade.state = State.STOPPED return {"status": "stopping trader ..."} return {"status": "already stopped"} def _rpc_reload_config(self) -> Dict[str, str]: """Handler for reload_config.""" self._freqtrade.state = State.RELOAD_CONFIG return {"status": "Reloading config ..."} def _rpc_stopentry(self) -> Dict[str, str]: """ Handler to stop buying, but handle open trades gracefully. """ if self._freqtrade.state == State.RUNNING: # Set 'max_open_trades' to 0 self._freqtrade.config["max_open_trades"] = 0 self._freqtrade.strategy.max_open_trades = 0 return {"status": "No more entries will occur from now. Run /reload_config to reset."} def _rpc_reload_trade_from_exchange(self, trade_id: int) -> Dict[str, str]: """ Handler for reload_trade_from_exchange. Reloads a trade from it's orders, should manual interaction have happened. """ trade = Trade.get_trades(trade_filter=[Trade.id == trade_id]).first() if not trade: raise RPCException(f"Could not find trade with id {trade_id}.") self._freqtrade.handle_onexchange_order(trade) return {"status": "Reloaded from orders from exchange"} def __exec_force_exit( self, trade: Trade, ordertype: Optional[str], amount: Optional[float] = None ) -> bool: # Check if there is there are open orders trade_entry_cancelation_registry = [] for oo in trade.open_orders: trade_entry_cancelation_res = {"order_id": oo.order_id, "cancel_state": False} order = self._freqtrade.exchange.fetch_order(oo.order_id, trade.pair) if order["side"] == trade.entry_side: fully_canceled = self._freqtrade.handle_cancel_enter( trade, order, oo, CANCEL_REASON["FORCE_EXIT"] ) trade_entry_cancelation_res["cancel_state"] = fully_canceled trade_entry_cancelation_registry.append(trade_entry_cancelation_res) if order["side"] == trade.exit_side: # Cancel order - so it is placed anew with a fresh price. self._freqtrade.handle_cancel_exit(trade, order, oo, CANCEL_REASON["FORCE_EXIT"]) if all(tocr["cancel_state"] is False for tocr in trade_entry_cancelation_registry): if trade.has_open_orders: # Order cancellation failed, so we can't exit. return False # Get current rate and execute sell current_rate = self._freqtrade.exchange.get_rate( trade.pair, side="exit", is_short=trade.is_short, refresh=True ) exit_check = ExitCheckTuple(exit_type=ExitType.FORCE_EXIT) order_type = ordertype or self._freqtrade.strategy.order_types.get( "force_exit", self._freqtrade.strategy.order_types["exit"] ) sub_amount: Optional[float] = None if amount and amount < trade.amount: # Partial exit ... min_exit_stake = self._freqtrade.exchange.get_min_pair_stake_amount( trade.pair, current_rate, trade.stop_loss_pct ) remaining = (trade.amount - amount) * current_rate if remaining < min_exit_stake: raise RPCException(f"Remaining amount of {remaining} would be too small.") sub_amount = amount self._freqtrade.execute_trade_exit( trade, current_rate, exit_check, ordertype=order_type, sub_trade_amt=sub_amount ) return True return False def _rpc_force_exit( self, trade_id: str, ordertype: Optional[str] = None, *, amount: Optional[float] = None ) -> Dict[str, str]: """ Handler for forceexit . Sells the given trade at current price """ if self._freqtrade.state != State.RUNNING: raise RPCException("trader is not running") with self._freqtrade._exit_lock: if trade_id == "all": # Execute exit for all open orders for trade in Trade.get_open_trades(): self.__exec_force_exit(trade, ordertype) Trade.commit() self._freqtrade.wallets.update() return {"result": "Created exit orders for all open trades."} # Query for trade trade = Trade.get_trades( trade_filter=[ Trade.id == trade_id, Trade.is_open.is_(True), ] ).first() if not trade: logger.warning("force_exit: Invalid argument received") raise RPCException("invalid argument") result = self.__exec_force_exit(trade, ordertype, amount) Trade.commit() self._freqtrade.wallets.update() if not result: raise RPCException("Failed to exit trade.") return {"result": f"Created exit order for trade {trade_id}."} def _force_entry_validations(self, pair: str, order_side: SignalDirection): if not self._freqtrade.config.get("force_entry_enable", False): raise RPCException("Force_entry not enabled.") if self._freqtrade.state != State.RUNNING: raise RPCException("trader is not running") if order_side == SignalDirection.SHORT and self._freqtrade.trading_mode == TradingMode.SPOT: raise RPCException("Can't go short on Spot markets.") if pair not in self._freqtrade.exchange.get_markets(tradable_only=True): raise RPCException("Symbol does not exist or market is not active.") # Check if pair quote currency equals to the stake currency. stake_currency = self._freqtrade.config.get("stake_currency") if not self._freqtrade.exchange.get_pair_quote_currency(pair) == stake_currency: raise RPCException( f"Wrong pair selected. Only pairs with stake-currency {stake_currency} allowed." ) def _rpc_force_entry( self, pair: str, price: Optional[float], *, order_type: Optional[str] = None, order_side: SignalDirection = SignalDirection.LONG, stake_amount: Optional[float] = None, enter_tag: Optional[str] = "force_entry", leverage: Optional[float] = None, ) -> Optional[Trade]: """ Handler for forcebuy Buys a pair trade at the given or current price """ self._force_entry_validations(pair, order_side) # check if valid pair # check if pair already has an open pair trade: Optional[Trade] = Trade.get_trades( [Trade.is_open.is_(True), Trade.pair == pair] ).first() is_short = order_side == SignalDirection.SHORT if trade: is_short = trade.is_short if not self._freqtrade.strategy.position_adjustment_enable: raise RPCException(f"position for {pair} already open - id: {trade.id}") if trade.has_open_orders: raise RPCException( f"position for {pair} already open - id: {trade.id} " f"and has open order {','.join(trade.open_orders_ids)}" ) else: if Trade.get_open_trade_count() >= self._config["max_open_trades"]: raise RPCException("Maximum number of trades is reached.") if not stake_amount: # gen stake amount stake_amount = self._freqtrade.wallets.get_trade_stake_amount( pair, self._config["max_open_trades"] ) # execute buy if not order_type: order_type = self._freqtrade.strategy.order_types.get( "force_entry", self._freqtrade.strategy.order_types["entry"] ) with self._freqtrade._exit_lock: if self._freqtrade.execute_entry( pair, stake_amount, price, ordertype=order_type, trade=trade, is_short=is_short, enter_tag=enter_tag, leverage_=leverage, mode="pos_adjust" if trade else "initial", ): Trade.commit() trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first() return trade else: raise RPCException(f"Failed to enter position for {pair}.") def _rpc_cancel_open_order(self, trade_id: int): if self._freqtrade.state != State.RUNNING: raise RPCException("trader is not running") with self._freqtrade._exit_lock: # Query for trade trade = Trade.get_trades( trade_filter=[ Trade.id == trade_id, Trade.is_open.is_(True), ] ).first() if not trade: logger.warning("cancel_open_order: Invalid trade_id received.") raise RPCException("Invalid trade_id.") if not trade.has_open_orders: logger.warning("cancel_open_order: No open order for trade_id.") raise RPCException("No open order for trade_id.") for open_order in trade.open_orders: try: order = self._freqtrade.exchange.fetch_order(open_order.order_id, trade.pair) except ExchangeError as e: logger.info(f"Cannot query order for {trade} due to {e}.", exc_info=True) raise RPCException("Order not found.") self._freqtrade.handle_cancel_order( order, open_order, trade, CANCEL_REASON["USER_CANCEL"] ) Trade.commit() def _rpc_delete(self, trade_id: int) -> Dict[str, Union[str, int]]: """ Handler for delete . Delete the given trade and close eventually existing open orders. """ with self._freqtrade._exit_lock: c_count = 0 trade = Trade.get_trades(trade_filter=[Trade.id == trade_id]).first() if not trade: logger.warning("delete trade: Invalid argument received") raise RPCException("invalid argument") # Try cancelling regular order if that exists for open_order in trade.open_orders: try: self._freqtrade.exchange.cancel_order(open_order.order_id, trade.pair) c_count += 1 except ExchangeError: pass # cancel stoploss on exchange orders ... if ( self._freqtrade.strategy.order_types.get("stoploss_on_exchange") and trade.has_open_sl_orders ): for oslo in trade.open_sl_orders: try: self._freqtrade.exchange.cancel_stoploss_order(oslo.order_id, trade.pair) c_count += 1 except ExchangeError: pass trade.delete() self._freqtrade.wallets.update() return { "result": "success", "trade_id": trade_id, "result_msg": f"Deleted trade {trade_id}. Closed {c_count} open orders.", "cancel_order_count": c_count, } def _rpc_list_custom_data(self, trade_id: int, key: Optional[str]) -> List[Dict[str, Any]]: # Query for trade trade = Trade.get_trades(trade_filter=[Trade.id == trade_id]).first() if trade is None: return [] # Query custom_data custom_data = [] if key: data = trade.get_custom_data(key=key) if data: custom_data = [data] else: custom_data = trade.get_all_custom_data() return [ { "id": data_entry.id, "ft_trade_id": data_entry.ft_trade_id, "cd_key": data_entry.cd_key, "cd_type": data_entry.cd_type, "cd_value": data_entry.cd_value, "created_at": data_entry.created_at, "updated_at": data_entry.updated_at, } for data_entry in custom_data ] def _rpc_performance(self) -> List[Dict[str, Any]]: """ Handler for performance. Shows a performance statistic from finished trades """ pair_rates = Trade.get_overall_performance() return pair_rates def _rpc_enter_tag_performance(self, pair: Optional[str]) -> List[Dict[str, Any]]: """ Handler for buy tag performance. Shows a performance statistic from finished trades """ return Trade.get_enter_tag_performance(pair) def _rpc_exit_reason_performance(self, pair: Optional[str]) -> List[Dict[str, Any]]: """ Handler for exit reason performance. Shows a performance statistic from finished trades """ return Trade.get_exit_reason_performance(pair) def _rpc_mix_tag_performance(self, pair: Optional[str]) -> List[Dict[str, Any]]: """ Handler for mix tag (enter_tag + exit_reason) performance. Shows a performance statistic from finished trades """ mix_tags = Trade.get_mix_tag_performance(pair) return mix_tags def _rpc_count(self) -> Dict[str, float]: """Returns the number of trades running""" if self._freqtrade.state != State.RUNNING: raise RPCException("trader is not running") trades = Trade.get_open_trades() return { "current": len(trades), "max": ( int(self._freqtrade.config["max_open_trades"]) if self._freqtrade.config["max_open_trades"] != float("inf") else -1 ), "total_stake": sum((trade.open_rate * trade.amount) for trade in trades), } def _rpc_locks(self) -> Dict[str, Any]: """Returns the current locks""" locks = PairLocks.get_pair_locks(None) return {"lock_count": len(locks), "locks": [lock.to_json() for lock in locks]} def _rpc_delete_lock( self, lockid: Optional[int] = None, pair: Optional[str] = None ) -> Dict[str, Any]: """Delete specific lock(s)""" locks: Sequence[PairLock] = [] if pair: locks = PairLocks.get_pair_locks(pair) if lockid: locks = PairLock.session.scalars(select(PairLock).filter(PairLock.id == lockid)).all() for lock in locks: lock.active = False lock.lock_end_time = datetime.now(timezone.utc) Trade.commit() return self._rpc_locks() def _rpc_add_lock( self, pair: str, until: datetime, reason: Optional[str], side: str ) -> PairLock: lock = PairLocks.lock_pair( pair=pair, until=until, reason=reason, side=side, ) return lock def _rpc_whitelist(self) -> Dict: """Returns the currently active whitelist""" res = { "method": self._freqtrade.pairlists.name_list, "length": len(self._freqtrade.active_pair_whitelist), "whitelist": self._freqtrade.active_pair_whitelist, } return res def _rpc_blacklist_delete(self, delete: List[str]) -> Dict: """Removes pairs from currently active blacklist""" errors = {} for pair in delete: if pair in self._freqtrade.pairlists.blacklist: self._freqtrade.pairlists.blacklist.remove(pair) else: errors[pair] = {"error_msg": f"Pair {pair} is not in the current blacklist."} resp = self._rpc_blacklist() resp["errors"] = errors return resp def _rpc_blacklist(self, add: Optional[List[str]] = None) -> Dict: """Returns the currently active blacklist""" errors = {} if add: for pair in add: if pair not in self._freqtrade.pairlists.blacklist: try: expand_pairlist([pair], self._freqtrade.exchange.get_markets().keys()) self._freqtrade.pairlists.blacklist.append(pair) except ValueError: errors[pair] = {"error_msg": f"Pair {pair} is not a valid wildcard."} else: errors[pair] = {"error_msg": f"Pair {pair} already in pairlist."} res = { "method": self._freqtrade.pairlists.name_list, "length": len(self._freqtrade.pairlists.blacklist), "blacklist": self._freqtrade.pairlists.blacklist, "blacklist_expanded": self._freqtrade.pairlists.expanded_blacklist, "errors": errors, } return res @staticmethod def _rpc_get_logs(limit: Optional[int]) -> Dict[str, Any]: """Returns the last X logs""" if limit: buffer = bufferHandler.buffer[-limit:] else: buffer = bufferHandler.buffer records = [ [ format_date(datetime.fromtimestamp(r.created)), r.created * 1000, r.name, r.levelname, r.message + ("\n" + r.exc_text if r.exc_text else ""), ] for r in buffer ] # Log format: # [logtime-formatted, logepoch, logger-name, loglevel, message \n + exception] # e.g. ["2020-08-27 11:35:01", 1598520901097.9397, # "freqtrade.worker", "INFO", "Starting worker develop"] return {"log_count": len(records), "logs": records} def _rpc_edge(self) -> List[Dict[str, Any]]: """Returns information related to Edge""" if not self._freqtrade.edge: raise RPCException("Edge is not enabled.") return self._freqtrade.edge.accepted_pairs() @staticmethod def _convert_dataframe_to_dict( strategy: str, pair: str, timeframe: str, dataframe: DataFrame, last_analyzed: datetime, selected_cols: Optional[List[str]], ) -> Dict[str, Any]: has_content = len(dataframe) != 0 dataframe_columns = list(dataframe.columns) signals = { "enter_long": 0, "exit_long": 0, "enter_short": 0, "exit_short": 0, } if has_content: if selected_cols is not None: # Ensure OHLCV columns are always present cols_set = set(DEFAULT_DATAFRAME_COLUMNS + list(signals.keys()) + selected_cols) df_cols = [col for col in dataframe_columns if col in cols_set] dataframe = dataframe.loc[:, df_cols] dataframe.loc[:, "__date_ts"] = dataframe.loc[:, "date"].astype(int64) // 1000 // 1000 # Move signal close to separate column when signal for easy plotting for sig_type in signals.keys(): if sig_type in dataframe.columns: mask = dataframe[sig_type] == 1 signals[sig_type] = int(mask.sum()) dataframe.loc[mask, f"_{sig_type}_signal_close"] = dataframe.loc[mask, "close"] # band-aid until this is fixed: # https://github.com/pandas-dev/pandas/issues/45836 datetime_types = ["datetime", "datetime64", "datetime64[ns, UTC]"] date_columns = dataframe.select_dtypes(include=datetime_types) for date_column in date_columns: # replace NaT with `None` dataframe[date_column] = dataframe[date_column].astype(object).replace({NaT: None}) dataframe = dataframe.replace({inf: None, -inf: None, nan: None}) res = { "pair": pair, "timeframe": timeframe, "timeframe_ms": timeframe_to_msecs(timeframe), "strategy": strategy, "all_columns": dataframe_columns, "columns": list(dataframe.columns), "data": dataframe.values.tolist(), "length": len(dataframe), "buy_signals": signals["enter_long"], # Deprecated "sell_signals": signals["exit_long"], # Deprecated "enter_long_signals": signals["enter_long"], "exit_long_signals": signals["exit_long"], "enter_short_signals": signals["enter_short"], "exit_short_signals": signals["exit_short"], "last_analyzed": last_analyzed, "last_analyzed_ts": int(last_analyzed.timestamp()), "data_start": "", "data_start_ts": 0, "data_stop": "", "data_stop_ts": 0, } if has_content: res.update( { "data_start": str(dataframe.iloc[0]["date"]), "data_start_ts": int(dataframe.iloc[0]["__date_ts"]), "data_stop": str(dataframe.iloc[-1]["date"]), "data_stop_ts": int(dataframe.iloc[-1]["__date_ts"]), } ) return res def _rpc_analysed_dataframe( self, pair: str, timeframe: str, limit: Optional[int], selected_cols: Optional[List[str]] ) -> Dict[str, Any]: """Analyzed dataframe in Dict form""" _data, last_analyzed = self.__rpc_analysed_dataframe_raw(pair, timeframe, limit) return RPC._convert_dataframe_to_dict( self._freqtrade.config["strategy"], pair, timeframe, _data, last_analyzed, selected_cols ) def __rpc_analysed_dataframe_raw( self, pair: str, timeframe: str, limit: Optional[int] ) -> Tuple[DataFrame, datetime]: """ Get the dataframe and last analyze from the dataprovider :param pair: The pair to get :param timeframe: The timeframe of data to get :param limit: The amount of candles in the dataframe """ _data, last_analyzed = self._freqtrade.dataprovider.get_analyzed_dataframe(pair, timeframe) _data = _data.copy() if limit: _data = _data.iloc[-limit:] return _data, last_analyzed def _ws_all_analysed_dataframes( self, pairlist: List[str], limit: Optional[int] ) -> Generator[Dict[str, Any], None, None]: """ Get the analysed dataframes of each pair in the pairlist. If specified, only return the most recent `limit` candles for each dataframe. :param pairlist: A list of pairs to get :param limit: If an integer, limits the size of dataframe If a list of string date times, only returns those candles :returns: A generator of dictionaries with the key, dataframe, and last analyzed timestamp """ timeframe = self._freqtrade.config["timeframe"] candle_type = self._freqtrade.config.get("candle_type_def", CandleType.SPOT) for pair in pairlist: dataframe, last_analyzed = self.__rpc_analysed_dataframe_raw(pair, timeframe, limit) yield {"key": (pair, timeframe, candle_type), "df": dataframe, "la": last_analyzed} def _ws_request_analyzed_df(self, limit: Optional[int] = None, pair: Optional[str] = None): """Historical Analyzed Dataframes for WebSocket""" pairlist = [pair] if pair else self._freqtrade.active_pair_whitelist return self._ws_all_analysed_dataframes(pairlist, limit) def _ws_request_whitelist(self): """Whitelist data for WebSocket""" return self._freqtrade.active_pair_whitelist @staticmethod def _rpc_analysed_history_full( config: Config, pair: str, timeframe: str, exchange, selected_cols: Optional[List[str]] ) -> Dict[str, Any]: timerange_parsed = TimeRange.parse_timerange(config.get("timerange")) from freqtrade.data.converter import trim_dataframe from freqtrade.data.dataprovider import DataProvider from freqtrade.resolvers.strategy_resolver import StrategyResolver strategy = StrategyResolver.load_strategy(config) startup_candles = strategy.startup_candle_count _data = load_data( datadir=config["datadir"], pairs=[pair], timeframe=timeframe, timerange=timerange_parsed, data_format=config["dataformat_ohlcv"], candle_type=config.get("candle_type_def", CandleType.SPOT), startup_candles=startup_candles, ) if pair not in _data: raise RPCException( f"No data for {pair}, {timeframe} in {config.get('timerange')} found." ) strategy.dp = DataProvider(config, exchange=exchange, pairlists=None) strategy.ft_bot_start() df_analyzed = strategy.analyze_ticker(_data[pair], {"pair": pair}) df_analyzed = trim_dataframe(df_analyzed, timerange_parsed, startup_candles=startup_candles) return RPC._convert_dataframe_to_dict( strategy.get_strategy_name(), pair, timeframe, df_analyzed.copy(), dt_now(), selected_cols, ) def _rpc_plot_config(self) -> Dict[str, Any]: if ( self._freqtrade.strategy.plot_config and "subplots" not in self._freqtrade.strategy.plot_config ): self._freqtrade.strategy.plot_config["subplots"] = {} return self._freqtrade.strategy.plot_config @staticmethod def _rpc_plot_config_with_strategy(config: Config) -> Dict[str, Any]: from freqtrade.resolvers.strategy_resolver import StrategyResolver strategy = StrategyResolver.load_strategy(config) # Manually load hyperparameters, as we don't call the bot-start callback. strategy.ft_load_hyper_params(False) if strategy.plot_config and "subplots" not in strategy.plot_config: strategy.plot_config["subplots"] = {} return strategy.plot_config @staticmethod def _rpc_sysinfo() -> Dict[str, Any]: return { "cpu_pct": psutil.cpu_percent(interval=1, percpu=True), "ram_pct": psutil.virtual_memory().percent, } def health(self) -> Dict[str, Optional[Union[str, int]]]: last_p = self._freqtrade.last_process res: Dict[str, Union[None, str, int]] = { "last_process": None, "last_process_loc": None, "last_process_ts": None, "bot_start": None, "bot_start_loc": None, "bot_start_ts": None, "bot_startup": None, "bot_startup_loc": None, "bot_startup_ts": None, } if last_p is not None: res.update( { "last_process": str(last_p), "last_process_loc": format_date(last_p.astimezone(tzlocal())), "last_process_ts": int(last_p.timestamp()), } ) if bot_start := KeyValueStore.get_datetime_value(KeyStoreKeys.BOT_START_TIME): res.update( { "bot_start": str(bot_start), "bot_start_loc": format_date(bot_start.astimezone(tzlocal())), "bot_start_ts": int(bot_start.timestamp()), } ) if bot_startup := KeyValueStore.get_datetime_value(KeyStoreKeys.STARTUP_TIME): res.update( { "bot_startup": str(bot_startup), "bot_startup_loc": format_date(bot_startup.astimezone(tzlocal())), "bot_startup_ts": int(bot_startup.timestamp()), } ) return res def _update_market_direction(self, direction: MarketDirection) -> None: self._freqtrade.strategy.market_direction = direction def _get_market_direction(self) -> MarketDirection: return self._freqtrade.strategy.market_direction